WO2016118810A1 - Medical logistic planning software - Google Patents

Abstract

The present invention is a software, methods, and system for creating and editing a medical logistics simulation model and for presenting the simulation model simulated within a military or disaster relief scenario. A user interface that allows a user to enter and edit platforms and associated attributes for a simulation model. The system runs the simulation model based on user input and historical data stored in databases using the inventive software. The present invention provides an output for allowing a user to view casualty rates, patient streams, and medical requirements or any other desired aspect of the simulation model.

Description

MEDICAL LOGISTIC PLANNING SOFTWARE

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001 ] This application is a continuation-in-part application of Patent App. No.

14/192,521 filed on 02/27/2014 (now pending), and claims priority to US Provisional

Application No. 62 107,072 filed on 01/23/2015.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] This invention was made with Government support under contracts W91 IQY-l l-D-0058 and N62645-12-C-4076 that were awarded by the OSD DHA, OPNAV (N81), and the Joint Staff. The Government has certain rights in the invention.

BACKGROUND

[0003] In today's military and emergency response operations, medical planners frequently encounter problems in accurately estimating illnesses, casualties and mortalities rates associated with an operation. Largely relying on anecdotal evidences and limited historical infomiation of similar operations, medical planners and medical system analysts don't have a way to scientifically and accurately projecting medical resources, and personnel requirements for an operational scenario. Inadequate medical logistic planning can lead to shortage of medical supplies, which may significantly impact the success of any military, humanitarian or disaster relief operation and could result in more casualties and higher mortality rates. Therefore, there is an urgent need for the development of a science based medical logistics and planning tool.

I [0004] Before the development of this invention, some useful, but not comprehensive medical modeling and simulation tools were used in attempts to virtually determine the minimum capability necessary in order to maximize medical outcomes, and ensure success of the militaiy medical plan, such as Ground Casualty Projection System (FORECAS) and the Medical Analysis Tool (MAT),

[0005] FORECAS produced casualty streams to forecast ground causalities. It provide medical planners with estimates of the average daily casualties, the maximum and minimum daily casualty load, the total number of casualties across an operation, and the overall casualty rate for a specified ground combat scenario. However, FORECAS does not specify the type of injury or take into account the time required for recover}'.

[0006] MAT and later the Joint Medical Analysis Tool (JMAT) consisted of two modules. One module was designed as a requirements estimator for the joint medical treatment environment while the other module was a course of action assessment tool Medical planners used MAT to generate medical requirements needed to support patient treatment within a joint warfighting operation. MAT could estimate the number of beds, the number of operating room tables, number and type of personnel, and the amount of blood required for casualty streams, but was mainly focused at the Theater Hospitalization level of care are definitive cares, which comprises of combat support hospitals in theaters (CSH) but does not include the forward medical facilities like the Battalion Aid Station or Surgical companies. Furthermore, MAT treated the theater medical capabilities as consisting of three levels of care, but failed to take into account medical treatment facilities (MTFs) at each level, their spatial arrangements on a battlefield, nor the transportation assets necessary to interconnect the network. Because MAT was a DOD-owned software program, it also did not include a civilian model. As MAT was designed to be used as a high-level planning tool, it does not have the capability to evaluate forward medical capabilities, or providing a realistic evaluation of mortality, JMAT, the MAT successor, failed V erifieation and Validation testing in August 2011 , and the program were cancelled by the Force Health Protection Integration Council. Other simulations were described by in report by Von Tersch et al. [1],

[0007J The existing simulation and modeling software provide useful information for preparing for a military mission, However, they lack the capability to model the flow of casualties within a specific network of treatment facilities from the generation of casualties, and through the treatment networks, and fails to provide critical simulation of the treatment times, and demands on consumable supplies, equipment, personnel, and transportation assets. There are no similar medical logistic tools are on the market for civilian medical rescue and humanitarian operations planning.

[0008] Military medical planners, civilian medical system analysts, clinicians and logisticians alike need a science-based, repeatabie, and standardized methodology for predicting the likelihood of injuries and illnesses, for creating casualty estimates and the associated patient streams, and for estimating the requirements relative to theater hospitalization to service that patient stream. These capability gaps undermine planning for medical support that is associated with both military and civilian medical operations.

SUMMARY OF INVENTION

[0009] An objective of this invention is the management of combat, humani tarian assistance (HA), disaster relief (DR.), shipboard, and fixed base PCOFs (patient condition occurrence frequencies) distribution Tables. [00010] Another objective of this invention is estimation of casualties in HA and DR missions, and in ground, shipboard, and fixed-base combat operations.

[00011] Yet another objective of this invention is the generation of realistic patient stream simulations for a HA and DR missions, and in ground, shipboard, and fixed-base combat operations,

[00012] Yet another objective of this invention is the estimation of medical requirements and consumables, such as operations rooms, intensive care units, and ward beds, evacuations, critical care air transport teams and blood products, based on anticipated patient load.

DETAILED DESCRIPTION OF THE DRAWINGS

[00013] FIG. 1 is a schematic view of a computer system (that is, a system largely made up of computers) in which software and/or methods of the present invention can be used.

[00014] FIG, 2 is a schematic view of a computer sub-system that is a constituent subsystem) of the computer system of FIG. 1), which represents a first embodiment of computer system for medical logistic planning according to the present invention.

[00 15] FIG. 3 High-level process diagram for PCOF tool.

[00016] FIG. 4 High-level process diagram for CREsT.

[00017] FIG. 5 Diagram showing troop strength adjustment factor.

[00018] FIG. 6 The logic diagram showing the process of Generation of wounded in action (WIA) casualties (i.e. Daily WIA patient counts).

[00019] FIG. 7 The logic diagram showing the process of Calculating (disease and nonbattle injuries) DNBI Casualties.

[00020] FIG. S High-level process diagram for Expeditionary Medicine Requirements Estimator (EMRE),

[00021] FIG. 9 The logic diagram showing the process of determining casualties requiring follow-up surgery.

[00022] FIG. 10 The logic diagram showing the process of determining casualties

requiring for evacuation.

[00023] FIG. 11 The logic diagram showing how EMRE calculates evacuation (Evacs) and hospital beds status.

[00024] FIG. 12 The logic diagram showing how EMRE determines casualty will return to duty (RID).

DETAILED DESCRIPTION OF THE INVENTION

Definitions

[00025] Common data are data stored in one or more database of the invention, which include EMRE common data, CREstT common data, and PCOF common data. The application contains tables labeling inputs used in different software modules and identify them if they are common data.

[00026] Patient Conditions (PCs) are used throughout MPTk to identify injuries and illnesses. The PCOF Tool is used to determine the probability of each patient condition occurring. CREstT creates a patient stream by assigning a PC to each casualty it generates. EMRE determines theater hospitalization requirements based on the resources required to treat each PC in a patient stream. All patient conditions in MPTk are codes from the International Classification of Diseases, Ninth Revision (ICD-9). MPTk currently supports 404 ICD-9 codes. additional 68 codes were added to this set to provide better coverage, primarily of diseases. In each of the three tools, the user can select to use the full set of PC codes or only the 336

DMMPO PC codes.

[00027] PCOF scenarios organize patient conditions and their probability of occurrence into major categories and subcategories, and allow for certain adjustment factors to affect the probability distribution of patient conditions. While baseline PCOF scenarios cannot be directly modified by the user, they can be copied and saved with a new name to create derived PCOF scenarios.

[00028] Derived PCOF scenarios, created from any baseline PCOF scenario, also organize the probability of patient conditions into major categories and subcategories affected by adjustment factors, all of which may be edited directly by the user.

[00029] Unstructured PCOF scenarios provide the user with a list of patient conditions and their probability of occurrence, but do not contain further categorization and are not adjusted by other factors. MPTk includes a number of unstructured PCOF scenarios built and approved by HRC, and these may not be directly modified by the user. However, the user may copy and save unstructured PCOF scenarios as new unstructured PCOF scenarios, and these may be modified by the user. Users may also create new unstructured PCOF scenarios from scratch.

[00(330] Any new derived or unstructured PCOF scenarios are saved to the database, and will appear in the PCOF scenario list with the baseline and unstructured PCOF scenarios that shipped with MPTk,

[00031 ] A scenario includes parameters of a planned medical support mission. The scenario may be created in PCOF, CREstT or EMllE modules. A user establishes a scenario by providing inputs and defines parameters of each individual module. [00032] Casualty count is each simulated casualty in MPTk, which may be labeled and maybe assigned a PC code,

[00033] Theater Hospitalization level of care are definitive care, which comprises of combat support hospitals in theaters(CSH) but does not include the forward medical facilities like the Battalion Aid Station or Surgical companies.

[00034] This invention relates to a system, method and software for creating military and civilian medical plans, and simulating operational scenarios, projecting medical operation estimations for a given scenario, and evaluating the adequacy of a medical logistic plan for combat, humanitarian assistance (HA) or disaster relief (DR) activities.

I. COMPUTE! SYSTEM AND HARDWARE

[00035] FIG. 1 shows an embodiment of the inventive system. A computer system 100 includes a server computer 102 and several client computers 104, 106, 108, which are connected by a communication network 1 12. Each server computer 102, is loaded with a medical planner's toolkit (MPTk) software and database 200. The MPTk software 200 will be discussed in greater detail, below. While the MPTk software and database of the present invention is illustrated as intaled entirely in the server computer! 02 in this embodiment, the MPTk software and database 200 could alternatively be located separately in whole or in part in one or more of the client computers 104, 106, 108 or in a computer readable medium,

[00036] As shown in FIG. 2, server computer 102 is a computing/processing device that includes internal components 800 and external components 900. The set of internal components 800 includes one or more processors 820, one or more computer-readable random access memories (RAMs) 822 and one or more computer-readable read-only memories (ROMs 824) on one or more buses 826, one or more operating systems 828 and one or more computer-readable storage devices 830, The one or more operating systems 828 and MPTk software/database 200 (see FIG, 1) are stored on one or more of the respective computer-readable storage devices 830 for execution by one or more of the respective processors 820 via one or more of the respective RAMs 822 (which typically include cache memory), in the illustrated embodiment, each of the computer-readable storage devices 830 is a magnetic disk storage device of an internal hard drive. Alternatively, each of the computer-readable storage devices 830 is a semiconductor storage device such as ROM 824, EPROM, flash memory or any other computer-readable storage device that can store but does not transmit a computer program and digital information.

[00037] Set of internal components 800 also includes a (read/write) R/W drive or interface 832 to read from and write to one or more portable computer-readable storage devices 936 that can store, but do not transmit, a computer program, such as a CD-ROM, DVD, memory stick, magnetic tape, magnetic disk, optical disk or semiconductor storage device. MPTk

software/database (see FIG. 1) can he stored on one or more of the respective portable computer- readable tangible storage devices 936, read via the respective R/W drive or interface 832 and loaded into the respective hard drive or semiconductor storage device 830, The term "computer- readable storage device" does not include a signal propagation media such as a copper cable, optical fiber or wireless transmission media.

[00038] Set of internal components 800 also includes a network adapter or interface 836 such as a TCP/IP adapter card or wireless communication adapter (such as a 4G wireless communication adapter using OFDMA technology). MPTk (see FIG. 1) can be downloaded to the respective computing/processing devices from an external computer or external storage device via a network (for example, the Internet, a local area network or other, wide area network or wireless network) and network adapter or interface 836. From the network adapter or interface 836, the MPTk software and database in whole or partially are loaded into the respective hard drive or semiconductor storage device 830. The network may comprise copper wires, optical fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers.

[00039] Set of external components 900 includes a display screen 920, a keyboard or keypad 930, and a computer mouse or touchpad 934. Sets of internal components 800 also includes device drivers 840 to interface to display screen 920 for imaging, to keyboard or keypad 930, to computer mouse or touchpad 934, and/or to display screen for pressure sensing of alphanumeric character entry and user selections. Device drivers 840, R/W drive or interface 832 and network adapter or interface 836 comprise hardware and software (stored in storage device 830 and/or ROM 824).

[00040] The invention also include an non-transitory computer-readable storage medium having stored thereon a program that when executed causes a computer to implement a plurality of modules for generate estimates of casualty, mortality and medical requirements of a future medical mission based at least partially on historical data stored on the at least one database, the plurality of modules comprising:

A) a patient condition occurrence frequency (PCOF) module that

i) receives information regarding a plurality of missions of a predefined scenario including PCOF data represented as a plurality sets of baseline PCOF distributions for the plurality of missions; ii) selects a set of baseline PCOF distributions for a future medical mission based on a user defined PCOF scenario;

ill) determines and presents to the user adjustment factors applicable to the user defined PCOF scenario;

iv) modifies said selected set of baseline PCOF distributions manually or using one or more PCOF adjustment factors defined by the user to create a set of customized PCOF distributions for the user defined PCOF scenario; and

v) provides the set of customized PCOF distributions and the corresponding the user defined PCOF scenario and PCOF adjustment factors for storage and presentation;

[00041] Various executable programs (such as PCOF, CREsT, and EMRE Modules of MPTk, see FIG. 1 ) can be written in various programming languages (such as Java, C÷) including low-level, high-level, object-oriented or non object-oriented languages. Alternatively, the functions of the MPTk can be implemented in whole or in part by computer circuits and other hardware (not shown).

[00042] The database 200 comprises PCOF common data, CREstT common data and EMRE common data. The common data are developed based on historical emperial data, and subject matter expert opinions. For example, empirical data were used to develop an updated list of patient conditions for use in modeling and simulation, logistics estimation, and planning analyses. Multiple Injury Wound codes were added to improve both scope and coverage of medical conditions. Inputs were identified as Common Data in tables throughout this application to distinguish from inputs there were user defined or inputed. [00043] For many years, analysts have used a standardized list of patient conditions for medical modeling and simulation. This list was developed by the Defense Health Agency Medical Logistics (DHA MED LOG) Division, formerly known as the Defense Medical Standardization Board, for medical modeling and simulation. This subset of International Classification of Diseases, 9th Revision (ICD-9) diagnostic codes was compiled before the advent of modern health encounter databases, and was intended to provide a comprehensive description of the illnesses and injuries likely to afflict U.S. sendee personnel Medical encounters from recent contingency operations, were compared to the Clinical Classification Software (CCS; 2014), a diagnosis and procedure categorization scheme developed by the Agency for Healthcare Research and Quality, to establish the hybrid database as an authoritative reference source of healthcare encounters in the expeditionary setting.

II. COMPUTER PROGRAMS MODULES OF THE MEDICAL PLANNER'S TOOLKIT (MPTK)

[00044] The inventive MPTk software comprises three modeling and simulation tools: the Patient Condition Occurrence Frequency Tool (PCOF), the Casualty Rate Estimation Tool (C EstT) and the Expeditionary Medicine Requirements Estimator (E RE), Used

independently, the three simulation tools provide individual reports on causality generation, patient stream, and medical planning requirements, which can each be used by medical system analysts or logisti elans and clinicians in different phases of medical operation planning. The three stimulation tools can also be used collectively as a toolkit to generate detailed simulations of different medical logistic plan designed for an operational scenario, which can be compared to enhance a medical planner's overall efficiency and accuracy, . A. Patient Condition Oecarreace Frequency Tool (FCOF)

[00045] The PCOF tool provides medical planners and logistieians with estimates of the distributions of injury and illness types for a range of military operations (ROMO). These missions include combat, noncombat, humanitarian assistance (HA), and disaster relief (DR) operations. Using the PCOF tool baseline distributions of a patient stream composition may be modified by the user either manually and/or via adjustment factors such as age, gender, country, region to better resemble the patient conditions of a planned operationalion, A PCOF table can provide the probability of injury and illness at the diagnostic code level. Specifically, each PCOF is a discrete probability distribution that provides the probability of a particular illness or injury. The PCOF tool was developed to produce precise expected patient condition probability distributions across the entire range of military operations, These missions include ground, shipboard, fixed-base combat, and HA and DR non-combat scenarios. The PCOF distributions are organized in three levels; International Classification of Diseases, Ninth Revision (ICD-9) category, ICD-9 subcategory, and patient condition (ICD-9 codes). Example of ICD-9 category, ICD-9 subcategory and patient condition may be dislocation, dislcocation of the finger, disclocation of Open dislocation of metacarpophalangeal (joint), respectively, These PCOF distribution tables for combat missions were developed using historical combat data. The major categories and sub-categories for the HA and DR missions were developed using a 2005 datasheet by the International Medical Corps from ReliefWeb (a United Nations Web site). Because the ICD-9 codes from this datasheet is restrictive to that particular mission, the categories, sub-categories, and ICD-9 codes for trauma and disease groups of HA and DR operations are further expanded to account for historical data gathered from other sources, and modified to be consistent with current U.S. Department of Defense (DoD) medical planning policies. Because the ICD-9 codes are not exclusively used for military combat operations, all DoD military combat ICD-9 codes are used for HA and DR. operation planning in conjunction with the additional HA and DR ICD-9 codes in the present invention. The PCOF tool can generate a report that may be used to for support supply block optimization, combat scenario medical supportability analysis, capability requirements analysis, and other similar analysis.

[00046] The high level process diagram of PCOF is shown in FIG. 3. The PCOF tool includes a baseline set of predefined injur and illness distributions (PCOFs) for a variety of missions. These baseline PCOFs are derived from historical data collected from military databases and other published literature. PCOF tool also allows the import of user-defined PCOF tables or adjustment using user applied adjustment factor.

[00047] Each baseline PCOF table specifies the percentage of a patient type in the baseline. In one embodiment of the PCOF tool, there are five patient-type categories: wounded in action (WIA), non-battle injury (NBI), disease (DIS), trauma (TRA), and killed in action (KIA). The user can alter these percentages to reflect the anticipated ratios of a patient steam in a planned operation scenario. Adjustment factors applied at the patient-type level affect the percentage of the probability mass in each patient-type category, but do not affect the distribution of probability mass at the ICD-9 category, ICD-9 subcategory or patient condition levels within the patient-type category. Changes at patient-type level may be entered by the user directly. Patient Type is a member of the set {DIS, WIA, NBI, TRA} and PCTDIS, PCTWIA, PCTNBJ and PCTTRA are the proportions of DIS, WIA, NBI, and TRA patients respectively.

Then for ground combat scenarios: PCTDB + PCTWIA + PCTNBI - 100%

Π and for non-combat scenarios:

PCTDB + PCTTRA ^:::: 100%

[00048] The PCOF tool also allows users to make this type of manual adjustment at the ICD-9 category and ICD-9 subcategory levels. At each level, total probability of each level (patient-type, ICD-9 category or ICDR-9 subcategory) must add up to 100% whether the adjustment is accomplished manually or througli adjustmem factors. In an embodiment, adjustment factors are applied at the ICD-9 category (designated as Cat in all equations). The equation below shows the manner in which adjustment factors (AFs) are applied.

Adjusted JCD9_Cattj = Baseline _ICD9_Cati * AF_tJ

Where: i is the index of ICD-9 categories, j is the index of adjustment factors, where / £ (age, gender, region, season, climate, income},

Adjusted JCD9_ Cati_j is the adjusted probability mass in ICD-9 category i due to adjustment factor AF) ,

Baseline ICD9_ Cati is the baseline probability mass in ICD-9 category i, and AFi is the adjustment factor for an ICD-9 category due to adjustment factor j. [00049] The change in each ICD-9 category is calculated for each adjustment factor that applies to that category. The manner in which this calculation is performed depends on the specific application of the adjustment factor. While some adjustment factors adjust all ICD-9 categories directly, a select few adjustment factors adjust certain ICD-9 categories, hold those values constant, and normalizes the remainder of the distribution. For the adjustmen t factors who adjust categories directly, the change calculation is performed according to the following;

Change JCD9__Cat_{i j} = Adjusted JCD9__Cat_u ~ Baseline_ICD9_Cati,

For the adjustment factors which hold certain values constant, the calculation is performed in the following manner.

Change JCD9_ Catij = Norm(AdjustedJCD9_Cati_j) ~ Baseline JCD9_Cat_h where Change CD9 at;_j is the change in the baseline value for ICD-9 category i due to adjustment factor j. NormQ refers to the normalization procedure expressed in detail in the section describing the adjustment factor for response phase.

The total adjustment to ICD-9 category i is:

Total jidji =∑_j Change JCD9S&t

Once all adjustment factors have been applied and their corresponding total adjustments (Total idji) calculated, they are applied to the baseline values (Baseline JCD9_ C-at^ to arrive at the raw adjusted value. This value is calculated as follows:

Raw_Adj_Val_ICD9jCati - Total_adjj + Baseline _ICD9_Cat V i

The ICD-9 categories are renormalized as follows: Final_ICD9_Cati = Raw_Adj_ValJCD9_Cati ∑_t Raw dj ValJCD9 at_i , V i The adjusted patient condition probability {Pc xdjusted is calculated as follows:

Pcjxdjusted = Pc >aseline * ICD9_subjcategory * Final_ ICD9_ Catj Where:

Pc baseline is the value of the proportion of the PC among the other PC's in ICD-9 subcategory i.

I(∑>9jwbjsategoiy is the value of the proportion of the ICD-9 subcategory among the subcategories that make up ICD-9 category i, and

Final CD9 Cati is calculated as above.

[00050] Users are able to alter scenario variables from the the graphic user interface (GUI). The tool calculates the appropriate adjustment factors based on this user input. Not all adjustment factors affect all ICD-9 categories. Furthermore, adjustment factors may not affect all of the injury types within an ICD-9 category. Table 0 displays the adjustment factors that affect patient types by scenario type.

Table 1 PCOF Adjustment Factors

Adjustment HA DR Ground Combat

factors Disease Trauma Disease Trauma Disease NB1 WIA

Age x x x

Gender x x x x x x x

Region x

Response

phase x x

Season x x x Country x x X X

Calculation for each adjustment factors are described in the following sections.

PCOF types affected: HA, DR

Patient types affected: disease, trauma

[00051] The age adjustment factor was determined using the Standard Ambulatory Data

Record (SADR); a repository of administrative data associated with outpatient visits by military health system beneficiaiies. This data is the baseline population in all calculations below. The data were organized by age into four groups:

1) ages less than 5 years, i = 1 ;

2) ages 5 to 15 years , i = 2

3) ages 16 to 65 years, i ~ 3; and

4) ages greater than 65 years, i - 4.

The age adjustment factor is determined as follows:

Let ί denote the age group, where i€ {1, 2, 3, 4}

Let m denote the index for ICD-9 categories, where m 6 (1, 2_».. M} and there are M distinct ICD-9 categories.

Let BaselineAgei be the percentage of age group in the population of the baseline distribution.

Let AdjustedAgei be the user-adjusted percentage of the population in age group i.

Let ICD9„C&t„Age_iim be the percentage of the SADR. population in age group i within ICD-9 category m.

The adjustment factors for age are calculated as follows:

PCOF types affected; HA, DR., and ground combat

Patient types affected: WIA, NBI, disease, and trauma

[00052] The gender adjustment factor was derived in a manner simiiai" to the age adjustment factor. The data source for the gender adjustment factor was SADR. The data were organized by gender:

Male, i = 0

Female, i™ 1

The gender adjustment factor is calculated as follows:

Let Base line Gender^ be the percentage of the gender group i in the baseline population, i e {0,1}.

Let AdjustedGendeTi be the user adjusted percentage of the population in gender group I. Let ICD9_C&t_Gender_iim be the percentage of the SADR population in gender group i within ICD-9 category m.

The adjustment factor is calculated as follows:

[00053] The "OB/GYN Disorders" major category is adjusted in the same manner as all other major categories. However, in the special case where the population is 100% male, the percentage of OB/GYN disorders is automatically set to zero, and all other major categories are renormalized (Recalculated so the percentages add to 100%.

Adjustment Factor for Region

PCOF types affected: ground combat

Patient types affected: disease

[00054] The regional adjustment factor was developed via an analysis of data from World War II. The World War II data was categorized by combatant command (CCMD) and organized into the major disease categories found in the FCOF. The World War II data comprise the baseline population referenced below.

[00055] Let CCMD_Baseu_nem be the percentage of the World War ΙΪ population comprising ICD-9 category m for the baseline CCMD of the scenario.

Let CCMD_{MjUSted m} be the percentage of the World War II population comprising ICD-9 category m for the user-adjusted CCMD of the scenario.

The adjustment factor is calculated as follows:

{CCMDg_aseii_neiJn

Where AF_m is the adjustment factor used to transition an ICD-9 category m from CCMDsasei to

CCMD Adjusted-

Response Phase

PCOF types affected: DR Patient types affected: disease and trauma

[00056] Response phase denotes the time frame within the event when aid arrives. For the purposes of this adjustment factor, response phases were broken down into three time windows and are described below.

1} Early Phase is from the day the event occurs to the following day.

2) Middle Phase is the third day to the 15th day.

3) Late Phase is any time period after the 15t!i day,

[00057] These phases are described in the Pan American Health Organization's manual on the use of Foreign Field Hospitals (2003). Response phase adjustment factors perform two functions. First, they adjust the ratio of disease to trauma. Second, unlike the adjustment factors discussed above, they only adjust the percentages of a small subset of the major categories rather than the entire PCOF. Subject matter expert (SME) input and reference articles were used to develop adjustment factors that adjust the most likely conditions affected by the response phase for both disease and trauma casualties. The conditions are shown in Table 0 and Table 0,

Table 2 Disease Major Categories Affected by Response Phase

Disease major category

Gastrointestinal disorders, k Ϊ

infectious diseases, k = 2

Respiratory disorders, k = 3

Skin disorders, k = 4

Table 3 Trauma Major Categories Affected by Response Phase Trauma major eate e;gories

Fractures, 1 = 1

Open wounds, 1 ^:::: 2

[00058] For the major categories, which are adjusted and held constant, the calculations are as follows.

Let k denote the index for ICD-9 categories adjusted by response phase for disease, where k £

{1, 2, 3, 4} and / denote the same for trauma, where / E {!, 2}.

Let x_k be the percentage of major category k, which will be adjusted and held constant.

Let y_n be the percentage of major category n, which will be normalized such that the distribution sums to 1 , where n 6 {1, 2,.. ,, N}.

Let a_k be the adjustment factor for major category k for disease and let ¾ be the adjustment factor for major category / for trauma, The calculations for the major categories, which are adjusted and held constant, are calculated according to the formulas below (the example is for disease; the same formulation applies to trauma).

{∑k:^ii^xk^ak) r

The calculations for the major categories, which are normalized so that the distribution sums to 1, are as follows (the example is for disease; the same formulation applies to trauma).

[00059] The adjustment factor was developed via SME input and has no closed form. There are unique adjustment factors for each of the six distinctive combinations of baseline and adjusted response phases,

[00060] There is also an adjustment to the disease-io-trauma ratio due to a change in response phase. For any change in response phase, the adjustment factor for disease is inversely proportional to the adjustment factor for trauma. Therefore, if the adjustment factor for disease is

8, the adjustment factor for trauma will be ~ = 0.125,

Table 0 denotes the adjustments to relative disease and trauma percentages. These values are then normalized so that they sum to 100%,

Table 4 Response Phase Disease-to-Trauma Ratio Adjustment Factor

Baselme respo&se Adjusted Disease Trauma

phase res onse hase adj s ment factor adjustment factor

Early Middle 4 0.25

Early Late 8 0.125

Middle Early 0.25 4

Middle Late 4 0.25

Late Early 0.125 8

Late Middle 0.25 4

Adjustment Factor for Season

Top Category Adjustment

PCOF types affected: HA, DR, and ground combat

Patient types affected: disease

[00061 ] The development of the seasonal adjustment factor was performed via the analysis of SADR data for HA and DR scenarios, and from Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF) for ground combat scenarios that had been parsed by- season. For ground combat PCOFs, the default season is always "All," implying that the operation spanned multiple or all seasons. For HA and DR PCOFs, the default season is set respective to the season in which the operation took place. For each combination of seasons in HA and DR scenarios, an odds ratio was developed that measures the likelihood of a condition occurring in the user-adjusted season to a reference season (the baseline). [00062] The HA and DR season adjustment factors is calculated as follows: Let SeasoriBaseUne be the percentage of the SADR population comprising ICD-9 category k for the scenario's baseline season. Where ' denotes the ICD-9 categories from Table 2 Let

^e percentage of the SADR population comprising ICD-9 category k for the scenario's user-adjusted season. Then: r\A D ,· Season_Adiust_edik * (1 - Season_Basslineik)

easQ7i_Saselim;ik * (1 - Season_Adjustedik) and,

AF__HADRSeason_k = 0dds_Ratio_Basellneik→_AdJustedik

[00063] The ground combat season adjustment factor is calculated as follows:

Let SeasoriBaseime.m &^e e percentage of the OIF or OEF population comprising ICD-9 category m for the scenario's baseline season.

Let Season iii_juste_d.m ^^{e e} percentage of the OIF or OEF population comprising ICD-9 category m for the scenario's user-adjusted season.

( Season_MjUSted>m)

AF CombatSeason m.

[00064] The ground combat seasonal adjustment factor aligns all of the disease major categories. After adjustment_s the major categories are normalized so thai the distribution sums to 100%. The HA and DR seasonal adjustment factor, as in the ease of the response phase adjustment factor, only affects a specified set of major categories. Specifi cally, the adjustment factor for season only affects the disease major categories outlined in Table 0. Additionally, as with the response phase adjustment factor, these major categories are adjusted and kept constant while the remainder of the PCOF is normalized.

Subcategory Adjustment

PCOF types affected: HA, DR, and ground combat Patient types affected: NBI, TRA

[00065] Season is the only adjustment factor which affects PCOFs on the ICD-9 subcategory level. For NBI and TRA patient types, the season adjustment factor changes the relative percentage of the "Heat" and "Cold" subcategories within the "Heat and Cold" top category. Heat injuries are more common during the summer and cold injuries are more common during the winter. As shown in Table 0, the heat and cold subcategory' percentages are determined using only the season. Individual PCOFs cannot have heat and cold percentages other than what is shown in the table 5.

Table 5 Season Subcategory Adjustments

Subcategory Pereerata

Heat 50%

Cold 50%

Heat 5%

Cold 95%

Heat 50% Spring Cold 50%

Summer Heat 95%

Summer Cold 5%

Fall Heat 50%

Fall Cold 50%

Adjustment Factor for Country PCOF types affected: HA and DR

Patient types affected: disease and trauma (trauma is adjusted through age and gender only) [00066] The selection of a country in the PCOF tool triggers four adjustment factors. The first adjustment factor combines region and climate. Each country is classified by region according to the CCMD in which it resides. Along with this is a categorizing of climate type according to the Koppen climate classification. Each combination of CCMD and climate was analyzed according to disability adjusted life years (DALYs), which are the number of years lost due to poor health, disability, or early death, and a disease distribution was formed. Each country within the same CCMD and climate combination shares the same DALY disease distribution for this adjustment factor,

[00067] The region and climate t pe adjustment factor is calculated as follows:

Let Region_Climate_8aseli_ne_im be the percentage of the DALY population comprising iCD-9 category m for the region and climate combination of the baseline country in the selected season.

Let RegionjClimateA_djuste_d,™ ^^ε percentage of the DALY population comprising ICD-9 category m for the region and climate combination of the user-adjusted country in the selected scenario.

Region_Cli teg_aseii_ne - Table 6 Climate Classifications for Country Adjustment Factor

Climate classification

Tropical

Dry/Desert

Temperate

Continental

[00068] The second adjustment factor accounts for the impact of economy in the selected countr}'-. Each country's economy was categorized according to the human development index, SME input was used to develop adjustment factors for three major categories (Table 0). As in the case of the response phase adjustment factor and HA and DR seasonal adjustment factor, these three major categories are adjusted and held constant while the remainder of the PCOF is renormalized.

Table 7 Income Classifications for Country Adjustment Factor

Lower Middle

Upper Middle

Table 8 Disease Major Categories Affected by Income

Gastrointestinal disorders

Infectious diseases

Respiratory disorders

[00069] There is also an adjustment to the disease-to-trauma ratio due to a change in

3fs income. The disease and trauma percentages will be adjusted when the selection of a new country changes the income group. Odenotes the adjustments that will he applied to the disease patient type percentage. After the disease percentage is multiplied by the adjustment factor, the disease and trauma percentages are renorrnalized to sum to 100%.

Table 9 Income Disease-to-Trauma Ratio Adjustment Factor

Baseiiae laeome Current Income Disease

adjustment factor

Low Lower Middle 1.050

Low Upper Middle 1.100

Low High 1.150

Lower Middle Low 0.952

Lower Middle Upper Middle 1.050

Lower Middle High 1.100

Upper Middle Low 0.909

Upper Middle Lower Middle 0.952

Upper Middle High 1.050

High Low 0.870

High Lower Middle 0.909

High Upper Middle 0.952

[00070] Finally, adjustment factors are applied for the change in age and gender. These adjustments are performed in the same manner as user-input changes to age and gender distribution (described above). However, instead of a user-input age or gender distribution, the age and gender distribution of the user-chosen country is used.

B. Casualty_, Rate Estimation Tool (CREstT) [00071] The Casualty Rate Estimation Tool (CREstT) provides user estimate casualties and injuries resulting from a combat and non-combat event. CREstT may be used to generate causlties estimates for ground combat operations, attacks on ships, attacks on fixed facilities, and casualties resulting from natural disasters. These estimates allow medical planners to assess their operation plans, tailor operational estimates using adjustment factors, and develop robust patient streams best mimicking that expected in the anticipated operation. CREstT also has an interface with the PCOF tool, and can use the distributions stored or developed in that application to produce patient streams. Its stochastic implementation provides users with percentile as well as median results to enable risk assessment. Reports from CREsT may be programed to present data in both tabular and graphical formats. Output data is available in a format that is compatible with EMRE, JMPT, and other tools. The high level process diagram of PCOF is shown in FIG, 4,

Estimate for Ground Combat Operations

[00072] Baseline ground combat casualty rate estimates are based on empirical data spanning from World War II through OEF, Baseline casualty rates are modified through the application of adjustment factors. Applications of the adjustment factors provide greater accuracy in the causulty rate estimates. The CREsT adjustment factors are based largely on research by Trevor N. Dupuy and the Dupuy institute (Dupuy, 1990). The Dupuy factors are weather, terrain, posture, troop size, opposition, surprise, sophistication, and pattern of operations, The factors included in CREstT are region, terrain, climate, battle intensity, troop type, and population at risk (PAR). Battle intensity is used in CREstT instead of opposition, surprise, and sophistication factors to model enemy strength factors.

[00073] Casualty estimates for ground combat operations in CREstT are calculated using the process depicted in FIG 4. The following sections outline the sub-processes and provide descriptions of inputs and outputs and the algorithms used in the estimation.

2g Calculate Baseline Rates

[00074] The CREstT baseline rates are the starting point for the casualty generation process. There is a WiA baseline rate which is dependent on troop type, battle intensity, and service and a DNBI baseline rate which is dependent only on troop type.

Table 10 Calculate Baseline Rate inputs

Variable Description Source Min Max

Name

Troop Type The generic type of simulated unit. Troop User-input N/A N/A

Type ε {Combat Arms. Combat Support,

Service Support) .

Battle The level of intensity at which the battle will User-input N/A N/A

Intensity be fought. Battle intensity ε {None, Peace

Ops, Light, Moderate, Heavy, intense, User

Defined}.

Service The military service associated with the User-input N/A N/A scenario. Service ε {Marines, Army}.

User An optional user defined WIA rate (casualties User-input 0 100

Defined per 1000 PAR per day).

WIA Rate

[00075] Baseline WIA casualty rates based on historical data are provided for the Army and Marine Corps. Sufficient data does not exist to calculate historic ground combat WIA rates for the other services. Table 0 displays the baseline WIA rate for the Marine Corps for each troop type and battle intensity combination. Values are expressed as casualties per 1,000 PAR per day. WIA rates for combat support and service support are percentages of the combat arms WIA rate. The combat support rate is 28,5% of the combat arms rate and the service support rate is 10% of the combat amis rate. Peace Operations (Peace Ops) intensity rates are based on casualty rates from Operation New Dawn (Iraq after September 2010). Light intensity rates were derived from empirical data based on the overall average casualty rates from OEF 2010. Moderate intensity rates are derived from the average casualty rates evidenced in the Vietnam War and the Korean War. Heavy intensity rates are based on the rates seen during the Second Battle of Fallujah (during OIF; November 2004). Lastly, "Intense" battle intensity is based on rates sustained during the Battle of Hue (during the let Offensive in the Vietnam War).

Table 11 WIA Baseline Rates for U.S. Marine Corps

Troop Type None Peace Light Moderate Heavy Intense ops

Combat Arms 0 0.1000 0.6000 1.1600 1.8500 3.4700

Combat 0 0,0285 0.1710 0.3290 0.5270 0,9890 Support

Sendee 0 0.0100 0.0600 0.1 120 0.1850 0.3470

Support

[00076] Table 12 displays the baseline WIA rate for the Army for each troop type and battle intensity combination, Army rates are still under development, so the Army rates are currently set to the same values as the Marine Corps rates.

Table 12 WIA Baseline Rates for U.S. Army

Troop Type None Peace Light Moderate Heavy Intense ops

Combat Arms 0 0.1000 ^™O6000^™" 1.8500 ^"™ 4700^~

Combat 0 0.0285 0.1710 0.3290 0.5270 0.9890 support

Service 0 o.oioo 0.0600 0.1120 0.1850 0.3470

Support

[00077] If the user selects the "User Defined" battle intensity, then the user defined WIA rate will be used rather than a rate from the above tables. The disease and nonbattle injur}' (DNB I) baseline rates are determined only by troop type, independent of battle intensity and sendee. Table 0 displays the three DNB! baseline rates. As with WIA rates, values are in casualties per 1,000 PAR per day.

Table 13 DNBI Baseline Rates

Support All

category Intensities

Combat arms 4,23

Combat 3.25

support

Sendee 3.15

support

[00078] The DNBI baseline rate calculation process produces two sets of outputs, the respective WIA and DNBI baseline rates for each user-input selection of troop type and battle intensity (if applicable).

Table 14 Baseline Rate Outputs

Variable name Description Source Min Max

BR_W!AiTr00p The WIA baseline Calculate 0 3,47*

rate for troop type baseline rate

= Troop,

BRo Troop ^{The DNBI} Calculate 3.15 4.23

baseline rate for baseline rate

troop type =

Troop,

*Max value assumes user-defined baseline WIA rate is not used. Table 15 Adjustment Factor Variables

Variable name Description Source Min Max

The WIA baseline rate for troop Calculate 0 3.47* type = Troop. baseline

rate

^BN8!,Troop The DNBI baseline rate for troop Calculate 3.15 4.23 type - Troop. baseline rg The region selected for the scenario User-input N/A N/A

rg e {N0RTHC0M, S0UTHC0M,

EUCOM, CENTCOM, AFRICOM,

PACOM)

tr The terrain selected for the scenario User-input N/A N/A tr £

{Forested, Mountainous, Desert,

J MJly Lt:, UT Uillij

d The climate selected for the User-input N/A N/A scenario

cl E {Hot, Cold, Temperate]

sf The troop strength at which the User-input 0 20000 battle is adjudicated for the

scenario.

NBI% The percentage of DNBI casualties User-input 0 100 that are NBL

*Max value assumes user-defined baseline WIA rate is not used.

The formula for adjusted casualty rates for both WIA and DNBI are:

WlA_Troop = BR_wlAtTroop * jrg * tr * d * sf and,

DNBI_Troop = BR_DNBliTroop * j NBI% * rg_NBI + (1 - NBI¾) * rg_ms WIA Adjustment Factor for Region

Affected casualties: combat arras, combat support, and sendee support

[00079] CREstT allows the user to adjust the region or CCMD in which the modeled operation will occur, A previous study was performed to determine specific variables that influenced U.S. casualty incidence (Blood, Rotblatt, & Marks, 1996). The results of this study were aggregated for CCMDs during CREstT' s development. Table 0 lists the adjustment factors by region.

Table 16 Adjustment Factors for Region

CCMD Adjustment factor

USNORTHCOM ^" 020

USSOUTHCOM 0.50

USEUCOM 1.31

USCENTCOM 1.03

USAFRICOM 0.92

USPACOM 1.13

WIA Adjustment Factor for Terrain

Affected casualties: combat arms, combat support, and sendee support

[00080] Previous modeling efforts by Trevor N. Dupuy (1 90) have demonstrated that terrain and climate have the potential to impact the numbers of casualties in an engagement. Terrain factors previously derived by Dupuy were adapted for the development of terrain adjust factor seed in this tool The multiplicative factors for each terrain description were averaged in the aggregated category. The "Urban" terrain type serves as the baseline value. The average factors for each category were scaled so that Urban would have a value of 1.0. Table 0 describes each of the factors used by Dupuy and the adjustment factors found in MPTk.

Table 17 Dupuy Terrain Values and Ajustment factor for Terrain used in MPTk.

Terrain Description Dupuy Adjustment

Factor

Rugged, heavily wooded

Rugged, mixed

Rugged, bare

1.38

Rolling, foothills, heavily wooded 0.60

Roiling, foothills, mixed 0.70

Rolling, foothills, bare 0.80

Rolling, gentle, heavily wooded 0.65

Roiling, dunes 0.50

Rolling, gentle, mixed 0.75

Rolling, gentle, bare 0.85

LI

Flat, heavily wooded 0.70

Flat, mixed 0.80

Flat, bare, hard 1.00

Flat, desert 0.90

0.70

Swamp 030

Swamp, mixed or open 0.40

Urban 0.50

WIA Adjustment Factor for Climate

Affected casualties: combat arms, combat support, and service support [00081] Climate adjustment factors were also derived from the work of Dupuy. Climate descriptions were aggregated into larger groups similar to the process described in the Adjustment Factor for Terrain section. It should be noted that the aggregated values are adjusted so that the "Temperate" climate serves as the baseline with a value of 1 , This is perfonned by adjusting the "Temperate" climate average to a value of 1 and adjusting each of the other aggregate values by the same multiplier.

Table 18 Dupuy Climat Values and Ajustment factor for Climate used in MPTk

_ Climate description Dupuy Adjustm_ent factor

Dry, sunshine, extreme heat 0.8

Dry, overcast, extreme heat 0.9

Wet, light, extreme heat 0.7

Wet, heavy, extreme heat 0.5

Average

Dry, sunshine, extreme cold 0.7

Dry, overcast, extreme cold 0.6

Wet, light, extreme cold 0.4

Wet, heavy, extreme cold 0.3

Average 0.5

Dry, sunshine, temperate

Dry, overcast, temperate

Wet, light, temperate

Wet, heavy, temperate

WIA Adjustment Factor for Troop Strength

Affected casualties: combat arms, combat support, and sendee support

1 [00082] The troop-strength adjustment factor is derived from the user-input unit size.

However, if the unit size is greater than the PAR, the PAR will be used. Unit size will default to 1 ,000 unless adjusted by the user. If the user inputs a unit size of zero, the PAR. will be used for the troop strength adjustment factor calculation, FIG. 5 shows changes in troop strength adjustment factor as PAR increases. Unit sizes between 869 and 1 ,342 are adjusted using a Weibull hazard-rate function based on the ratio of W1A rates evidenced in divisions, companies, and battalions from the Second Battle of Fallujah. The hazard-rate function is displayed in FIG 5.

[00083] The hazard-rate step function is as follows:

Where: lis™ mm(PAR, unit size)

PAR is the actual PAR for the given troop type on that day. It reflects the interval PAR decreased by casualties on previous days (unless daily replacements are enabled).

DNBI Adjustment Factors for Region

Affected casualties: combat arms, combat support, and service support

[00084] DNBI regional adjustment factors were developed via an analysis of World War II data aggregated by both disease and NBI occurrences within each region. Disease and NBI each have an individual adjustment factor. The adjustment factors are as shown in Table 0, Table 19 Regional Adjustment Factors for DNBI CCMD Adjustment factor (DIS)

(NBI)

USNORTHCO 1.11 1.09

USSOUTHCOM 1.1 1 1.09

USEUCOM 0.89 1.10

USCENTCOM 1.00 1.00

USAFRICOM 1.12 0.94

USPACOM 1.07 LOl

[00085] The application of the adjustment factors yields two sets of outputs: the adjusted rate for WIA casualties and the adjusted rate for DNBI casualties. Table 0 describes the outputs.

Table 20 Application of Adjustment Factors Outputs

Variable name Description Source Min Max

WIA_Tr0Op The WIA adjusted rate Apply 0 12.73*

for Troop Type - Troop. adjustment

factors

DNBl_7roop The DNBI adjusted rate Apply 2.97 4.46

for Troop Type = Troop. adjustment

factors

*Max value assumes user-defined baseline WU i rate is not used.

Generate WIA. Casualt es

[00086] The inputs to the WIA casualty generation process are shown in table 21 and the logic used to generate WIA casualty generation process is shown in FIG 6.

Table 21 WIA Casualties Inputs

Variable name Description Source Min Max

WIA_Troop The WIA adjusted rate for Apply 0 12.73^s1

troop type - Troop. adjustment factors

The WIA baseline rate for Calculate 0 3.41 * troop type ^::: Troop, baseline

rate

PAR Y_OQP The PAR for the given troc )p User input 0 500,000

type. (minus

sustained

casualties j

Troop type The troop type. Troop type : ε User input N/A N/A

{Combat Arms, Combat

Support, Sendee Support}

*Max value as ssumes user-defined baseline WI A rate is not used.

[00087] All CREstT casualties are generated via a mixture distribution. First, a daily rate (DailyWIAt) is drawn from a probability distribution that has the adjusted casualty rate (WIA_Troov) as its mean. As described in detail below, this distribution will be either a gamma or exponential distribution. The daily rate (DailyWIA_t) is then applied to the current PAR and used as the mean of a Poisson distribution to generate the daily casualty count (NumW!A_Troop). The underlying distributions for WIA casualties are determined by the baseline WIA casualty rate (BR_w!AiTrgop). Rates corresponding to Moderate battle intensity or lower will use a gamma distribution, while those corresponding to Heavy or above will use an exponential distribution. Table 0 displays the cutoff point between the two distributions.

Table 22 WIA Casualty Rate Distributions

Troop Type Gamma Ex onential

Disiribut ioi i Hi Distribution if:

Combat Arms < 1.505 B^wiA.CA™ 1-505

Combat < 0.428 BRxviA.cs≥ 0-428

Sendee < 0.149 BRwiA,ss≥ 0-149

Support 88] The parameterization of the gamma distribution used in CREstT is as follows. pdf: fix) = ΓΓ ^Γ ^

p ^s { )β^α μ²

Shape Parameter a ^~ ~~r

Scale Parameter ^

Where: is the mean and σ² is the variance FQ indicates the gamma function Random variates of the gamma distribution are calculated as follow' Generate a randoxn number U™ uniform(0,l) (ιαπΐηια(α, β) ~ Gamma, Ιηνψ, α, β)

Where Gamma, Inv evaluates the gamma inverse cumulative distribution function at U to provide the gamma random van ate.

When generating gamma distributed casualty rates in CREstT, the mean (μ) is equal to W!A_Troop, it is assumed that the variance is equal to the mean to the power of 2.5. Thus, the parameters a and β can be calculated as follows: σ μ 2,5 μ ~ WIA_Troop 2 1 1

Shape Parameter a 2.S

^■oop

Scale Parameter β ~ ~~ ~ μ * ~ μ^1,δ™ _ΓΓ00ρ^1,5

MPTk generates gamma random variaies using the acceptance-rejection method first identified by R. Cheng, as described by Law (2007),

[00089] As described above (in Table 0), heavy and intense battle intensities use the exponential distribution, The exponential distribution can be characterized as a gamma distribution with shape parameter a ~ 1. Therefore, the parameterization of the exponential distribution is as follows:

Where β is the mean. Random variates of the exponential distribution are calculated as follows: Generate a random number U— Uniform(0,l) Εχρ(β) = Gamma. lnv(U, Ι, β)

Where Gamm a, !nv is the inverse of the gamma cumulative distribution function When generating exponentially distributed casualty rates in CREstT, the mean (β) is equal to

WIAn Troop- β - W!A Troop For CREstT ground combat scenarios, MPTk generates exponential random variates using the same method as gamma random variates (described above) with the alpha parameter

3 1.

Generate Daily Casualty

[00090] For combat support and service support troop types, the daily casualty rate (DaiiyWIA_t) for day t is calculated by generating a random variate with mean WIA_Troop from either a gamma or exponential distribution using the procedures described above.

If BR_WIA>Troop is below cutoff (Table 0):

DailyWIA_t ~ ~

JWIA_Troop

If BR_W!AiTroop is above cutoff (Table 0):

DailyWlA_t ~ Εχρ{β = WIA_Troop)

Generate Daily Casualty Rates (Combat Arms)

3 1] An underlying assumption of the CREstT casualty model is that combat arms WIA rates are autocorrelated. This autocorrelation indicates that the magnitude of any one day's casualties is related to the numbers of casualties sustained in the three immediately preceding days. Therefore, CREstT uses an autocorrelation function for the generation of combat arms casualties. Combat support and service support are not modeled using autocorrelation. The autocorrelation computation is as follows.

If BR_{W!A Troov} is below cutoff (Table 0): DailyWIAt = 0,3 * (Daily Wl A., t-i μ) + 0^,2 * (DailyWlA_t-2^™ μ)

+ 0.1 * (DailyWIA_t„2 - μ) + Gamina(a^)

Where:

Troop

l

a

jWlA_Trgop β = W/A S

Troop

I BR_W!AiTroop is above cutoff (Table 0):

DailyWIAt = 0.3 * (D ify A^ - ) + 0.2 * (DailyWIA_t-₂ - μ) +0.1 * (DailyWIAt - μ) + Εχρ{β)

Where; μ = WIA_TT00p and /? = WlA_Troftp

[00092] During the first three days of the simulation (days 0, 1 , and 2), casualty rates for three previous days are not available to perform the autocorrelation. This limitation is overcome by assuming that the three days prior to the start of the simulation all had rates equal to

DailyVVIA^„_x ~ DailyWIA_t- _₂ = DailyWIA_t- _₃ = μ = WIA Troop This has the effect of canceling out terms in the autocorrelation equations above that do not apply. For example, on day 0 with heavy battle intensity, the autocorrelation equation would reduce to:

DailyWIA_tss0 = 0,3 * (DailyWlA^ - μ) + 0.2 * (DailyWIA_t=.₂ - μ)

+0.1 * (DailyWIA_ts-₃ - μ) + Εχρ(β) DailyWIA_t=Q = 0.3 * (μ - μ) + 0.2 * (jx - μ) + 0.1 * (μ - μ) + Εχρ(β)

DailyWIA_t-_Q ^~ Εχρ(β) ^~ Exp(WlA_Troop)

It is possible for the autocorrelation equation to result in a negative result. Because casualty rates cannot be negative, negative casualty rates are corrected to 0.001 before moving on to the calculation of the next day's rate. if DailyWIAt < 0, DailyWIA_t = 0.001

[00093] Once the above calculations have been performed, either in the presence or absence of autocorrelation, the resulting rate ( DailyWIA_t) is used in a Poisson distribution to generate a daily casualty estimate. The pai-ameterization of the Poisson distribution's probability mass function is as follows: pmf: /(fc)= ^ e^"A

Where λ is the mean.

There is no exact method for generating Poisson distributed random numbers. In MPTk, Poisson random variates with means greater than 30 are generated using the rejection method proposed by Atkinson (1979), For means less than 30_? Knuth's method, as described by Law, is used (2007).

Generate Daily Casualty Counts

[00094] To generate the daily Wi A casualty estimate, the previously generated rate { DailyWIA_t) is multiplied by the current PAR divided by 1000 and used as the mean (A) of a Poisson distribution.

PAR \

λ™ DailyWIA_t * JQQQ]

The outputs for the WIA casualty generation process are simply the number of casualties the day that has been simulated.

Tab!e 23 WIA Casualty Generation Process Outputs

Variable name Description Source Min Max

NumWIA -roop The number of WIA Generate 0 -30,000*

casualties for troop type ~ WIA

Troop, casualties

*Max value assumes user-defined baseline WIA rate is not used,

Genexge_.OA_C^ l_.ties

The inputs for the KIA casualty generation process are as follows. Table 24 Generate KIA Casualties inputs

Source Mil Max

f_roop The number of WIA Generate 0 -30,000*

casualties for Troop type WIA

Troop. Casualties

KiA% The number of KIA User-Input 0 100 casualt es to create as a

percentage of WIA

casualties

Max value assumes user-defined baseline WIA rate is not used.

If the "Generate KIA CasuaUies" option is selected, KIA casualties are created as a percentage of the WIA casualties on each day. The calculation is as follows:

NumKIA_Troop = NumWIA_Traop * KIA%

The number of WIA casualties is not changed when KIA casualties are created. Ί able 25 KIA Casualty Generation Process Outputs

Variable Name Description Source

The number of Generate

KIA casualties for WIA

Troop type ~ Casualties

Troop.

Decrement the PAR after WIA and KIA

[00095] After WIA and KIA casualties have been generated, but before generating DNBI casualties, the PAR must be decremented, If the "Daily Replacements" option is selected for this troop type and interval, then the PAR is not decremented. The inputs for decrementing the PAR after WIA and KIA generation are as follows.

Table 26 Decrement PAR after WIA and KIA Inputs

Variable Name Description Source Mm Max

P(WIAocc)_x The probability of ^" PCOF 0 1

occurrence of ICD-9 x

in the WIA PCOF Ρ(Λάηϊ)_χ The probability that an CREstT 0 1

occurrence of ICD-9 x common data

becomes a theater

hospital admission

PAR_Troop The Population at Risk User input 0 500,000

for Troop type = Troop (minus

sustained

________________________ casualties)

[00096] if KIA casualties are generated, all ΪΑ casualties are removed from PAR, The

WIA casualties are adjusted so that only the casualties that are expected to require evacuation κ

Role 3 are removed. This adjustment assumes that all casualties that can return to duty after treatment at Role 1 or Role 2 are not removed from PAR and all casualties that are evacuated beyond Role 2 are permanently removed and not replaced,

~ PARfroop ~~ (NumWIA_Trcsop * ExpEvacPerc) - NumKIA_rroop

Where:

ExpEvacPerc = ^ P(WlAocc)_x * P(Adm)_x

X

Table 27 Decrement PAR after WIA and KIA Outputs

^Va iabl Name Description

PAR_Troop The Population at Decrement PAR

Risk for Troop type ^::s after WIA and

Troop KIA

Generate DNBI Casualties

The inputs for the DNBI casualty generation process are shown in table 28, Table 28 Generate DNBI Casualties Inputs

Variable name Description Source Min Max

DNBI_Troop The DNBI adjusted rate for Apply 2,97 4.46

troop type = Troop. adjustment

factors

roop The FAR for the given troop User input 0 S00,000 type. (minus

sustained

NBI% The percentage of DNBI User input 0 100

casualties that are NBI.

The logic to generate DNBI casualties is displayed in FIG 7,

[00097] The underlying distribution used to create DNBI is the WeibuU distribution. This distribution is standard across all troop types and battle intensities. The mean rate is the only- value that changes. The parameterization for the WeibuU distribution includes a shape parameter (a) and scale parameter (p). In CREstT, it is assumed that the shape parameter is 1.975658. This value is used to solve for the scale parameter. The paranieierizaiion of the WeibuU distribution used in CREstT is as follows:

Shape Parameter a. = 1.975658

Scale Parameter β

Where:

Mean μ = DNBl_Troop JTQ indicates the gamma function Random variates of the Weibull distribution are calculated as follows: Generate a random number U ~ uniform(0,l)

Weibullfa ) = (-β * In(lO)¹/*

Thus the daily DNBI rate is:

DNBI_t

[00098] As in the case of WIA casualties, the daily DNBI rate (DNBI*) is multiplied by the current PAR divided by 1000 and used as the mean (A) of a Poisson distribution. The Poisson distribution is simulated, as described above for WIA casualties, to produce integer daily casualty counts.

NumDNBI_Troop = Poission

1,000/

[00099] CREstT generates the number of DNBI casualties per day as described above, it then splits the casualties according to the user input for "NBI % of DNBI." The calculations are as follows:

NumDiSrroop = Round[(l ~~ NBI¾) * NuniDNBi_Traop} NumNBl_Troop™ NumDNBI_Troop - NumDis_Troop Table 29 DNBI Casualty Generation Process Outputs Variable name Description Source Min Max

NurnDis_Troop The number of DIS casual tie s Generate 0 -5000

for troop type = Troop, DNBI

casualties

NumNBl_TraQp The number of NBI Generate 0 -5000

casualties for troop type - DNBI

Troop. casualties

Decrement the PAR after DNBI

[000100] After DNBI casualties have been generated, but before moving to the next day, the PAR must be decremented. If the "Daily Replacements" option is selected for this troop type and interval, then the PAR is not decremented. The inputs for decrementing the PAR after DNBI generation are as follows,

Table 30 Decrement PAR after DNBI Inputs

Variable Name Description Source Min Max

P(DISocc)_x The probability of PCOF 0 1

occurrence of ICD-9 x

in the DIS PCOF

P(NBIocc)_x The probability of PCOF 0 1

occurrence of ICD-9 x

in the NBI PCOF

P(Adm)_x The probability that an CREstT 0 1

occurrence of ICD-9 x common data

becomes a theater

hospital admission

PAR_Tr00p The Population at Risk User input 0 500,000

for Troop type = Troop (minus

sustained

casualties)

[000101] The DIS and NBI casualties are adjusted so that only the casualties that are expected to require evacuation to Role 3 are removed. This adjustment assumes that all casualties that can return to duty after treatment at Role 1 or Role 2 are not removed from PAR and all casualties that are evacuated beyond Role 2 are permanently removed and not replaced. PAR_Troop - PAR_Troop - (NumDlS_Troop * ExpDISEvacPerc) - (NumNBI_rroop * ExpDISEvacPerc)

Where:

ExpDISEvacPerc ~ P(D!Socc)_x * P{Adm)_x

ExpNBIEvacPerc = ^ P(NBIocc)_x * P(i dm)₃

Table 31 Decrement PAR after DNBI Outputs itm lies

PAR_TrQ0T} The Population at Decrement PAR 0 500,000

Risk for Troop type ^:::: after DNBi

Troop

Disaster Relief

[000102] CREstT includes two modules that allow the user to develop patient streams stemming from natural disasters, These patient streams can subsequently be used to estimate the appropriate response effort. The two types of DR scenarios currently available in CREstT are earthquakes and hurricanes. The following sections provide descriptions of the overall process and describe the algorithms used in these simulations.

Earfhguake

[000103] The CREstT earthquake model estimates daily casualty composition stemming from a major earthquake. CREstT estimates the total casualty load based on user inputs for economy, population density, and the severity of the earthquake. This information is used to estimate an initial number of casualties generated by the earthquake. The user also inputs a treatment capability and day of arrival. CREstT decays the initial casualty estimate until the day of arrival. After arrival, casualties are treated each day based on the treatment capability until the mission ends. The specific workings of each subprocess are described in the following sections.

Calculate Total Casualties

[000104] The first step in the earthquake casualty generation algorithm is to calculate the total number of direct earthquake related casualties. This is a three-step process: calculate the expected number of kills, calculate the expected iryury-to-kills ratio, and calculate the expected number of casualties.

The inputs for these calculations are as follows.

Table 32 Total Earthquake Casualties Calculation inputs

Econ_k The regression coefficient for CREstT -6.98 0

number killed relative to the common

user-input economy. data

PopDens_kiu The regression coefficient for CREstT -3.50 0

number killed relative to the common

user-input population density. data

EC07li_rl j The regression coefficient for CREstT -2.44 97.8

the injury ratio relative to the common

user-input economy. data

PopBens_inj The regression coefficient for CREstT 4,53 0

the injury ratio relative to the common

user-input population density. data scripnon

Magnitude The magnitude of the User-input 5.5 9.5

earthquake.

Table 33 Economy Regression Coefficients (Eartliqiiake)

¾£!£ ntun_inj

6.9760 97J 6

3.3365 -1.9408

-1 0

0 -2.4355

Table 34 Population Density Regression Coefficients (Earthquake)

Population density

PopDens_int

Low -3.5001 -4.5310

Moderate -3.1618 4.5740

High -1.8161 -2.4978

Very high 0 0

The number ¹ of kills is calculated as follows: kill - e (8-i-Econ^_jii+PopDe Sj_tiii-i-(Magnitude*QA))

[000105] The injury-to-kills ratio is calculated as follows:

!nj Ratio™ 12 + (-0.354 * ln(kiU)) - Econ_inj - PopDens_inj [000106] Finally, the iota! number of casualties is calculated according to the following:

3. TotalCas = kill * Inj Ratio The single output from this process is the total number of casualties.

Table 35 Earthquake Casualties Calculation Outputs

Variable same Description Source Min Max

TotalCas The total number of casualties Calculate total 105 717,870 caused by the earthquake, casualties

Decay Tola! Casualties until Day of Arrival

[000107] The next step in the earthquake algorithm is to calculate the number of casualties remaining on the day of arrival. The inputs into this process are as follows.

Table 36 Decay Casualties until Day of Arrival Inputs

Variable Name Description Source Max

TotalCas The total number of casualties Calculate total 80 717,87 caused by the earthquake casualties 0

Arrival The day that the medical User-input 0 180

treatment capability begins

treating patients.

lambda Decay curve shaping CREstT 0.93 0.995 common Data 0

Magnitude The magnitude of the User-input 5.5 9.5

earthquake.

[000108] The initial number of direct earthquake casualties decreases over time. The rate at which they decrease is dependent on several unknown variables. These can include but are not limited to: the rate at which individuals stop seeking medical care; the number that die before receiving care; and the post disaster capability of the local health care system. A shaping parameter, lambda, is a proxy for these non-quantifiable effects, The model makes an assmnpiion that a nation's economic category is closely correlated with its ability to rebuild and organize infrastructure to respond to disasters. Additionally, since larger magnitude earthquakes produce exponentially greater casualties, the model assumes that earthquakes greater than 8.1 have a slower casualty decay, Therefore, a separate lambda is provided for each economic level and magnitudes < 8.1 and >8.1, as follows.

Table 37 Lambda Earthquake Values

Economy Magnitude Lambda

Developed (US) <8.1 0.940

Developed (Non U.S.) <8. 1 0.950

Emerging <8.1 0.992

Developing <8.1 0.994

Developed (US) >8.1 0.930

Developed (Non U.S.) >8.1 0.985

Emerging >8.1 0.986

Developing >8.1 0.995

The calculation for the number of disaster casualties remaining i days after the earthquake, where i > 0, is as follows.

The disaster casualties on day i ( _έ) is initialized to the initial casualties from the earthquake (Tot lCas) and the starting interval counter for the decay shaping parameter (k) is initialized to either 1 or a percentage of the initial casualties. hQn TotalCas 1 if TotalCas≤ 20,000

{ TotalCas * 0.001 if totalCas > 20,000

The casualties are then decayed each day using the following decay process. For i ^ G to Arrival- 1\ noise ^ Uniform(~-5_s5) = )_£ * ( lambda + delta)^⁰ k = k + l i - i + 1

Where delta™ Iog(0.5 * magnitude) * (1 ~ lambda)

scoter ^{L/ R0FAICA5 ≤ 250}'

if TotalC as > 25Q,

Delta provides an adjustment to the response based on earthquake magnitude and adds "noise" to the calculation. Sca er accelerates or decelerates the sweep as a function of the number of casualties.

The disaster casualties remaining on the day of arrival is referred to as ArrivaiCas.

ArrivaiCas hQ_arri_vai

The outputs for this portion of the algorithm are as follows.

Table 38 Decay Casualties until Day of Arrival Outputs

ArrivaiCas The number of casualties Decav

remaining on the day of canities until

arrival. day of arrival Table 39 Calculate Residual Casualties Inputs

caused by the earthquake casualties 0

[000109] The next step in the earthquake algorithm is to calculate the residual casualties in the population. Residual casualties are diseases and traumas that are not a direct result of the earthquake event. For example, residual casualties can be injuries sustained from an automobile accident, chronic hypertension, or infectious diseases endemic in the local population. Non- disaster related casualties initially represent a small proportion of the initial causality load (Kreiss et. al, 2010). Over time the percentage of non-disaster related casualties increases until it reaches the endemi c or background levels extant in the population.

The calculation for the daily number of residual casualties is:

ResidualCas^■= 1.6722 * TotalCas⁰³⁷' Table 40 Calculate Residual Casualties Outputs

Variable Name Description Source Mm Max

ResidualCas The daily number of residual Calculate 8 248

casualties. residual

casualties

Generate Earthquake Casualties

[0001 10] Beginning on the day of arrival, trauma and disease casualties are generated based on the number of initial casualties still seeking treatment and the daily number of residual casualties. After the day of arrival, casualties waiting for treatment are decayed in a manner similar to how they were decayed before they day of arrival.

Table 41 Generate Earthquake Casualties Inputs

Variable Name Deseription Source

The total number of casualties Calculate total 717,87 caused by the earthquake casualties 0 The number of casualties Decay 717,87 remaining on the day of casualties until 0 arrival. day of arrival

The daily number of residual Calculate 248 casualties. residual

casualties

The day that the medical User-input 180 treatment capability begins

treating patients.

Decay curve shaping CREstT 0.93 0.995 common Data 0

The magni tude of the User input 5.5 9.5 earthquake.

The daily treatment capability. User-input 5000

The number of days patients User-input 180 will be treated

The disaster casualties on day after the earthquake hQ ) for the day of arrival is initialized to ArrivalCas and the starting interval counter for the decay shaping parameter (k) is initialized to either 5 or a percentage of the initial casualties, The delta parameter is defined in the same manner as it was before the day of arrival. The scaler parameter is defined as a function of the casualties remaining on the day of arrival (ArrivalCas). arrival ArrivalCas

5 if hO,

TotalCas * 0,001 if HQ delta™ log(0.5 * magnitude) * (1 — lambda)

if ArrivalCas ≤ 250,000 scaler

if ArrivalCas > 250,000

[000111] For each day in the casually generation process. Trauma and Disease casualties are generated using one of three methods, depending on the number of remaining casualties, the treatment capability, and the level of residual casualties, MPTk will display results beginning with the day of arrival, which will be labeled as day zero. The trauma and disease casualties on d&yj after arrival (Traj and DiSj) are calculated using the index j = \ ~ Arrival.

For i -Arrival to Arrival + duration - 1: if remaining casualties (&0_j) exceeds treatment capability (Treatment) then: Arrival ~ Poisson(p * (Treatment)) Bi^si~Arrivai ^~ Poisso7i((l ~~ p) * (Treatment))

Where

If remaining casualties are less than treatment capability and ResidualCas > treatment capability then:

Tra, -Arrival ~~ Poisson(Treatment * 0.1) i-^si-Arrimi^™ Poi$son(Treatment * 0.9)

If remaining casualties are less than treatment capability and ResidualCas < treatment capability then: rai^_Arrivai = Max(Poisson(ResidualCas * 0,1), \hQ_t * p ) i^si-Arrivai ~ Max{Poisson(ResidualCas * 0.9), |7i0_£ * (1 - p}])

Where | is the ceiling operator (round up to nearest integer).

The casualties waiting for treatment on the next day is then calculated by decaying the current remaining casualties and subtracting the current day's patients. noise - Uniform(-S,5)

h0_i+1 = hOi * (lambda + delta)^^{sc ler} * ^{k + oise}} - Tra^_Arrivai - Dis_i→rrival

k = k + l

i = i + 1

Table 42 Generate Earthquake Casualties Outputs

Variable name Description Source Min Max

The number of trauma patients Generate daily

on day j . casu all counts

The number of disease patients Generate daily

on day j . casualty counts Humcarjg

[0001 12] The CREstT hurricane model is similar to the earthquake model. It estimates daily casualty composition stemming from a major hurricane. Similar to the earthquake model, CREstT estimates the total casualty load based on user inputs for economy, population density, and liumcane severity, This information is used to estimate an initial casualty number. The user also inputs a treatment capability and day of arrival. CREstT decays the initial casualty estimate until the day of arrival. After arrival, casualties are treated each day based on the treatment capability until the mission ends.

Calculate Total Casualties

[000113] The first step in the hurricane casualty estimation process is to determine the total number of casualties, This process is performed in a similar fashion as described in the corresponding process in the earthquake algorithm. The steps required to perform this process are as follows:

1, calculate the expected number killed, and use the baseline fatality estimate and adjust by the population density and economic parameters to estimate the overall disaster related casualty numbers.

Table 43 Total Hurricane Casualties inputs

Variable name DeseripiioE

Category The hurricane's category. User-input 1 5

Econ The average human CREstT 20.3 98.9

development index percentile common data rank for the user-input economy.

) ns The regression coefficient for CREstT 0.7 2.4

the user-in£ut_r^gulation density common data Table 44 Population Density Regression Coefficients (Hurricane)

Pop latioH density PopDens

Low 0.70

Moderate LOO

High 1.50

Very high 2.40

Table 45 Economy Regression Coefficients (Hurricane)

Economy Eeoa

Developed (U.S.) 98.8610

Developed (non-U.S.) 82.8182

Emerging 41.5348

Developing 20.2513

The total number of kills is calculated as follows; * Category - 0.085 * Econ)² * PopDens if Category < 2

* Category ~~ 0.171 * Econ)² * PopDens if Category≥ 3 total number of casualties is calculated as follows

TotalCas = Kill * 1.6 * 3.37 4

The single output from this process is the total number of expected casualties for the simulated hurricane. Table 0 describes this output. Table 46 Total Hurricane Casualty Outputs

TotaiCas The total number of Calculate total

expected casualties from casualties,

the hurricane.

Decay Total Casualties until Day of Arrival

[000114] The next step in the hunicane algorithm is to calculate the number of casualties remaining on the day of arrival. The inputs into this process are as follows.

Table 47 Decay Casualties until Day of Arrival Inputs

Variable Nam* i Description Source Mia Max

TotaiCas The total number of casualties Calculate total 26 34,686 caused by the hurricane casualties

Arrival The day that the medical User-input 0 180 treatment capability begins

treating patients.

lambda Decay curve shaping CREstT 0.93 0.995 common Data 0

Category The hurricane's category. User-input 1 5

[000115] Similar to the earthquake model, the initial number of direct disaster related casualties decreases over time. The rate at which they decrease is dependent on several unknown variables, to include but not limited to: the rate at which individuals stop seeking medical care; the number that die before receiving care; and the post disaster capability of the local health care system. A shaping parameter, lambda, is a proxy for these non-quantifiable effects. The model makes an assumption that a nation's economic category is closely correlated with its ability to rebuild and organize infrastructure to respond to disasters. Therefore, a separate lambda is provided for each economic level as follows. Table 48 Hurricane Lambda Values iConomy Lambd;

Developed (US) 0.945

Developed (Non U.S.) 0.950

Emerging 0,970

Developing 0.980

The calculation for the number of disaster casualties remaining i days after the hurricane, where i > 0, is as follows.

The disaster casualties on day i ( )j) is initialized to the initial casualties from the hurricane (TotalCas) and the starting interval counter for the decay shaping parameter (7c) is initialized to either 5 or a percentage of the initial casualties. ft0₀™ TotalCas if TotalCas ≤ 20,000

* 0.001 if totalCas > 20,000

The casualties are then decayed each day using the following decay process.

For i ^~ 0 to Arrival-! : noise = i/?iI orm(-5,5)

(i-f-l) fiQi * (lambda 4- delta) ^iscait

i = i + l

Where delta = log(0,5 * category) * (1 - lambda)

if TotalCas < 20

if TotalCas > 20;

Delta provides an adjustment to the response based on hurricane category and adds "noise" to the calculation. Scaler accelerates or decelerates the sweep as a function of the number of casualties.

The disaster casualties remaining on the day of arrival is referred to as ArrivalCas.

ArrivalCas ~ 0_arrivai The outputs for this portion of the algorithm are as follows.

Table 49 Decay Casualties until Day of Arrival Outputs

Variable Name Description Source Mm Max

ArrivalCas The number of casualties Decay 0 34,686 remaining on the day of casualties until arrival. day of arri val

Calculate Residual Casualties Table 50 Calculate Residual Casualties Inputs

Variable Name Description

TotalCas The total number of casualties Calculate total 26 34,'

caused by the hurricane casualties

[000116] The next step in the hurricane algorithm is to calculate the residual casualties in the population. Residual casualties are diseases and traumas that are not a direct result of the hurricane event. For example, residual casualties can be injuries sustained from an automobile accident chronic hypertension, or infectious diseases endemic in the local population. Non- disaster related casualties initially represent a small proportion of the initial causality load (Kreiss et, a!., 2010). Over time the percentage of non-disaster related casualties increases until reaches the endemic or background levels extant in the population.

The calculation for the daily number of residual casualties is:

ResidualCas^™ 1,6722 * TotalCas ³⁷⁰⁷

Table 51 Calculate Residual Casualties Outputs

ResidualCas The daily number of residual Calculate

casualties, residual

casualties

Generate Hurricane Casualties

[0001 17] Beginning on the day of arrival, trauma and disease casualties are generated based on the number of initial casualties still seeking treatment and the daily number of residual casualties. After the day of arrival, casualties waiting for treatment are decayed in a manner similar- to how they were decayed before they day of arrival.

§5 Table 52 Generate Hurricane Casualties Inputs

Variable Name Description Source Mia Max

To t lC s The total number of casualti es Calculate total 26 34,686 caused by the hurricane casualties

ArrivalCas The number of casualties Decay 0 34,686 remaining on the day of casualties until arrival. day of arrival

ResidualCas The daily number of residual Calculate 6 81

casualties. residual

casualties

Arrival The day that the medical User-input 0 180

treatment capability begins

treating patients.

lambda Decay curve shaping CREstT 0.94 0.980 common Data 5

C l gory The hurricane' s category. User-input. 1 5

Treatment The daily treatment capability. User-input 1 5000

Duration The number of days patients User-input 1 180

will be treated

The disaster casualties on day after the hurricane (ZtGj) for the day of arrival is initialized to AmvaiCas and the starting interval counter for the decay shaping parameter (k) is initialized to either 5 or a percentage of the initial casualties. The delta parameter is defined in the same maimer as it was before the day of arrival. The scaler parameter is defined as a function of the casualties remaining on the day of arrival (ArrivalCas).

^arrival ⁼ ArrivalCas

{5 if hQ_arrival < 20,000

{TotaiCas * 0,001 if h _arrivai > 20,000 delta = log(0.5 * category) * (1 - lambda) if ArrivalCas≤ 20,000 scaler

if ArrivalCas > 20,000

ArrivalCas.

[0001 18] For each day in the casualty generation process, Trauma and Disease casualties are generated using one of three methods, depending on the number of remaining casualties, the treatment capability, and the level of residual casualties. MPTk will display results beginning with the day of arrival, which will be labeled as day zero. The trauma and disease casualties on day j after arrival (ΤΥ ,· and Dis_j) are calculated using the index j = i -Arrival

For i - Arrival to Arrival ÷ duration - 1:

If remaining casualties (/lOj) exceeds treatment capability (Treatment) then: Tra i~Arrivai ~~ Poisson(p * (Treatment)) DiSi„_Arrivai ~ Poisson({l - p) * (Treatment)) Where

if remaining casualties are less than treatment capability and Resid alCas capability then:

Tra.i„_Arrival™ Poisson(Treatment * 0.1) i-^si~ Arrival ~ Poisson(Treatment * 0.9) If remaining casualties are less than treatment capability and ResidualCas < treatment capability then:

Tra^_Arrivai = Max(Paisson(ResidualCas * 0.1), [7ιΟ_έ * p]) -Arriv l ~~ Max(Poisson(ResiduaiCas * 0.9), [TiGj * (1 - p)]) Where [ ] is the ceiling operator (round up to nearest integer).

The casualties waiting for treatment on the next day is then calculated by decaying the current remaining casualties and subtracting the current day's patients. noise ~ Uniform(~-5_}S) h0_t+1 = h0_t * (iamhda + delta)^^{scaler t k + nois}^ - Tra^_Arriml ~~ Dis^ k = k + l

i ~ i + 1

Table 53 Generate Hurricane Casualties Outputs

Variable name Description Source Min Max

Tra_< The number of trauma patients Generate daily ^•5300 on day j. casualty counts

DiSi The number of disease patients Generate daily ^■5300 on day . casualty counts [000119] The humanitarian assistance casualty generation algorithm generates random daily casualty counts based on a user-input rate. For each interval, the inputs for this process are as follows.

Table 54 HA Inputs

Variable Description Source

name

Start The start day of the interval, User input 180

The final day of the interval User input 180 The daily rate of casualties. User input 5000

Trauma% The percentage of the daily casualties that User input 100 will be trauma,

TransitTime The number of days at the beginning of User input

the interval during which the medical

capabilities are "in transit" and unable to

treat patients.

[000120] The first step in the HA casualty generation algorithm is calculate the parameters of the lognormal distribution. The parameters μ and σ² are so that the lognormal random variates generated will have mean λ and standard dev v = (0.3 * iy

[000121] For each day, if the HA mission is considered "in transit", then no casualties are produced. Otherwise, random vaiiaies are produced by first generating a lognormal random variate, then generating two Poisson random variates. The calculations are as follows for casualties on day i,

If i - Start < TransitTime

Traumai - 0

Diseas i ~ 0

Otherwise

X( = Lognormal^ a²)

Traumai ~ PoissQn(Trauma% * X )

Diseasei = Poisson((l - Trauma o) * X )

TotalCasualtieSi = Traumai + Diseasei

Lognormal random variates are generated using an implementation of the Box-Muller transform, Poisson random variates with means greater than 30 are generated using the rejection method proposed by Atkinson (1979), For means less than 30, Knuth's method, as described by Law, is used (2007).

The outputs for this process are described in Table 0.

Table 55 HA Outputs

Variable name Description Source Min Max TotalCasuaitieSi The total number of

casualties on day I.

Trauma-i The number of trauma

casualties on day i.

Dise sei The number of disease

casualties on day i.

Fixed Base

[000122] The fixed base tool was designed to generate casualties resulting from various weapons used against a military base. The tool simulates a mass casualty event as a result of these attacks. Along with generating casualties, the tool also creates a patient stream based on a patient condition occurrence estimation (PCOE) developed from empirical data. This tool gives medical planners an estimate of the wounded and killed to be expected from a number of various weapon strikes.

Front End Calculations

Table 56 inputs for Front-End Calculations

Are _8ase The area of the entire base. User-input > Q 50 mi"

Area_Unit_s The units ofthe base area User-input N/A N/A

{Square Miles, Square KM, Acre.

LethalRadiuSi The radius of weapon strike i User-input > 0 300

within which casualties will be

killed (meters).

WoundR dim The radius of weapon strike i User-input > 0 1500 within which casualties will be

wounded (meters).

^ 8a_$e The population at risk within User-input > Q 100,00 the entire base. 0

PercentPAR_j The percentage of the total User-input > 0 100 population at risk within sector

PercentAre _j The percentage of the total area User-input > 0 100 of the base within sector ,

[000123] The area of the base must first be converted into square meters to simplify future calculations in which weapons are involved. These calculations are as follows:

If Area_Units ^~ Square Miles

Area_BasetMeters = Area_Base * 2589975.2356

If Areo-units ~ Square Kilometers

Area_BaseMeters - Area_Base * 1000000

If Area_Uni_ts™ Acres

Area_BaseMeters = Area_Base * 4046.86

Next, TotalCasArea, LethalArea, and WoundArea must be calculated for each unique combination of WeaponType and WeaponSize,

For each weapon strike i,

TotalCasArea.1 π * (WoundRadiusi)²

LethalAreai - n * LethalRadiusf

WoimdAreai - TotalCasAreai - LethalAreai. [000124] Finally, the total area and PAR must be split amongst each of the sectors according to their characteristics. The calculations for this are as follows.

For each sector j:

PercentPaTi

(Per cent Area._]

Area,_} = Area_Bass *

The outputs for the front end calculations are shown in 0 Table 57 Outputs for Front-End Calculations

Variable same DescriptioE Source Mm Max

Are _Base>Msters The area of the entire base in Front end > 0 1 .3* 10**

square meters. calculations

TotalCasAre i The total area of weapon type Front end > 0 7.i *10⁶

i within which casualties will calculations

be wounded or killed (irf ).

LethalAreai The area of weapon type i Front end > 0 282743

within which casualties will calculations

be killed (m²).

WoundAreai The area of weapon type £ Front end > 0 7.1 *10⁶

within which casualties will calculations

be wounded (m").

PARj The PAR within sector j. Front end > 0 100000 calculations

Area,j The area within sector j (m~ ). Front end > 0 1.3 *10⁸ calculations

Assign Hits to Sectors

[000125] The next step in the simulation process is to stochastically assign each weapon hit to individual sectors based upon their probability of being hit. The inputs for this process are shown in Table 0. Table 58 inputs for Weapon Hit Assignment

Variable name Description Source Min Max

PHit_j The probability thai a given User input

weapon strike will land in sector /.

Weapon itSi The number of weapon hits by User input

i.

[000126] The first step in this process is to build a cumulative distribution of each of the sector's PHits. The cumulative probability for each sector is calculated according to the following: s

CumPHitj - ) PHits,

it=l

Once a cumulative distribution has been built, weapon hits are assigned according to the following process:

2, generate a random number U = Uniform(0,l), and select the sector from the cumulative distribution corresponding with the smallest value greater than or equal to U.

The outputs for the hit assignment process are shown in Table 0.

Table 59 Outputs for Weapon Hit Assignment

Variable mme PeseripiioE

Num itS_j j The number of hits from Assign hits to 0

weapon type i that fall sectors WeaponHitSi within sector . Calcula te WIA and KIA

[000127] Once individual weapon hits have been assigned, the simulation calculates the number of WIA and KIA casualties for each weapon strike. The inputs for this process are shown in Table 0,

Table 60 Inputs for WIA and KIA Calculation

Variable s me Description

U The number of hits from Assign 0

weapon type i that fall weapon hits NumHitSj within sector j,

The PAR within sector j. Front end > 0 20000 calculations

The area within sector j. Front end > 0 1.3* 10⁸

calculations

The total area of weapon Front end > 0 7.1*10⁶ type i within which calculations

casualties will be

wounded or killed.

The area of weapon type Front end > Q 282743 i within which casualties calculations

will be killed.

The area of weapon type Front end > 0 7J*1Q⁶ i within which casualties calculations

will be wounded.

The percent reduction in User-input 0 100% lethal and wounding

radii from shelter use.

SMj is 0 unsheltered

sectors.

The calculation of KIAs and WIAs is performed according to the following. If TotalCasAreai * (l - SMj)^" < Area

WoundAredi

TotalCasAreai

If TotalCasAreai * (l - ^ ,·)² > _4rea/ and LethalAreai * (l - S y)" < ,4re¾:

(LethalAreai

AArreeaa;i

J J J

7 2

If TotalCasAreai * (i - S /)^" > <4reo/ and LethalAreai * ~ > Area^;

[000128] These calculations are perfonned for each weapon strike, and the PAR is decremented prior to the calculations for the next weapon strike. Once all of the calculations have been performed, the total number of WIA and KIA are summed together. These are the outputs for this portion of the simulation. Table 61 Outputs for WIA & KIA Calculations

^' Variable name Description Source Min Max

KIAj The number of casualties Calculate WIA 0 PARj killed in action from sector /. and KIA

WlAj The number of casualties Calculate WIA 0 PARj wounded in action from and KIA

sector j.

KIA The total number of casualties Calculate WIA 0 PARsase killed in action. arid KIA

WIA The total number of casualties Calculate WIA 0 PAR-Base

wounded in action. and KIA

Shipboard

[000129] The shipboard casualty estimation tool was designed to generate casualties resulting from various weapons impacting a ship at sea. The tool, similar to the fixed base tool, generates a mass casualty event as a result of these weapon strikes. Shipboard casualty estimation tool can simulate attacks on up to five ships in one scenario. Each ship can be attacked up to five times, but it can only be attacked by one type of weapon. Each ship is simulated independently. The process below applies to a single ship and should be repeated for each ship in the scenario.

Front End Calculations

[000130] The front end calculations in shipboard calculate the WLA and KIA rate for a specific combination of ship category and weapon type. The inputs to this process are shown in the following table. 1 able 62 Front End Calculations Inputs

E WlAlciass.We pon The expected number of CREstT 2,2 84,{

WIA casualties when a common

weapon of type Weapon hits data

a ship of type Class,

The expected number of CREstT 1,1 125, KIA casualties when a common

weapon of type Weapon hits data

a ship of type Class.

DefaultPAR_ciai s The population at risk for a CREstT 100 6155

ship of type Class. common

Class The category of ship class. User input N/A N/A

Possible values are: CVN,

CG/DDGA FF/MCM/PC,

LHA/LHD, LSD/LPD,

Auxiliaries

Weapon The type of weapon that hits User input N/A N/A

the ship. Possible values are:

Missile, Bomb, Gunfire,

Torpedo, and VBIED.

The following three tables show the values of E[WlA]_Ci_as5iWeapQn, E{K!A]_ciasS!Weapan, and Def ult? AR_aass. The default PAR for a CVN includes an air wing. The default PARs for oiher ships include ship's company, but not embarked Marines. These values are stored in the CREstT common data.

Table 63 Ship Types and Population at Risk

Category

CVN Multi-purpose aircraft carrier 6155

CG/DDG Guided missile cruiser, guided missile destroyer 298

FF/MCM/PC Fast frigate, mine countenneasures ship, patrol craf 100

LHA/LHD Amphibious assault ships 1204

LSD/LPD Dock landing ship, amphibious transport dock 387

Auxiliaries Auxiliary ships 198 Table 64 Expected WIA Casualties for each Ship Class and Weapon Type

Weapon CVN CG DDG FF/MCM/ LHA/LMD LSD LFD Auxiliaries

Missile 49,5 54.4 14,6 63. Ϊ 31.6 __

Bomb 46.4 29.3 8,7 84.0 42.0 12.3

Gunfire 5.1 2.2 4.9 1 1.5 5.8 7,1

Torpedo 15.6 21.5 57.3 75,0 37.5 38,9

Mine ^ "7 13.6 15.7 39.9 20.0 34.4

VBIED 39,2 39.0 44,3 59.7 34.4 26.5

Note: VBIED is vehicle-borne improvis ed exp losive device.

Table 65 E? [peeled KIA Casualties for ea eh Shi p Class and Weapon Type

Weapon CVN CG DDG FF /MCIV 1/ LH A/L D LSD/LPD Auxiliaries

PC

Missile 40.9 51.1 7.8 36.2 18.1 6.0

Bomb 36.1 25.0 4.1 35.0 17.5 7.4

Gunfire 1.4 1.1 3.2 7.0 3.5 4.2

Torpedo 11.0 47.8 39.3 125,0 62.5 30.2

Mine 7.6 13.6 5.7 26.0 13,0 4.4

VBIED 1 1.6 17.0 1 1.5 22.5 13.0 6.3

Note: VBI ED is v ehicle-horne improvis ed explosive device.

[000131 ] The WLA rate and KIA rate are calculated by dividing the expected number of casualties by the PAR of the ship,

E[WI£ Ciass,Weapan

WIARate_Ci_{ass Weapon}

DefaultPARciass

E[KIA] ci ss,Weapon

KIARate, Classweapon ^~ _Defaul_{tPA Rclass}

^"?9 The outputs of this process are as follows: Table 66 Front End Calculations Outputs

Variable name Description SoMfce Mis Max

WIARate_aass,weapon The WIA casualty rate Front End 0.0008

(casualties per PAR) when a Calculations

Weapon hits a ship of type

Class,

K!ARate_ciasSiWeapon The iA casualty rate Front End 0.0002 0.3930

(casualties per PAR) when a Calculations

Weapon hits a ship of type

Class.

[000132] Casualty courjts in Shipboard are generated using an exponential distribution. The parameterization of the exponential distribution is as follows:

pdf: /(*) = - e β

Where β is the mean. Random variates of the exponential distribution are calculated as follows: Generate a random number U ~ Uniform(0,l) Εχρ(β) - -β * 1η(ί/)

Calculate WIA and KIA

[000133] Once the casualty rates have been calculated, they are used to simulate the number of casualties caused by each hit. Each ship can be hit up to five times by the same type of weapon, and the PAR is decreased after each hit by removing the casualties caused by that hit, The inputs to this process are shown in the following table.

Table 67 inputs for WiA and KIA Calculation

Variable name Description Source Min Max

WIARaie_Ci_asSiWeapon The WIA casualty rate front-end 0.0008 0.5730

(casualties per PAR) when a calculations

Weapon hits a ship of type

Class.

K!ARo.te£[_ass iy_eap_0n The KIA casualty rate front-end 0.0002 0,3930

(casualties per PAR) when a calculations

Weapon hits a ship of type

Class.

NumHits The number of times the User input 1 5 weapon hits the ship.

PAR The population at risk. The User input or 0 10,000 default value for the class of CREstT

ship will be used if a value is common data

not entered bv the user.

[000134] The calculation of WIA and KIA casualties is performed according to the following process.

For each hit, i:

Generate a random number of KIA and WIA casualties from an exponential distribution as described in the previous section and round the result to an integer:

WIAi - τοηηά(Εχρ(β = WlAR te, Cl ss,Weapon * PAR)) If the number of KIA casualties exceeds PAR, then all PAR is KIA and there are no

WIA: if (KIAi > PAR):

KIAi = AR

WIA, = 0

If KIA and WIA casualties combined are more than PAR, then KIA casualties are assigned first, and all remaining PAR becomes WIA:

WlAi = PAR - KIAi

PAR is then decremented:

PAR = PAR - KIAi ~~ WIAi Total KIA and WIA for each ship are the sum of KIA and WIA from each hit:

NumHits

NurnHits

The outputs for this process are as follows. Table 68 Outputs for KIA and WIA Calculation

KIA The total KIA for this ship. Calculate 0 PAR

WIA and

KIA

The total WIA for this ship. Calculate 0 PAR

WIA and

[000135] The previous sections described the procedures used by CREstT to produce counts of casualties on a daily basis. In addition to these casualty counts, CREstT also produces patient streams, which assign ICD-9 codes to each patient. This process is common to all of the casualty generation algorithms within CREstT.

Table 69 Inputs for Assignment of ICD-9 Codes

Variable name Description Source Min Max

NumCas Number of casualties for the Various 0 PAR

given day, replication, casualty CRestT

type, group, etc. processes

PCOF The PCOF selected for use with User input N/A N/A

these casualties.

[000136] To assign ICD-9 codes, the PCOF is first converted into a CDF (cumulative distribution function). This allows CREstT to randomly select a ICD-9 code from the distribution via the generation of a uniform (0,1) random number.

[000137] ICD-9 code assignment for each casualty consists of the following two steps:

1. generate a random number U = uniform (0, 1 ), and

S3 select the ICD-9 code from the cumulative distribution corresponding with the smallest value greater than or equal to U.

The outputs of this process are an ICD-9 code assigned to each casual ty.

Table 70 Outputs for Assignment of ICD-9 Codes

Variable name Description Source

/CD , The assigned ICD-9 code Assignment of ICD-9 codes

for casualty i

Combined Scenarios

[000138] Combined scenarios allow the user to combine the results of multiple individual CREstT scenarios into a single set of results. Each individual scenario is executed according to the methodology for its mission type. The combined results are then generated by treating each component scenario as its own casualty group. For mission types with multiple casualty groups, the results for the ^* Aggregate⁵ casualty group are sent to the combined scenario.

C. EXPEDITIONARY MEDICAL REQUIREMENTS ESTIMATOR (EMRE) [000139] The Expeditionary Medical Requirements Estimator (EMRE) is a stochastic modelling tool that can dynamically simulate theater hospital operations. EMRE can either generate its own patient stream or import a simulated patient stream directly from CREstT. The logic diagram showing process of EMRE is shown in FIG. 8. in one embodiment, EMRE can generate its own patient stream based on the user input of an average number of patient presentations per day. EMRE first draws on a Poisson distribution to randomly generate patient numbers for each replication. The model then generates the patient stream by using that randomly drawn number of patients and a user-specified PCOF distribution. In another embodiment, if the user opts to import & CREstT-generated patient stream, EMRE randomly filters the occurrence-based casualty counts to admissions based on return-to-duty percentages. The EMRE common data tables are attached at the end of this application.

[000140] The EMRE tool is comprised of four separate algorithms:

a. the casually generation algorithm,

b. the opperation table (OT) algorithm,

c. the bed and evacuation algorithm, and

d. the blood planning factors algorithm.

Casualty Generation

[000141] EMRE has two different methods for generating casualties : use a CREstT scenario or generate casualties using a user defined rate. In each case, MPTk will generate casualty occurrences then probabilistically determine which of those occurrences will become admissions at the theater hospitalization level of care. These two methods of generating casualties are described in detail below.

Casualty Generation Using a CREstT Patient Stream

[000142] When a CREstT patient stream is used, all casualties from CREstT are considered. However, the patient stream generated by CREstT must be adjusted to account for the fact that many of the casualty occurrences generated by CREstT will not become admissions at the theater hospitalization level The inputs to this process are shown in the table below. Table 71 Casualty Generation Using a CREstT Patient Stream inputs

Variable Description Source Min Max name

0ccJCD9_iJik The assigned ICD-9 code for CREstT N/A N/A casualty i, rep j, day k.

P(Adm)_x The probability that an occurrence EMRE 0 100 of ICD-9 x becomes a theater Common data hospital admission,

[000143] The procedure for adjusting casualty occurrences to arrive at theater hospital admissions is as follows:

For each occurrence 0ccJCD9i _k:

Generate a Uniform(QJ) random vallate, U

If < P(Adm)_{0cc !C}D_{9IJK >} Add

to /CD9y_ifc

Where !CD9i _rk is the ICD-9 codes for the casualties who are admitted to the theater hospital.

T

Casualty Generation Using a The assigned ICD-9 for CREstT Original Patient /CD9;j_i¾ casualty re day k. Stream ______

Casualty Generation Using a User Defined Rate

The user defined rate casualty generation process stochastically generates the number of casualties who will receive treatment at the modeled theater hospital on a given day. These numbers are distributed according to a Poisson distribution. The inputs to the user defined rate casualty generation process are shown below.

Table 73 Casualty Generation Using a User Defined Rate Inputs

Variable Description Source Mm Max name

nReps The number of replications. User input 1 200 iiDays The number of days in each replication. User input 1 180 λ The average number of patients per day. User input 1 2,500

P(Adm)_x The probability that an occurrence of EMRE 0 100

ICD-9 x becomes a theater hospital Common

admission. data

P(type) The probability a theater hospital User input 0 100 admission is the given patient type, where

type 6 {WIA, NBI_S D1S, Trauma}.

The user-selected distribution of ICD-9 N/A N/A PCQF eod&s. User input

[000144] The first step when generating casualties from a user defined rate is to determine the number of admissions on each day, k, for each replication, j, (NumAdm._jik). This number is determined by a random simulation of the Poisson distribution with a mean equal to the user input number of patients per day (A). As is the case throughout MPTk, Poisson random variates with means greater than 30 are generated using the rejection method proposed by Atkinson (1979). For means less than 30, Knuth's method, as described by Law, is used (2007).

NumAdm_{j k} = Poisson(X) V j, k

[000 Ϊ 45] EMRE then generates a patient stream that consists of the ICD-9 codes for each admission that occurs on each day for each replication. To accomplish this, EMRE generates casualty occurrences from the given PCOF. It then randomly determines if each occurrence becomes an admission using the same procedure used with CREstT casualty inputs in EMRE. This is repeated until the proper number of casualties has been generated (NumAdmj_ik). The procedure is as follows.

For each replication j and day k:

For n = 1 to NumAdm.j_ik'.

Generate casualty occurrence and assign patient type

Admission∞ FALSE

While admission is FALSE assign iCD-9 code {0ccJCD9i _ik)

Generate random Uniform(0,l) variate, U

If < P(Adm)_0ccJcm, . _k :

Add OccJCD9_Uik to ICD9_tJik Admission ^::: TRUE

L n = n+1

[000146] The result of this process is the set of ICD-9 codes for every theater hospital admission on each day of each replication (/CD9_;jiic). The process for generating the ICD-9 codes of casualty occurrences (OccJCD9 j_ik) is described in detail below, EMRE first stochastically assigns the patient type of each casualty occurrence using the user-input patient type distribution (P(iype)). The user-input patient type distribution is converted into a CDF (cumulative distribution function) for random selection. This allows EMRE to randomly select a patient type from the distribution via the generation of a uniform (0,1) random number. EMRE then generates a random number for each casualty and selects from the cumulative distribution. After generating a unifomi (0,1) random number, EMRE selects the injury type corresponding to the smallest value greater than or equal to that number.

[000147] Injur}' type assignment for each casualty consists of the following two steps:

1) generate a random number U ~ uniform (0,1), and

2) select the injur}' type from the cumulative distribution corresponding with the smallest value greater than or equal to U,

[000148] Once the patient type is assigned, the casualty is randomly assigned an ICD-9 code using the user specified PCOF. The manner in which ICD~9s are assigned is identical to the process used to assign ICD-9 codes within CREstT.

Table 74 Casualty Generation Using a User Defined Rate Outputs

Variable Description Source

name

The assigned ICD-9 for casualty i, Casualty Generation Using User rep , day k, Defined Rates

Calculate Initial Surgeries

[000149] The Calculate Initial Surgeries algorithm stochastically determines whether casualties will receive surgery at the modeled theater hospital. EMRE does this based on its common data, which contains a probability of surgery value for each individual ICD-9 code.

;9 These values range irora zero (in which case a particular ICD-9 code will never receive surgery) to 1 (where a casualty will always receive surgery). EMRE randomly selects from the distribution similarly to how injury types and ICD-9 codes are assigned.

Table 75 Calculate Initial Surgeries Inputs

Variable name Description Source Min Max

The assigned ICD-9 code for ICD-9 N/A N/A casualty i, rep j, day k. assignment

algorithm

P(Surg)_x The probability that a patient EMRE common 0 1

with ICD-9 code x will receive data

surgery.

[000150] Determining surgery for each casualty consists of the following two steps:

1) generate a random number U ^~ uniform (0,1), and

2) if U < P{Surg)_x, the casualty receives surgery; otherwise, they do not,

[000151] This process creates a single set of outputs— a Boolean value for each casualty describing whether they received surgery.

Table 76 Calculate initial Surgeries Outputs

Variable name Description Source Min Max

Su ,]* A Boolean value for whether Calculate False = True = 1

casualty i on rep / on day k initial 0 receives surgery. Surgeries

[000152] These variables can be used to calculate the number of surgeries on a given day or replication. As an example, the calculation for the number of Surgeries on rep J = 1 day k^™ 1 is as follows:

9Q

Calculate Follow-Up Surgeries

[000153] The logic diagram showing how follow-up surgery is calculated is shown in FIG. 9. After a casualty receives an initial surgery there is a possibility that he will require follow-up surgery. Not all patients will require follow-up surgeries. For the casualties who may receive follow-up surgery, the occurrence depends on the recurrence interval and the evacuation delay, the amount of time he is required to stay. If the casualty will require follow-up surgery before he is able to be evacuated then he will receive the surgery otherwise, he will not. The following table describes the input variables for the follow-up surgery process.

Table 77 Calculate Follow-Up Surgeries Inputs

Variable name Description Source Min Max

The assigned ICD-9 code for iCD-9 N/A i\7A casualty L rep /, and day k. assignment

algorithm

A Boolean value for whether Calculate initial False True casualty i on rep / on day k surgeries - 0 - 1 receives surgery.

Re cur i The recurrence interval— the EMRE common 0 2

time in days between the first data

surgery and recurring surgeries.

EvacDelay The minimum amount of time, User input 1 4

in days, that a patient must wait

before being evacuated.

Table 78 Calculate Follow-Up Surgeries Outputs

Variable name Description Source Min Max

RecurSurgi ^ A Boolean value for Calculate False = True = 1 whether casualty i on rep j follow-up 0

on day k receives follow-up surgeries

surgery. Calculating OR Load Hours

[000154] The next step in the EMRE process is to calculate the time in surgery for each of those casualties who required surgery in the previous two processes. EMRE's common data contains values by ICD-9 code for both initial and follow-up surgery times. If the casualty was chosen to have surgery, a value is randomly generated from a truncated normal distribution around the appropriate time. The inputs for this process are shown below.

Table 79 Calculate OR Load Hours inputs

Variable name Description Source Min Max

The assigned ICD-9 for ICD-9 N/A N/A casualty i, rep j, and day k. assignment

algorithm

Surg_{i sk} A Boolean value for whether Calculate False True

casualty i on rep j on day k initial - 0 = 1 receives surgery. surgeries

RecurSurg_itj_ik A Boolean value for whether Calculate False True

casualty on rep j on day k follow-up - 0 = 1 receives follow-up surgery. surgeries

SurgTime_x The average length of time in EMRE 30 428

minutes a casualty with ICD-9 common data code x will spend in initial

surgery.

RecurTime_x The average length of time in EMRE 30 30

minutes a casualty with ICD-9 common data code x will spend in follow-up

surgery.

ORSetupTime The length of time in hours User input 0 4

required to setup the OR before

a surgery occurs.

[000155] Surgery times are drawn from a truncated normal distribution where the distribution is bounded within 20% of the mean surgical time. The standard deviation is assumed to be one fifteenth of the mean. [000156] The total amount of OR time a patient uses for their initial surgery (QRTime iiti ^) is the simulated amount of time necessary to complete the surgery plus the OR setup time.

ORTimelniti x ~

Surgi _jik * (JrkNorm( n.ean ~ μ, s. d. = σ, min ~ a, max ~ b) + ORSetupTime)

Whew. μ ^~ SurgTime_{x s} a ^~™ , a = 0,8 * μ, and b = 1.2 * μ

And TrkNorm() is a truncated normal distribution.

[000157] A similar calculation is used to calculate the amount of OR time that is required for follow-up surgery.

QRTimeRecuri k ~

RecurSurgi _{j k} * (TrkNorm(mean = μ, 5, ά. ^~ σ, ταϊη ^~ , max = b) + ORSetupTime) Where: μ = RecurTim.e_x , a = ~ , a = 0,8 * , and b = 12 * μ

And Trk orrnQ is a truncated normal distribution.

[000158] Random variates are simulated from the truncated normal distribution as follows:

The percentiles of the normal distribution that are associated with the minimum and maximum of the truncated normal distribution (p_xand p₂) can be calculated from the CDF of the normal disiribuiion. Because ihe standard deviation is a constant ratio of the mean, these values will be the same for every ICD-9 and only need to be computed once, p₁ - Norm. CDF (nwan - μ, s, d, ~—· , x - .8 * - 0,00135 p₂ = Norm. CDF (mean = μ, ε. ά. - γρ, χ = 1.2 * μ) - 0,99865

Where Norm. CDF is the cumulative distribution function of the normal distribution evaluated at x.

[000159] To generate a random variate from this distribution, generate a uniform random number.

U = Uniform(O.l)

Use Uto generate a uniform random number between -i and p₂-

V = Uniformip^ pz) = p₁ + U * (p₂ - p_t) = .00135 + U * 0.9973

Use Vto generate a normal random variate from a normal distribution.

TrkNormfa, σ, a, b) = Norm, Inv(x = V, mean = μ, s. d. = σ)

Where Norm.inv evaluates the inverse of the Normal distribution cumulative distribution function at x.

[000160] The total number of load hours needed each day k, in a given replication j, (LoadHourS_{j k}) is the sum of the times necessary to complete all initial and follow-up surgeries that occur on that day. LoadHourS_jfi - / ORTimeIniti _ik + ) ORTimeRecw\_jik

[000161] The outputs for this process are the total OR load for each day of each replication, and are described in the following table.

Table 80 Calculate OR Load Hours Outputs

Variable name Description Source Min Max

LoadH oursjfi The total number of OR load Calculate OR 0 00

hours on rep j, and day k. load hours

process

Calculating OR Tables

[000162] The calculation of the required number of OR tables is a simple extension of the process for calculating OR load hours. EMRE calculates, for each day, the necessary number of OR tables to handle the patient load. This calculation is based upon the following inputs.

Table 81 Calculate OR Tables Inputs

Variable name Description Source Min Max

LoadHourSj_ik The total number of OR load Calculate 0

hours on rep j, and day k. OR load

hours

process

OperationaiHours The number of hours each OR User input 8 24

will be operational on a given

day.

[000163] The calculation is the ceiling of the daily load hours divided by the operational hours. This process produces a single output— the number of required OR tables on each day of each replication

X LoadHourSj _k

ORTables_{j k} = _;

" \ OperationaiHours Table 82 Calculate OR Tables Outputs

Variable name Description Source Min Max

0RTableS_jik The number of OR tables Calculate OR (30

required to treat the patient load tables process

on rep /, and day k.

Determining Patient Evac Status [000164] The next step in the high-level EMRE process is to determine the evacuation status and length of stay in both the ICU and the ward for each patient. H e inputs for this process are shown below.

Table 83 Determine Patient Evac Staais Inputs

Variable name Description Source Min Max

ICD9 i,j^" _:k The assigned ICD-9 code ICD-9 N/A for casualty / ,rep /, and assignment

V L

A Boolean value for False True whether casualty i on rep initial ^« 0 on day k receives surgery. surgeries

QRICULQSy The ICU length of stay in EMRE 0

days for patients with ICD- common data

9 code x who had

previously received

surgery.

QRWardLQS,. The ward length of stay in 180 days for patients with ICD- common data

9 code x who had

previously received

surgery.

NoORlCULOSy The ICU length of stay in

days for patients with ICD- common data

9 code x who had not

received surgery.

NoORWardLOS, The ward length of stay in

days for patients with ICD- common data

9 code x who had not

received surgery.

EvacPolicy The maximum amount of User input 15 time in days that a casualty

may be held at the theater hospital for treatment.

[000165] There are two decision points for this logic, First, casualties are split according to whether they required surgery. Their length of stay for both the ICU and the Ward is then determined. Next, if the total length of stay is greater than the evacuation policy, the casualty will evacuate; otherwise, they will return to duty. FIG 10 displays this logic.

[000166] As a convention, a patient's status is always determined at the end of the day. For example, a patient that arrives on day 3, stays for 3 niglits in the ward, and then evacuates will generate demand for a bed on days 3, 4, and 5. On day 6, they will be counted as a ward evacuee, but they will not use a bed on day 6 because they are not present at the end of the day. The outputs for this process are as follows.

Table 84 Determine Patient Evac Status Outputs

Variable name Description Source Min Max

Status _jik The patient evacuation status Determine Evac RTD

for casualty z, repy, and day k. patient

evacuation status

process

ICULQSi The ICU length of stay for Determine 0 3

casualty ?^*, rep j, and day k patient

evacuation status

process

WardLQSi _¾ The ward length of stay for Determine 0 180

casualty /, rep/, and day Jt. patient

evacuation status

process

Calculating Number of Beds and Evacuations [000167] The next step in the EMRE process is to determine the number of beds, both in the ICU and the ward, required to support the patient load on a given day. Coupled with this is the calculation of the evacuations, both from the ICU and the ward, on any given day. Casualties that evacuate from the ward are also counted towards demand for staging beds. The inputs for this process are as follows.

Table 85 Calculate Number of Bed and Evacuation Inputs

Variable name Description Source Min Max

ICD9_tJJt The assigned ICD-9 for ICD-9 N/A N/A casualty, rep j, and day k. assignment

algorithm

IGULOSi fl The ICU length of stay for Determine 0 3 casualty, rep j, and day k. patient

evacuation status

process

WardLOSi _k The Ward length of stay for Determine 0 180 casualty, rep j, and day k. patient

evacuation status

process

EvacDelay The number of days a User input 1 10 patient must wait before

being evacuated.

CCATT A Boolean value identifying User input False = 0 Trae ~ 1 whether CCATT teams are

available for transport.

StagingHold The number of days a ward User input 1 3 evac patient will be held in

a staging bed

[000168] This process is broken down into two subprocesses. First, the calculations are performed for casualties who were designated for evacuation in the Determining Patient Evac Status section. Next, a different process is performed for patients who were designated to return to duty. FIG 1 1 and FIG 12 outline the subprocesses. The outputs for these sub-processes include the number of beds, both in the ICU and the ward, for each day of the simulation, as well as the number of evacuations from the ICU and ward for each day. Table 86 Calculate Number of Bed and Evacuation Outputs

Variable name Description Source Min Max

ICUBedS_j z The number of patients requiring Calculate beds 0

beds in the ICU on rep j and day and evacuations

k. process

WardBedSj _k The number of patients requiring Calculate beds 0 00 beds in the ward on rep j and day and evacuations

k process

ICUEvacS_j The number of patients Calculate beds 0 CO evacuating from the ICU on rep j and evacuations

and day k, process

WardEvacSj _k The number of patients Calculate beds 0 00 evacuating from the ward on rep j and evacuations

and day k. process

StagingBeds_{j k} The number of patients requiring Calculate beds 0 CO staging beds on rep j and day k. and evacuations

process

C^^^^^^^\wim Factors

[000169] The final process in an EMRE simulation is the calculation of blood planning factors. This process simply takes the user-input values for blood planning factors, either according to specific documentation or specific values from the user, and applies them to specific casualty types. The inputs are displayed in Table 87.

Table 87 Calculate Blood Planning Factors Inputs

Variable name Description Source

CasType _>k The patient type for casualty i, rep Casualty

j, and day A^r. type

assignment

algorithm

RBC The number of units of red blood User input

cells used as a planning factor for

the scenario.

FFP The number of units of fresh User input

frozen plasma used as a planning factor for the scenario,

Platelet The number of units of platelet User input

concentrates used as a planning

factor for the scenario.

Cryo The number of units of User input

cryoprecipitate used as a planning

factor for the scenario.

[000170] The calculation of the blood products is simple. If a casualty has the patient type WIA, NBI, or trauma, e receives the blood products according to the user-input quantities. Therefore, it is simply a multiplier of the total number of WIA, NBI, and trauma casualties and the quantities for the blood planning factors. As an example, below is the calculaiion for red blood cells. The calculations for each of the other planning factors are calculated similarly,

[000171]

lie outputs of the calculate blood planning factors are described in Tabl Table 88 Calculate Blood Planning Factors Outputs

Variable name Description Source

RBC_{j k} The number of units of red blood User input

cells required on rep j, and day k.

FFPj _k The number of units of fresh User input

froze plasma required on rep j,

and day k.

Platelet_{} i} The number of units of platelet User input

concentrates required on rep j,

and day k.

CryO_jik The number of units of User input

cryoprecipitate required on rep j,

and day k. IK Examples of medical planning stimulations using MPTk software

[000172] The Medical Planners' Toolkit (MPTk) is a software suite of tools (modules) developed to support the joint medical planning community. This suite of tools provides planners with an end-to-end solution for medical support planning across the range of military operations (R.OMO) from ground combat to humanitarian assistance, MTPk combines the Patient Condition Occurrence Frequency (PCOF) tool, the Casualty Rate Estimation Tool (CREstT), and the Expeditionary Medical Requirements Estimator (EMRE) into a single desktop application. When used individually the MPTk tools allow the user to manage the frequency distributions of probabilities of illness and injury, estimate casualties in a wide variety of military scenarios, and estimate level three theater-medical requirements. When used collectively, the tools provide medical planning data and versatility to enhance medical planners' efficiency.

[000173] The PCOF tool provides a comprehensive list of ROMO-spanning, baseline probability distributions for illness and injury based on empirical data. The tool allows users to store, edit, export, and manipulate these distributions to better fit planned operations. The PCOF tool generates precise, expected patient probability distributions. The mission-centric distributions include combat, humanitarian assistance (HR), and disaster relief (DR). These mission-centric distriutions allows medical planner to assess medical risks associated with a planned mission.

[000174] The CREstT provides the capability for planners to emulate the operational plan to calculate the combat and non-combat injuries and illnesses that would be expected during military operations. Casualty estimates can be generated for ground combat, ship attacks, fixed facilities, and natural disasters. This functionality is integrated with the PCOF tool, and can use the distributions developed in that application to construct a patient stream based on the casualty estimate and user-selected PCOF distribution, CREstT uses stochastic methods to generate estimates, and can therefore provide quantile estimates in addition to average value estimates.

[000175] EMRE estimates the operating room, ICU bed, ward bed, evacuation, and blood product requirements for theater hospitalization based on a given patient load. EMRE can provide these estimates based on a user-specified average daily patient count, or it can use the patient streams derived by CREstT as EMRE is fully integrated with both CREstT and the PCOF tool. EMR also uses stochastic processes to allow users to evaluate risk in medical planning,

[000176] The MPTk software can be used separately or collectively in medical logistics and planning. For example, the PCOF module can be used individually in a method for assessing medical risks of a planned mission comprises. The user first establishes a PCOF scenario for a planned mission. Then ran simulations of the planned missi on to create a set of mission-centric PCOF distributions. The PCOF stores the mission-centric PCOF distributions for presentations. The user can use these mission-centric PCOF to rank patient conditions for the mission and thus identifying medical risks for the mission.

[000177] In another embodiment, the MPTK may he used collectively in a method for assessing adequacy of a medical support plan for a mission. The user first establishes a scenario for a planned mission in MPTk. The user then stimulates the planned mission to create a set of mission-centric PCOF using PCOF module, The user then can then use the CREstT module to generate estimated estimate casualties for the planned mission and use the EMRE module to calculate estimated medical requirements for the planned mission. The results from the simulation in three modules can then be used to assess the adequacy of a medical support plan. Multiple simulations may be created and ran using different user inputs, and the results from each simulation compared to select the best medical support plan, which reduces the casualty or provides adequate medical requirements for the mission. The MPTk software can also be used in a method for estimating medical requirements of a planned mission, in this embodiment, the user first establishes a scenario for a planned mission in MPTk or only in EMRE. Then the user run simulations of the planned medical support mission to generate estimated medical requirements, The estimated medical requirements may be stored and used in the planning of the mission. In an embodiment of the inventive method for estimating medical requirements medical requirements of a planned mission, medical requriemensts estimated including but not limited to: a. the number of hours of operating room time needed;

b. the number of operating room tables needed;

c. the number of intensive care unit beds needed;

d . the number o f ward beds needed;

e. the total number of ward and ICU beds needed;

f. the number of staging beds needed;

g. the number of patients evacuated after being treated in the ward;

h. the total number of patients evacuated from the ward and ICU;

i. the number of red blood cell units needed;

j. the number of fresh frozen plasma units needed;

k. the number of platelet concentrate units needed; and

1. the number of Cryoprecipitate units needed. IV. Verification and Validation of MPTk Software

[000178] A MPTk V&V Working Group were designated by the Services and Combatant Commands in response to a request by The Joint Staff to support the MPTk Verification and validation effort. The members composed of medical planners from various Marine, Army, and Navy medical support commands. Each member of the Working Group received one week of MPTk training conducted at Teledyne Brown Engineering, Inc., Huntsviile, AL. The training was provided to two groups; the first group receiving training 28 April— 2 May 2014 and the second group from 5 - 9 May 2014. During the training, each member of the Working Group received training on MPTk, to include detailed instruction on the PCOF tool, CREstT, and EMRE as well as training on the verification, validation, and accreditation processes. Specific- training on the V&V process included the development of acceptability criteria, testing methods, briefing formats, and the use of the Defense Health Agency's eRoom capabilities, which serv ed as the information portal for the MPTk V&V process.

[000179] Towards the end of each week, initial testing began using the same procedures that would be used throughout the testing to familiarize each of the Working Group members with the process, The major validation events of the V&V process occurred on the Defense Connect Online (DCO), report calls that were conducted during the validation phase of the testing. On each of the DCO calls during validation testing of the model, Working Group members were presented briefings on topics they had selected on validation issues by the software developers. The Working Group members then discussed validation issues. The major issue identified during the validation phase of the testing was a recommendation to add the ability for the user to select a semce baseline casualty rate (vs. a Joint baseline casualty rate) and a use rdefmed baseline casualty rate. The MPTk V&V Working Group members determined this was a valid concern and the capability was added to the model and thoroughly tested. Once this capability was added, the Working Group members were satisfied with the validation phase of the testing.

[0001] Comparison testing on MPTk was conducted on DCO calls on 6 Aug 2014 and 13 Aug 2014. Testing was conducted comparing MPTk results to real world events, and also to output from another DoD medical planning model, JMPT. Working Group members identified several issues during the comparison testing of MPTk, all of which were corrected and retested. At the conclusion of the testing, all Working Group members were satisfied with the results of the comparison testing.

[000180] Multiple iterations of the changes made have recently been incorporated into MPTk, These include:

a. Patient conditions form the basis upon which the model operates. Previous PCs were SME-derived. Thes patient data have been replaced with 282 single injury and 37 multiple PCs that have been developed using scientific processes and objective data.

b. A medical supply projection capability has been added that allows medical

materiel to be projected for the scenarios used within the software. c. The core data has been replaced with objective military data sets. This allows updates to be conducted on the core data files. Updating of the core data is now occurs twice annually. [0002] Based on the foregoing, a computer system, method and software have been disclosed for medical logisiic piaaning purpose. However, numerous modifications and substitutions can be made without deviating from the scope of the present invention. Therefore, the present invention will be disclosed, the DETAILED DESCRIPTION section, by way of example and not limitation.

Mefresces

1. Atkinson, A. C. ( 1979), Recent developments in the computer generation of Poisson random variables. Applied Statistics. 28(3), 260-263.

2. Blood, C. G., Rotblatt, D., Marks IS, (1996). Incorporating Adversary-Specific

Adjustments into the FORCAS Ground Casualty Projection Model (Report No. 96-lOJ). San Diego, CA: Naval Health Research Center.

3. Dupuy, T. N. (1990). Attrition: Forecasting battle casualties and equipment losses in modem war. Fairfax, VA: Hero Books,

4. Eikins, T., & Wing. V. (2013). Expeditionary Medicine Requirements Estimator (EMRE) (Report No, 13-2B), San Diego, CA: Naval Health Research Center.

5. Eikins, T._s Zouris, J., & Wing, V. (2013). The development of modules for shipboard and fixed facility casualty estimation. San Diego, CA: Naval Health Research Center.

6. Kreiss, Y., Merin, O., Peleg, K„ Levy, G., Vinker, S._; Sagi, R,_} & ...Ash, N. (2010). Earl disaster response in Haiti: the Israeli field hospital experience. Annals of internal medicine, 153 (1), 45-48.

7. Law, Averill M. (2007). Generating Discrete Random Variat.es. In K. Case & P. Wolfe (Eds.) Simulation Modeling and Analysis, (p. 466). New York: The McGraw-Hill Companies. Inc.

8. Nix, R, Negus, T.L., Eikins, T, Walker, J, Zouris, J., D'Souza, E, & Wing, V. (2013). Development of a patient condition occurrence frequency (PCOF) database for military, humanitarian assistance, and disaster relief medical data (Report No. 13-40). San Diego, CA: Naval Health Research Center. 9. Pan American Health Organization, (2003). Guidelines for the Use of Foreign Field Hospitals in the Aftermath of Sudden-impact Disasters. Washington, DC: Regional Office of the World Health Organization,

10. Zouris, 1, D'Souza, E., Eikins, T., Walker, J,, Wing, V., & Brown, C. (2011). Estimation of the joint patient condition occurrence frequencies from Operation Iraqi Freedom and

Operation Enduring Freedom Volume I: Development of methodology (Report No. 1 1-91). San Diego, CA: Naval Health Research Center.

1 1. Zouris, J., D'Souza, E., Walker, J., Honderich, P., Tolbert, B,, & Wing, V. (2013).

Development of a methodology for estimating casualty occurrences and the types of illnesses and injuries for the range of military operations (Report No. 13-06). San Diego, CA: Naval Health Research Center.

EMRE COMMON DATA

The tables below (Tables 89- 1) show the data used by EMRE to support the previously described processes. All variables with a source listed as "EMRE common data" are defined here. Some values may be stored at a greater precision in the MPTk database and rounded for display in these tables.

Table 89 EMRE Common Data: Surgery Data

Syrglime R®tur ReosrTfm©

PC Type Descri tion P(Ssirg) (mins) (c jays) (hours)

005 D PO Food poisoning 0.00 0

bacteria!

006 QMMPQ Amebiasis 0.00 0

007.9 DMMPO Unspecified protozoa! 0.00 0

intestinal disease

008.45 DMMPO Intestinal infection due 0.00 0

to Clostridium difficile

008.8 DMMPO intestinal infection due 0.00 0

to other organism not

classified

010 DMMPO Primary tb 0.00 0

037 DMMPO Tetanus 0.00 0

038.9 DMMPO Unspecified septicemia 0.00 0

042 DMMPO Human 0.00 0

immunodeficiency virus

[HIV] disease

047.9 DMMPO Viral meningitis 0.00 0

052 DMMPO Varicella 0.00 0

053 DMMPO Herpes zoster 0.00 0

054.1 DMMPO Genital herpes 0.00 0

057.0 DMMPO Fifth disease 0.00 0

060 DMMPO Yellow fever 0.0Q 0

061 DMMPO Dengue 0.00 0

062 DMMPO Mosq. borne 0.00 0

encephalitis 063.9 D MPO Tick borne encephalitis 0.00 0

065 D MPO Arthropod-borne 0.00 0

hemorrhagic fever

066.40 DMMPO West nile fever, 0.00 0

unspecified

070.1 DMMPO Viral hepatitis 0.00 0

PC Type Description P(Surg) SurgTime Recur ecurTime

(mins) (days) (hours)

071 DMMPO Rabies 0.00 0

076 DMMPO Trachoma 0.00 0

078.0 DMMPO Molluscom coniagiosum 0.00 0

078.1 DMMPO Viral warts 0.00 0

078.4 DMMPO Hand, foot and mouth 0.00 0

disease

079.3 DMMPO Rhinovirus infection in 0.00 0

conditions elsewhere

and of unspecified site

079.99 DMMPO Unspecified viral Q.00 0

infection

082 DMMPO Tick-borne rickettsials 0.00 0

084 DMMPO Malaria 0.00 0

085 DMMPO Leishmaniasis, visceral 0,00 0

086 DMMPO Trypanosomiasis 0.00 0

091 DMMPO Early primary syphilis 0.00 0

0919 DMMPO Secondary syphilis, 0.00 0

unspec

094 DMMPO Neurosyphilis 0.00 Q

09S.5 DMMPO Gonococcal arthritis 0.00 0

099.4 DMMPO Nongonnococcal 0.00 0

urethritis

100 DMMPO Leptospirosis 0.00 0 274 DMMPO Gout 0.00 0

276 DMMPO Disorder of fluid, 0.00 0

electrolyte + acid base

balance

296.0 DMMPO Bipolar disorder, single 0.00 0

manic episode

298,9 DMMPO Unspecified psychosis 0.00 0

309.0 DMMPO Adjustment disorder 0.00 0

with depressed mood

309.81 DMMPO Ptsd 0.00 0 309.9 DM PO Unspecified adjustment Q.Q0 0 reaction

310.2 D PO Post concussion 0.00 0 syndrome

345.2 DMMPO Epilepsy petit mal 0.00 0

345.3 DMMPO Epilepsy grand mal 0.00 0

364.3 DMMPO Uveitis nos 0.00 0

365 DMMPO Glaucoma 0.00 0

370.0 DMMPO Cornea! ulcer 0.00 0

379,31 DMMPO Aphakia 0.00 0

380.1 DMMPO Infective otitis externa 0.00 0

380.4 DMMPO Impacted cerumen 0.00 0

381 DMMPO Acute nonsuppurative 0.00 0 otitis media

381.9 DMMPO Unspecified eustachian 0.00 0 tube disorder

384.2 DMMPO Perforated tympanic 0.00 0 membrane

38S.3 DMMPO Tinnitus, unspecified 0.00 0

389.9 DMMPO Unspecified hearing ioss 0.00 0

401 DMMPO Essential hypertension 0.00 0

410 DMMPO Myocardial infarction 0.00 0

413.9 DMMPO Other and unspecified 0.00 0 angina pectoris

427.9 DMMPO Cardiac dysryhthmia 0.00 0 unspecified

453.4 DMMPO Venous 0.00 0 embolism/thrombus of

deep vessels lower

extremity

462 DMMPO Acute pharyngitis 0.00 0

465 DMMPO Acute uri of multiple or 0.00 0 unspecified sites

466 DMMPO Acute bronchitis & 0.00 0 bronchiolitis

475 DMMPO Peritonsillar abscess 0.25 176 0

486 DMMPO Pneumonia, organism 0.00 0 unspecified 491 DMMPO Chronic bronchitis 0.00 0

492 D PO Emphysema 0.00 0

493.9 DMMPO Asthma Q.00 0

523 DMMPO Gingival and 0.00 0

periodontal disease

530.2 DMMPO Ulcer of esophagus 0.00 0

530.81 DMMPO Gasiroesophageal reflux 0.00 0

PC Type Description P{Surg) SurgTime Recur ecurTirne

531 DMMPO Gastric uicer 0.00 0

532 DMMPO Duodenal uicer 0.18 150 0

540.9 DMMPO Acute appendicitis 0.80 291 1 0.5

without mention of

peritonitis

541 DMMPO Appendicitis, 0.83 90 1 0.5

unspecified

550.9 DMMPO Unilateral inguinal 0.01 191 0

nernta

553.1 DMMPO Umbilical hernia 0,87 90 0

553.9 DMMPO Hernia nos 0.10 90 0

564.0 DMMPO Constipation 0.00 0

5641 DMMPO Irritable bowel disease 0.00 0

566 DMMPO Abscess of anal and 0.75 45 1 0.5

rectal regions

567.9 DMMPO Unspecified peritonitis 0.00 0

574 DMMPO Cholelithiasis 0.05 182 0

577.0 DMMPO Acute pancreatitis 0.00 0

577.1 DMMPO Chronic pancreatitis 0.00 0

578.9 DMMPO Hemorrhage of 0.00 0

gastrointestinal tract

unspecified

584.9 DMMPO Acute renal failure 0.00 0

unspecified

592 DMMPO Calculus of kidney 0.00 0

599.0 DMMPO Unspecified urinary tract 0.00 0

infection

599.7 DMMPO Hematuria 0.00 0

6Q8.2 DMMPO Torsion of testes 1.00 147 0

608.4 DMMPO Other inflammatory 0.00 0

disorders of male

genital organs 611.7 DMMPO Breast lump 0.00 0

633 DMMPO Ectopic preg 0.50 173 0

634 DMMPO Spontaneous abortion 0.75 162 0

881 DMMPO Cellulitis and abscess of 0.00 0

finger and toe

682.0 DMMPO Cellulitis and abscess of 0.00 0

face

PC Type Description P(Surg) SurgTims Recur RecurTirne

(mins) (days) {hours)

682.6 DMMPO Cellulitis and abscess of 0.00

leg except foot

682.7 DMMPO Cellulitis and abscess of 0.00 0

foot except toes

682.9 DMMPO Cellulitis and abscess of 0.00 0

unspecified parts

719.41 DMMPO Pain in joint shoulder 0.00

719.46 DMMPO Pain in joint lower leg 0,00

719.47 DMMPO Pain in joint ankle/foot 0.00

722.1 DMMPO Displacement lumbar 0.00

intervertebral disc w o

myelopathy

723.0 DMMPO Spinal stenosis in 0.00 0

cervical region

724.02 DMMPO Spinal stenosis of 0.00 0

lumbar region

724.2 DMMPO Lumbago 0.00 0

724.3 DMMPO Sciatica 0.00 0

724.4 DMMPO Lumbar sprain 0.00 0

(thoracic/lumbosacrai)

neuritis or radiculitis,

unspec

724.5 DMMPO Backache unspecified 0.00 0

726.10 DMMPO Disorders of bursas and 0,00 0

tendons in shoulder

unspecified

726,12 DMMPO Bicipital tenosynovitis 0.00

7263 DMMPO Enthesopathy of elbow 0,00

region

726.4 DMMPO Enthesopathy of wrist 0.00

and carpus

726.5 DMMPO Enthesopathy of hip 0,00

region

726.6 DMMPO Enthesopathy of knee 0.00 726.7 D PO Enthesopathy of ankle 0.00 0 and tarsus

729,0 DMMPO Rheumatism unspecified 0.00 0

and fibrositis

729.5 DMMPO Pain in limb 0.00 0

780,0 DMMPO Alterations of 0.0Q 0

consciousness

780,2 DMMPO Syncope 0.00 0

PC Type Description P(Surg) SurgTime Recur ecurTi ne

(mirts) (days) {hours}

780.39 DMMPO Other convulsions 0.00 0

780,5 DMMPO Sleep disturbances 0.00 0

780.6 DMMPO Fever 0.00 0

782.1 DMMPO Rash and other 0.00 0

nonspecific skin

eruptions

7823 DMMPO Edema 0.00 0

783,0 DMMPO Anorexia 0.00 0

784.0 DMMPO Headache 0.00 0

784.7 DMMPO Epistaxis 0.00 0

734.8 DMMPO Hemorrhage from 0,00 0

throat

786.5 DMMPO Chest pain 0.00 0

787.0 DMMPO Nausea and vomiting 0.00 0

787.91 DMMPO Diarrhea nos 0.00 0

789.00 DMMPO Abdominal pain 0,00 0

unspecified site

800.0 DMMPO Closed fracture of vault 0,00 0

of skull without

intracranial injury

801.0 DMMPO Closed fracture of base 0.10 200 0

of skuii without

intracranial injury

801.76 DMMPO Open fracture base of 1.00 241 0

skull with subarachnoid,

subdural and extradural

hemorrhage with loss of

consciousness of

unspecified duration

802,0 DMMPO Closed fracture of nasal 0.10 211 0

bones

802,1 DMMPO Open fracture of nasal 1.00 241 0

bones 802.6 DMMPO Fracture orbital floor 0.30 179 0 closed (blowout)

802.7 D MPO Fracture orbital floor 100 241 0

open (blowout)

802.8 DMMPO Closed fracture of other 0.10 192 0

facial bones

802,9 DMMPO Open fracture or other 1.00 241 0

facial bones

PC Type Description P(Surg) SurgTime Recur ecurTime

(rnins) (days) (hours)

805 DMMPO Closed fracture of 035 SO 0

cervical vertebra w/o

spinal cord injur/

806,1 DMMPO Open fracture of cervical 0.15 212 0

vertebra with spinal

cord injury

806.2 DMMPO Closed fracture of dorsal 0.10 201 0

vertebra with spinal

cord injury

806.3 DMMPO Open fracture of dorsal 0.40 242 0

vertebra with spinal

cord injury

806.4 DMMPO Closed fracture of 0.2S 200 0

lumbar spine with spinal

cord injur/

806.5 DMMPO Open fracture of lumbar 1.00 241 0

spine with spinal cord

injury

806.60 DMMPO Closed fracture sacrum 0.25 200 0

and coccyx vv/unspec

spinal cord injury

806.70 DMMPO Open fracture sacrum 1.00 241 0

and coccyx vv/unspec.

spinal cord injury

807.0 DMMPO Closed fracture of rib(s) 0.10 60 0

807.1 DMMPO Open fracture of rib(s) 1.00 284 1 0.5

807.2 DMMPO Closed fracture of 0.10 200 0

sternum

807.3 DMMPO Open fracture of 1.00 241 0

sternum

808.8 DMMPO Fracture of pelvis 0.95 313 0

unspecified, closed

808.9 DMMPO Fracture of pelvis 1.00 329 0

unspecified, open

810.0 DMMPO Clavicle fracture, closed 0.35 45 0

810.1 DMMPO Clavicle fracture, open 1.00 241 0 810.12 DMMPO Open fracture of shaft 1.00 241 1 0.5 of clavicle

811.0 D MPO Fracture of scapula, 0.10 200 0

closed

811.1 DMMPO Fracture of scapula, 1.00 241 1 0.5

open

812.00 DMMPO Fracture of unspecified 0.25 200 0

part of upper end of

humerus, closed

PC Type Description P(Surg) SurgTime Recur ecurTime

(mins) (days) (hours)

813.8 DMMPO Fracture unspecified 0.25 200 0

part of radius and ulna

closed

813.9 DMMPO Fracture unspecified 1.00 256 1 0,5

part of radius and ulna

open

815,0 DMMPO Closed fracture of 0.10 211 0

metacarpal bones

816.0 DMMPO Phalanges fracture, 0.10 211 0

closed

816.1 DMMPO Phalanges fracture, 1.00 84 1 0.5

open

817.0 DMMPO Multiple closed fractures 0.10 68 0

of hand bones

817.1 DMMPO Multiple open fracture 1.00 86 1 0.5

of hand bones

820.8 DMMPO Fracture of femur neck, 0.25 200 0

closed

820.9 DMMPO Fracture of femur neck, 1.00 241 1 0,5

open

821.01 DMMPO Fracture shaft femur, 1.00 208 0

closed

821,11 DMMPO Fracture shaft of femur, 1.00 238 1 0.5

open

822.0 DMMPO Closed fracture of 0.2S 200 0

paxeiia

822.1 DMMPO Open fracture of patella 1.00 229 1 0,5

323_*82 DMMPO Fracture tib fib, closed 0.25 233 0

823.9 DMMPO Fracture of unspecified 1.00 258 1 0.5

part of tibia and fibula

open

824.8 DMMPO Fracture ankle, nos, 0.25 222 0

closed

824.9 DMMPO Ankle fracture, open 1.00 251 1 0.5

825.0 DMMPO Fracture to calcaneus, 0.25 200 0

closed 826,0 DMMPO Closed fracture of one 0.10 211 0 or more phalanges of

foot

829,0 DMMPO Fracture of unspecified 0.25 200 0

bone, closed

830.Q DMMPO Closed dislocation of 0.00 Q

jaw

83Q.1 DMMPO Open dislocation of jaw 0.10 235 1 0.5

PC Type Description P(Surg) SurgTime Recur ecurTime

(mins) (days) (hours)

831 DMMPO Dislocation shoulder 0.00 0

831.04 DMMPO Closed dislocation of 0.00 0

acromioclavicular joint

831.1 DMMPO Dislocation of shoulder, 0.10 235 1 0.5

open

832.0 DMMPO Dislocation elbow. 0.00 0

closed

832.1 DMMPO Dislocation elbow, open 0.10 235 1 0.5

833 DMMPO Dislocation wrist closed 0.45 120 0

833,1 DMMPO Dislocated wrist, open 0.45 233 1 0.5

834.0 DMMPO Dislocation of finger, 0.00 0

closed

834.1 DMMPO Dislocation of finger, 0.10 235 1 0.5

open

835 DMMPO Closed dislocation of 0.00 0

hip

835.1 DMMPO Hip dislocation open 0.45 235 0

836.0 DMMPO Medial meniscus tear 0.00 0

8361 DMMPO Lateral meniscus tear 0.00 0

836.2 DMMPO Meniscus tear of knee 0.00 0

836.5 DMMPO Dislocation knee, closed 0.00 0

836.6 DMMPO Other dislocation of 0.45 235 1 0.5

knee open

839.01 DMMPO Closed dislocation first 0.00 0

cervical vertebra

840.4 DMMPO Rotator cuff sprain 0.00 0

840.9 DMMPO Sprain shoulder 0.00 0

843 DMMPO Sprains and strains of 0.00 0

hip and thigh

844.9 DMMPO Sprain, knee 0.00 0

845 DMMPO Sprain of ankle 0.00 0

846 DMMPO Sprains and strains of 0.00 0

sacroiliac region 846.0 DMMPO Sprain of lumbosacral 0.00 0

(joint} {ligament)

847.2 DMMPO Sprain lumbar region 0.00 0

847,3 DMMPO Sprain of sacrum 0,00 0

848.1 DMMPO Jaw sprain 0.00 0

8483 DMMPO Sprain of ribs 0.00 0

850.9 DMMPO Concussion 0.00 0

PC Type Description P(Surg) Surg Time Recur RecurTirne

(rnins) (days) (hours)

851.0 DMMPO Cortex (Cerebral) 0.00 0

contusion w/o open

intracranial wound

851.01 DMMPO Cortex (Cerebral) 0.00 0

contusion w/o open

wound no loss of

consciousness

852 DMMPO Subarachnoid subdural 0.15 338 0

extradural hemorrhage

injury

853 DMMPO Other and unspecified 0.15 335 0

intracranial hemorrhage

injury w/o open wound

853.15 DMMPO Unspecified intracranial 015 337 1 0,5

hemorrhage with open

intracranial wound

860.0 DMMPO Traumatic 0.30 250 0

pneumothorax w/o

open wound into thorax

860.1 DMMPO Traumatic 0.30 250 1 0.5

pneumothorax vv/open

wound into thorax

860.2 DMMPO Traumatic hemothorax 0.30 250 0

w/o open wound into

thorax

8603 DMMPO Traumatic hemothorax 0.30 250 1 0.5

with open wound into

thorax

860.4 DMMPO Traumatic 0.06 241 0

pneumohemothorax

w/o open wound thorax

860.5 DMMPO Traumatic 0,30 250 1 0,5

pneumohemothorax

with open wound thorax

861.0 DMMPO injury to heart w/o open 0,38 229 0

wound into thorax 851.10 DMMPO Unspec. injury of heart 1.00 268 0.5 w/open wound into

thorax

861.2 DMMPO Injury to lung, nos, 0.30 250 0

closed

8613 DMMPO injury to lung nos, open 0.30 250 1 0.5

863.0 DMMPO Stomach injury, w/o 1.00 390 0

open wound into cavity

PC Type Description P(Surg) SurgTime Recur RecurTime

(mins) (days) (hours)

86410 DMMPO Unspecified injury to 1.00 434 1 0,5

liver with open wound

into cavity

865 DMMPO injury to spieen 1.00 411 0

866.0 DMMPO injury kidney w/o open 1.00 390 0

wound

866.1 DMMPO Injury to kidney with 1.00 415 1 0.5

open wound into cavity

867.0 DMMPO Injury to bladder urethra 1.00 352 0

without open wound

into cavity

867.1 DMMPO injury to bladder and 1.00 397 1 0,5

urethrea with open

wound into cavity

867.2 DMMPO Injur ' to ureter w/o 1.00 352 0

open wound into cavity

8673 DMMPO Injury to ureter with 1.00 352 1 0.5

open wound into cavity

867.4 DMMPO Injury to uterus w/o 1.00 352 0

open wound into cavity

867.5 DMMPO Injury to uterus with 1.00 352 1 0.5

open wound into cavity

870 DMMPO Open wound of ocular 0.63 30 0

adnexa

870.3 DMMPO Penetrating wound of 0.63 30 0

orbit without foreign

body

870.4 DMMPO Penetrating wound of 0.78 30 0

orbit with foreign body

871.5 DMMPO Penetration of eyeball 0.10 167 0

with magnetic foreign

body

872 DMMPO Open wound of ear 0.23 30 1 0.5

873.4 DMMPO Open wound of face 0.22 226 1 0.5

without mention of

complication 873.8 DMMPO Open head wound w/o 0.25 236 1 0.5 complication

873.9 D PO Open head wound with 033 369 1 0.5

complications

874.8 DMMPO Open wound of other 0.25 236 1 0.5

and unspecified parts of

neck w/o complications

PC Type Description P(Surg) SurgTime Recur ecurTime

(mins) (days) (hours)

875.0 DMMPO Open wound of chest 0.33 266 £ 0.5

(wall) without

complication

876.0 DMMPO Open wound of back 0.40 278 1 0.5

without complication

877,0 DMMPO Open wound of buttock 0.00 0

without complication

878 DMMPO Open wound of genital 0.72 206 1 0.5

organs (external)

including traumatic

amputation

879.2 DMMPO Open wound of 0.50 397 2 0.5

abdominal wall anterior

w/o complication

879.6 DMMPO Open wound of other 0.40 278 2 0.5

unspecified parts of

trunk without

complication

879.8 DMMPO Open wound(s) 0.00 0

(multiple) of unspecified

sitefs) w/o complication

880 DMMPO Open wound of the 0.25 228 1 0.5

shoulder and upper arm

881 DMMPO Open wound elbows, 010 210 I 0.5

forearm, and wrist

882 DMMPO Open wound hand 0.00 0

except fingers alone

883.0 DMMPO Open wound of fingers 0.64 244 1 0.5

without complication

884.0 DMMPO Multiple/unspecified 0.64 244 I 0.5

open wound upper limb

without complication

885 DMMPO Traumatic amputation 0.82 244 1 0.5

of thumb (complete)

(partial)

886 DMMPO Traumatic amputation 0.82 244 1 0.5

of other finger(s)

(complete) (partial) 887 DMMPO Traumatic amputation 1,00 0.5 of arm and hand

(complete) (partial)

890 DMMPO Open wound of hip and 0.25 226 0.5

thigh

891 DMMPO Open wound of knee 0.25 215 0.5

ieg (except thigh) and

ankle

PC Type Description ³(Surg) SurgTirne Recur ReeurTime

(reins) (days) (hours)

892.0 DMMPO Open wound foot 0.64 244 1

except toes alone w/o

complication

894.0 DMMPO Multiple/unspecified 0.54 0.5

open wound of lower

limb w/o complication

895 DMMPO Traumatic amputation 1,00 0.5

of toeis) (complete)

(partial)

896 DMMPO Traumatic amputation 1.00 297 0.5

of foot (complete)

(partial)

897 DMMPO Traumatic amputation 1.00 294 0.5

of leg(s) (complete)

(partial)

903 DMMPO Injury to blood vessels 1.00 198 0

of upper extremity

904 DMMPO Injury to blood vessels 1.00 200 0

of lower extremity and

unspec. sites

910.0 DMMPO Abrasion/friction burn 0.00

of face, neck, scaSp w/o

infection

916.0 DMMPO Abrasion/friction burn 0.Q0

of hip, thigh, ieg, ankle

w/o infection

916.1 DMMPO Abrasion/friction burn 0.00

of hip, thigh, leg, ankle

with infection

916.2 DMMPO Blister hip & leg 0,00 0 9163 DMMPO Blister of hip thigh leg 0.00 0

and ankle infected

916.4 DMMPO Insect bite nonvsnom 0.00

hip, thigh, leg, ankle w/o

infection

916.5 DMMPO Insect bite nonvenom 0.00

hip, thigh, leg, ankle,

with infection 918.1 D PO Superficial injury cornea 0.00 0

920 DMMPO Contusion of face scalp 0.00 0

and neck except eye(s)

921.0 DMMPO Black eye 0.00 0

922.1 DMMPO Contusion of chest wail 0.00 0

922.2 DMMPO Contusion of abdominal 0.00 0

waj!

PC Type Description P(Surg) SurgTime Recur RecurTime

(mlns) _m i^^ours)„

922.4 DMMPO Contusion of genital 0.00 0

organs

924.1 DMMPO Contusion of knee and 0.00 0

lower leg

924.2 DMMPO Contusion of ankle and 0.00 0

foot

9243 DMMPO Contusion of toe 0.00 0

925 DMMPO Crushing injury of face, 0.25 385 1 0.5

scalp & neck

926 DMMPO Crushing injury of trunk 0.25 318 1 0.5

927 DMMPO crushing injury of upper 0.61 317 1 0.5

!imb

928 DMMPO Crushing injury of tower 0.33 272 1 0.5

limb

930 DMMPO Foreign Body on 0.00 0

External Eye

935 DMMPO Foreign body in mouth, 1.00 200 0

esophagus and stomach

941 DMMPO Burn of face, head, neck 0.33 60 0

942.0 DMMPO Burn of trunk, 0.49 60 0

unspecified degree

943.0 DMMPO Burn of upper limb 0.48 60 0

except wrist and hand

unspec. degree

944 DMMPO Burn of wrist and hand 0.40 60 0

945 DMMPO Burn of lower limb(s) 0.50 120 0

950 DMMPO Injury to optic nerve and 0.60 120 0

pathways

953.0 DMMPO Injury to cervical nerve 0,35 60 0

root

953.4 DMMPO Injury to brachial plexus 0,57 60 0

955.0 DMMPO Injury to axillary nerve 0.64 60 0

956.0 DMMPO Injury to sciatic nerve 0.43 60 0

959.01 DMMPO Other and unspecified 0.35 60 0

injury to head 959.09 DMMPO Other and unspecified 0.35 0.5 injury to face and neck

959.7 D PO Other and unspecified 0.14 60

injury to knee Isg ankle

and foot

989.5 DMMPO Toxic effect of venom 0.00

PC Type Description P(Surg) SurgTime Recur Rec

subst chiefly

rtonrnedicinai/source

991.3 DMMPO Frostbite 0.00 0

991.6 DMMPO Hypothermia 0.Q0 0

992.0 DMMPO Heat stroke and sun 0.00 0 stroke

992.2 DMMPO Heat cramps 0.00 0

992.3 DMMPO Heat exhaustion 0.00 0 anhydrotic

994.0 DMMPO Effects of lightning 0.00 0

994.1 DMMPO Drowning and nonfatai 0.00 0 submersion

994.2 DMMPO Effects of deprivation of 0.00 0 food

994.3 DMMPO Effects of thirst 0.00 0

994,4 DMMPO Exhaustion due to 0.00 0 exposure

994.5 DMMPO Exhaustion due to 0.00 0 excessive exertion

994,6 DMMPO Motion sickness 0.00 0

994.8 DMMPO Electrocution and 0.00 0 nonfatal effects of

electric current

995.0 DMMPO Other anaphylactic 0,00 0 shock not elsewhere

classified

E991.2 DMMPO Injury due to war ops 0.63 90 i 0.5 from other bullets (not

rubber/peilets)

E991.3 DMMPO Injury due to war ops 0.76 90 1 0.5 from antipersonnel

bomb fragment

E991.9 DMMPO Injury due to war ops 0.69 90 1 0.5 other unspecified

fragments E993 D PO injury due to war ops by 0.71 90 1 0.5 other explosion

VOLS DMMPO Contact with or Q.0O 0

exposure to rabies

V79.0 DMMPO Screening for 0.00 0

depression

001.9 Extended Cholera unspecified 0.00 0

PC Type Description P(Surg) SurgTime Recur RecurTime

(mins) (days) (hours)

002.0 Extended Typhoid fever 0.00 0

004.9 Extended Shigellosis unspecified 0.00 0

055.9 Extended Measles 0.00 0

072.8 Extended Mumps with unspecified 0.00 0

complication

072.9 Extended Mumps without 0.QQ 0

complication

110.9 Extended Dermatophytosis, of 0.00 0

unspecified site

12S.9 Extended Other and unspecified 0.00 0

Helminthiasis

132.9 Extended Pediculosis and Phthirus 0.00 0

infestation

133.0 Extended Scabies 0.00 0

184.9 Extended Malignant neoplasm of 0.00 0

other and unspecified

female genital organs

239.0 Extended Neoplasms of 0.80 60 0

Unspecified Nature

246.9 Extended Unspecified Disorder of 0.00 ft

Thyroid

250.00 Extended Diabetes e!iitus w/o 0.00 0

complication

264.0 Extended Vitamin A deficiency 0.00 0

269.8 Extended Other nutritional 0.00 0

deficiencies

276.51 Extended Volume Depletion, 0.00 0

Dehydration

277.89 Extended Other and unspecified 0.00 0

disorders of metabolism

280.8 Extended Iron deficiency anemias 0.00 0

300.00 Extended Anxiety states 0.00 0

349.9 Extended Unspecified disorders of 0.00 0

nervous system

368.00 Extended Cataract 0.00 0

369.9 Extended Blindness and low vision 0.00 0 Extended Conjunctivitis,

unspecified

379.90 Extended Other disorders of eye 0.00 0

380.9 Extended Unspecified disorder of 0.00 0

external ear

383.1 Extended Chronic mastoiditis 0.00 0

PC Type Description P{Surg) SurgTime Recur ecurTime

(rnins) (days) (hours)

386,10 Extended Other and unspecified 0.00 0

peripheral vertigo

386.2 Extended Vertigo of central origin 0.00 0

388.8 Extended Other disorders of ear 0.07 30 0

411.81 Extended Acute coronary 0.00 0

occlusion without

myocardial infarction

428.40 Extended Heart failure 0.00 0

437.9 Extended Cerebrovascular disease, 0.00 0

unspecified

443.89 Extended Other peripheral 0.00 0

vascular disease

459.9 Extended Unspecified circulatory 0.00 0

system disorder

477.9 Extended Allergic rhinitis 0.00 0

519.8 Extended Other diseases of 0.06 30 0

respiratory system

521.00 Extended Dents! caries 0.00 0

522.0 Extended Pulpitis 0.00 0

525.19 Extended Other diseases and 0.00 0

conditions of the teeth

and supporting

structures

527.8 Extended Diseases of the salivary 0.01 30 0

glands

569.83 Extended Perforation of intestine 0.58 30 0

571.40 Extended Chronic hepatitis 0,00 0

571.5 Extended Cirrhosis of liver without 0.00 0

alcohol

594.9 Extended Calculus of lower urinary 0.04 60 0

tract, unspecified

S99.8 Extended Urinary tract infection, 0.00 0

site not specified

600.90 Extended Hyperplasia of prostate 0.00 0

608.89 Extended Other disorders of male 0.50 30 0

■enital organ 614.9 Extended Inflammatory disease of 0.05 45 0 female pelvic

organs/tissues

616.10 Extended Vaginitis and 0.00 0

vulvovaginitis

623.5 Extended Leukorrhea not 0.00 0

specified as infective

PC Type Description PiSurg} SurgTirne Recur RecurTirne

(mins) (days) (hours)

626.8 Extended Disorders of 0.18 45 0

menstruation and other

abnormal bleeding from

female genital tract

629.9 Extended Other disorders of 0.00 0

female genital organs

650 Extended Normal delivery 0.00 0

653.S1 Extended Disproportion in 0,00 0

pregnancy labor and

delivery

690.8 Extended Erythematosquamous 0.00 0

dermatosis

6918 Extended Atopic dermatitis and 0.00 0

related conditions

692.9 Extended Contact Dermatitis, 0.00 0

unspecified cause

693.8 Extended Dermatitis due to 0.00 0

substances taken

internally

696.1 Extended Other psoriasis and 0.00 0

similar disorders

709.9 Extended Other disorders of skin 0.15 45 0

and subcutaneous tissue

714.0 Extended Rheumatoid arthritis 0.00 0

733.90 Extended Disorder of bone and 0.28 60 0

cartilage, unspecified

779.9 Extended Other and ill-defined 0.00 0

conditions originating in

the perinatal period

780.79 Extended Other malaise and 0.00 0

fatigue

780,96 Extended Generalized pain 0.00 0

786.2 Extended Cough 0.00 0

842.00 Extended Sprain of unspecified 0.00 0

site of wrist Table 9C ) E RE Cc jmmon Data: Bee i Data

PC Type Descri tion ORE IJMLC }S ORWardl LOS oORICU LOS oOH ardLO

(days) (days) (days) 5

fdays)

005 DMMPO Food poisoning 0 0 0 5

bacterial

006 DMMPO Amebiasis 0 0 0 10

007,9 DMMPO Unspecified 0 0 0 10

protozoa!

intestinal disease

008.45 DMMPO Intestinal 0 0 0 30

infection due to

Clostridium

difficile

008.8 DMMPO Intestinal 0 0 0 30

infection due to

other organism

not classified

010 DMMPO Primary tb 0 Q 0 180

037 DMMPO Tetanus 0 0 0 14

038.9 DMMPO Unspecified 0 0 1 13

septicemia

042 DMMPO Human 0 0 0 180

immunodeficienc

y virus [HIV]

disease

047.9 DMMPO Viral meningitis 0 0 1 13

052 DMMPO Varsceiia 0 0 0 14

053 DMMPO Herpes zoster 0 0 0 10

054.1 DMMPO Genital herpes 0 0 0 3

057.0 DMMPO Fifth disease 0 0 0 14

060 DMMPO Yeiiow fever 0 0 I 180

061 DMMPO Dengue 0 0 0 180

062 DMMPO Mosq. borne 0 0 1 13

encephalitis

063.9 DMMPO Tick borne 0 0 1 13

encephalitis

065 DMMPO Arthropod-borne 0 0 1 13

hemorrhagic

fever

066.40 DMMPO West nile fever, 0 0 0 30

unspecified

070.1 DMMPO Viral hepatitis 0 0 0 30

071 DMMPO Rabies 0 0 0 180 PC Type Description O ICULOS ORWardLOS NoORICULOS NoORWardLOS

(days) (days) (days) (days)

076 DMMPO Trachoma 0 0 0 10

078.0 DMMPO olluscom 0 0 0 1

contagiosum

07S.1 DMMPO Viral warts Q 0 0 1

078.4 DMMPO Hand, foot and 0 0 0 14

mouth disease

0793 DMMPO Rhinovirus 0 0 0 3

infection in

conditions

elsewhere and of

unspecified site

079.99 DMMPO Unspecified vtra! 0 0 0 180

infection

082 DMMPO Tick-borne 0 0 0 10

rickettsiosis

084 DMMPO Malaria 0 0 0 30

085 DMMPO Leishmaniasis, 0 0 0 30

visceral

086 DMMPO Trypanosomiasis 0 0 0 14

091 DMMPO Eariy primary 0 0 0 5

syphilis

091,9 DMMPO Secondary 0 Q 0 5

syphilis, unspec

094 DMMPO Neurosyphilis 0 0 1 180

098.5 DMMPO Gonococcal 0 Q 0 14

arthritis

099,4 DMMPO Nongonnococcal 0 Q 0 1

urethritis

100 DMMPO Leptospirosis Q 0 2 12

274 DMMPO Gout 0 0 0 5

27β DMMPO Disorder of fluid, 0 0 0 3

electrolyte + acid

base balance

296.0 DMMPO Bipolar disorder, 0 0 0 30

single manic

episode

298.9 DMMPO Unspecified 0 0 0 30

psychosis

309.0 DMMPO Adjustment 0 0 0 30

disorder with

depressed mood

309.81 DMMPO Ptsd 0 0 0 30 PC Type Description Q ICULQS ORWardLOS NoORlCULOS NoO WardLOS

(days) (days) (days) (days)

309.9 DMMPO Unspecified 0 0 0 14

adjustment

reaction

310.2 DMMPO Post concussion 0 C 0 7

syndrome

345.2 DMMPO Epilepsy petit 0 c 1 ISO

mai

3453 DMMPO Epilepsy grand 0 0 1 180

mai

346 DMMPO Migraine 0 0 0 3

361 DMMPO Retinal 0 0 0 7

detachment

364.3 DMMPO Uveitis nos 0 0 0 7

365 DMMPO Glaucoma 0 0 0 180

370.0 DMMPO Corneal ulcer 0 0 0 5

379.31 DMMPO Aphakia 0 0 0 7

380.1 DMMPO Infective otitis 0 0 0 1

externa

3S0.4 DMMPO Impacted 0 0 0 3

cerumen

381 DMMPO Acute 0 0 0 3

nonsuppurative

otitis media

381.9 DMMPO Unspecified 0 0 0 3

eustachian tube

disorder

384.2 DMMPO Perforated 0 0 0 10

tympanic

membrane

SS83 DMMPO Tinnitus, 0 0 0 3

unspecified

389,9 DMMPO Unspecified 0 0 0 5

hearing loss

401 DMMPO Essential 0 0 0 14

hypertension

410 DMMPO Myocardial 0 0 1 SO

infarction

413.9 DMMPO Other and 0 0 0 180

unspecified

angina pectoris

427.9 DMMPO Cardiac 0 0 0 180

dysryhthmia

unspecified Description ORiCULOS ORWardLOS NoO ICULOS NoO WardLOS

(days) (days) (days) (days)

453.4 D PO Venous 0 0 1 30

emboiisrn/throm

bus of deep

vessels lower

extremity

462 DM PO Acute 0 0 0 7

pharyngitis

465 DM PO Acute uri of 0 0 0 5

multiple or

unspecified sites

466 DMMPO Acute bronchitis 0 Q 0 10

& bronchiolitis

475 DMMPO Peritonsillar 0 10 0 10

abscess

486 DMMPO Pneumonia, 0 0 0 7

organism

unspecified

491 DMMPO Chronic 0 0 0 14

bronchitis

492 DMMPO Emphysema 0 0 0 14

493.9 DMMPO Asthma 0 0 0 1

523 DMMPO Gingival and 0 0 0 2

periodontal

disease

530,2 DMMPO Uicer of 0 0 0 14

esophagus

530,81 DMMPO Gastroesophage 0 0 0 5

a! reflux

531 DMMPO Gastric uicer 0 0 0 14

532 DMMPO Duodenal uicer 0 5 0 5

540.9 DMMPO Acute 0 30 0 30

appendicitis

without mention

of peritonitis

541 DMMPO Appendicitis, 0 30 0 30

unspecified

550.9 DMMPO Unilateral 0 30 0 30

inguinal hernia

553.1 DMMPO Umbilical hernia 0 14 0 14

553.9 DMMPO Hernia nos 0 14 0 14

564.0 DMMPO Constipation 0 0 0 1

564.1 DMMPO Irritable bowel 0 0 0 30

disease PC Type Description OR1CULOS ORWardLOS NGO IGULOS NoORWardi

(days) (days) (days) (days)

566 D MPO Abscess of ami 0 30 0 30

and recta!

regions

567.9 D MPO Unspecified 0 0 0 30

peritonitis

574 DMMPO Cholelithiasis 0 14 0 14

577.0 DMMPO Acute 0 0 1 180 pancreatitis

577.1 DMMPO Chronic 0 0 1 180 pancreatitis

578.9 DMMPO Hemorrhage of 0 0 0 7

gastrointestinal

tract unspecified

584.9 DMMPO Acute renal 0 0 2 180 failure

unspecified

592 DMMPO Ca!cuius of 0 0 0 ?

kidney

599.0 DMMPO Unspecified 0 0 0 3

urinary tract

infection

599.7 DMMPO Hematuria 0 0 0 3

608.2 DMMPO Torsion of testes 0 180 0 180

608.4 DMMPO Other 0 0 0 10

inflammatory

disorders of male

geniia! organs

611.7 DMMPO Breast lump 0 0 0 14

633 DMMPO Ectopic preg 0 30 0 30

634 DMMPO Spontaneous 0 30 0 30

abortion

681 DMMPO Cellulitis and 0 0 0 7

abscess of finger

and toe

682.0 DMMPO Cellulitis and 0 0 0 7

abscess of face

682.6 DMMPO Cellulitis and 0 0 0 7

abscess of leg

except foot

682,7 DMMPO Cellulitis and 0 0 0 7

abscess of foot

except toes

682.9 DMMPO Cellulitis and 0 0 0 7

abscess of

unspecified parts PC Type Description ORICULOS O WardLOS NoO iCULOS NoO WardLOS

J^days) (days) (days) (days)

719.41 DMMPO Pain in joint 0 0 0 14

shoulder

719,46 DMMPO Pain in joint 0 0 0 14

lower leg

719,47 DMMPO Pain in joint 0 0 0 14

ankle/foot

722.1 DMMPO Displacement 0 0 0 30

lumbar

intervertebral

disc w/o

myelopathy

723.0 DMMPO Spinal stenosis in 0 0 0 30

cervical region

724.02 DMMPO Spinal stenosis of 0 0 0 30

lumbar region

724,2 DMMPO Lumbago 0 G 0 5

724.3 DMMPO Sciatica 0 0 0 30

724,4 DMMPO Lumbar sprain 0 0 0 5

{thoracic/lumbos

acrai) neuritis or

radiculitis,

unspec

724.5 DMMPO Backache 0 0 0 5

unspecified

726.10 DMMPO Disorders of 0 0 0 14

bursae and

tendons in

shoulder

unspecified

726.12 DMMPO Bicipital 0 0 0 14

tenosynovitis

726.3 DMMPO Enthesopathy of 0 0 0 14

elbow region

726.4 DMMPO Enthesopathy of 0 0 0 14

wrist and carpus

726.5 DMMPO Enthesopathy of 0 0 0 14

hip region

726.6 DMMPO Enthesopathy of 0 0 0 14

knee

725.7 DMMPO Enthesopathy of 0 0 0 14

ankle and tarsus

729.0 DMMPO Rheumatism 0 0 0 14

unspecified and

fsbrositis

729.5 DMMPO Pain in limb 0 0 0 14

332 C Type Description O iCULOS ORWardLOS NoQRICULOS NoO WardLOS

(days) (days) (days) (days)

780.0 DMMPO Alterations of 0 0 0 10

consciousness

780.2 DMMPO Syncope 0 0 0 3

780.39 DMMPO Other 0 0 0 10

convulsions

780.5 DMMPO Sleep 0 0 0 4

disturbances

780.6 DMMPO Fever 0 0 0 5

782.1 DMMPO Rash and other 0 0 0 4

nonspecific skin

eruptions

782.3 DMMPO Edema 0 0 0 4

783.0 DMMPO Anorexia 0 0 Q 4

784.0 DMMPO Headache 0 0 0 10

784.7 DMMPO Epistaxis 0 0 0 4

784.8 DMMPO Hemorrhage 0 0 0 10

from throat

786.5 DMMPO Chest pain 0 0 0 10

787.0 DMMPO Nausea and 0 0 0 4

vomiting

787.91 DMMPO Diarrhea nos 0 0 0 5

789.00 DMMPO Abdominal pain 0 0 0 10

unspecified site

800.0 DMMPO Closed fracture 0 0 2 ISO

of vault of skull

without

intracranial injury

801.0 DMMPO Closed fracture 2 ISO 2 180

of base of skull

without

intracranial injury

801.76 DMMPO Open fracture 3 180 3 180

base of skull with

subarachnoid,

subdural and

extradural

hemorrhage with

loss of

consciousness of

unspecified

duration

802.0 DMMPO Closed fracture 0 180 0 180

of nasal bones PC Type Description O ICULOS O WardLOS NoO ICULOS NoO WardLOS

(days) (days) (days) (days)

80ΖΪ DMMPO Open fracture of 180

nasal bones

802.6 DMMPO Fracture orbital 180 180

floor closed

[blowout)

802.7 DMMPO Fracture orbital 180 180

floor open

(blowout)

502.8 DMMPO Closed fracture 180 180

of other facial

bones

502.9 DMMPO Open fracture of 180

other facial

bones

80S DMMPO Closed fracture 180

of cervical

vertebra w/o

spinal cord injury

806.1 DMMPO Open fracture of 180

cervical vertebra

with spina! cord

injury

806.2 DMMPO Closed fracture 180 ISO

of dorsal

vertebra with

spinal cord injury

8053 DMMPO Open fracture of 180 180

dorsal vertebra

with spinal cord

injury

806.4 DMMPO Closed fracture 180

of lumbar spine

with spinal cord

injury

806.5 DMMPO Open fracture of 180

lumbar spine

with spinal cord

injury

806.60 DMMPO Closed fracture 180

sacrum and

coccyx w/unspec.

spinal cord injury

806.70 DMMPO Open fracture ISO 180

sacrum and

coccyx w/unspec.

spinal cord inju Description O ICULOS ORWardLOS NoORICULOS NoORWardLOS

[days) (days) (days) (days)

807.0 DMMPO Closed fracture 0 30 0 30

of rib(s)

807.1 DMMPO Open fracture of 0 180 0 180

rib(s)

807.2 DMMPO Closed fracture 0 18Q 0 180

of sternum

807.3 DMMPO Open fracture of 0 180 0 180

sternum

808.8 DMMPO Fracture of pelvis 1 180 1 180

unspecified,

ciosed

808.9 DMMPO Fracture of pelvis 1 180 1 180

unspecified,

open

810.0 DMMPO Clavicle fracture, 0 30 0 30

closed

810.1 DMMPO Clavicle fracture, 0 180 0 180

open

810.12 DMMPO Open fracture of 0 180 0 180

shaft of clavicle

811.0 DMMPO Fracture of 0 180 0 180

scapula, closed

811.1 DMMPO Fracture of 0 ISO 0 180

scapula, open

812.00 DMMPO Fracture of 0 180 0 180

unspecified part

of upper end of

humerus, ciosed

813.8 DMMPO Fracture 0 180 0 180

unspecified psrt

of radius and

ulna closed

813.9 DMMPO Fracture 0 180 0 180

unspecified part

of radius and

ulna open

815.0 DMMPO Closed fracture 0 180 0 180

of metacarpal

bones

816.0 DMMPO Phalanges 0 180 0 180

fracture, closed

816.1 DMMPO Phalanges 0 30 0 30

fracture, open

817.0 DMMPO Multiple dosed 0 30 0 30

fractures of hand Description ORICULOS G WardLOS NoQ !CULOS MoORWardLOS

817.1 DMMPO Multiple open 0 180 0 180

fracture of hand

bones

820.8 DMMPO Fracture of femur 0 180 180

neck, closed

820.9 DMMPO Fracture of femur 0 180 180

neck, open

821.01 DMMPO Fracture shaft 0 180 180

femur, closed

821.11 DMMPO Fracture shaft of 0 180 180

femur, open

822.0 DMMPO Closed fracture 0 180 180

of patella

8221 DMMPO Open fracture of 0 180 0 180

patella

823.82 DMMPO Fracture tib fib, 0 180 0 180

closed

823.9 DMMPO Fracture of 0 180 0 180

unspecified part

of tibia and

fibula open

824.8 DMMPO Fracture ankle, 180 0 180

nos, closed

824.9 DMMPO Ankle fracture, 180 0 180

open

825.0 DMMPO Fracture to 0 180 0 180

calcaneus, closed

826.0 DMMPO Closed fracture 0 180 0 180

of one or more

phalanges of

DMMPO Fracture of 180 180

unspecified

bone, closed

830.0 DMMPO Closed

dislocation of

jaw

830.1 DMMPO Open dislocation 180 180

of jaw

831 DMMPO Dislocation

shoulder

831.04 DMMPO Ciosed 14

dislocation of

acromioclavicular

joint PC Type Description O iCULOS ORWardLOS NoO ICULOS NoO WatdLOS

(days) (days) (days) (days)

831.1 DMMPO Dislocation of 0 180 0 180

shoulder, open

832.0 DMMPO Dislocation 0 0 0 30

elbow, closed

832.1 DMMPO Dislocation 0 180 0 180

elbow, open

833 DMMPO Dislocation wrist Q 30 0 30

closed

833.1 DMMPO Dislocated wrist, 0 30 0 30

open

834.0 DMMPO Dislocation of 0 0 0 3

finger, closed

834.1 DMMPO Dislocation of 0 30 0 30

finger, open

835 DMMPO Closed 0 0 0 30

dislocation of hip

835.1 DMMPO Hip dislocation Q 180 0 180

open

836.0 DMMPO Medial meniscus 0 0 0 2

tear

836.1 DMMPO Lateral meniscus 0 0 0 2

tear

836.2 DMMPO Meniscus tear of 0 0 0 2

knee

836.5 DMMPO Dislocation knee, 0 0 0 14

ioseo

836.8 DMMPO Other dislocation 0 180 0 180

of knee open

839.01 DMMPO Closed 0 0 1 13

dislocation first

cervical vertebra

840.4 DMMPO Rotator cuff 0 Q 0 3

sprain

840.9 DMMPO Sprain shoulder 0 0 0 3

843 DMMPO Sprains and 0 0 0 3

strains of hip and

thigh

844.9 DMMPO Sprain, knee 0 0 0 5

845 DMMPO Sprain of ankle 0 0 0 5

846 DMMPO Sprains and 0 0 0 5

strains of

socroiliac region

846.0 DMMPO Sprain of 0 0 0 5

lumbosacral

(joint) {ligament} PC Type Des ription O ICULOS O WardLOS NoO ICULOS NoO WardLOS

(days) (days) (days) (days)

847.2 DMMPO Sprain lumbar Q 0 0 3

region

847.3 DM PO Sprain of sacrum 0 0 0 3

848.1 DMMPO Jaw sprain 0 0 Q 3

848.3 DMMPO Sprain of ribs 0 0 0 3

850.9 DMMPO Concussion 0 0 0 7

851.0 DMMPO Cortex (Cerebral) 0 0 2 30

contusion w/o

open intracranial

wound

851.01 DMMPO Cortex (Cerebral) 0 0 2 30

contusion w/o

open wound no

toss of

consciousness

852 DMMPO Subarachnoid 2 180 2 ISO

subdural

extradural

hemorrhage

injury

853 DMMPO Other and 2 30 2 30

unspecified

intracranial

hemorrhage

m ry w/o open

wound

853.15 DMMPO Unspecified 3 180 3 180

intracranial

hemorrhage with

open intracranial

wound

860,0 DMMPO Traumatic 0 180 0 180

pneumothorax

w/o open wound

into thorax

860.1 DMMPO Traumatic 2 180 2 180

pneumothorax

w/open ound

into thorax

860.2 DMMPO Traumatic 2 180 2 180

hemothorax w/o

open wound into

thorax Type Description O JCULOS OR ardLOS NoO ICULOS NoO WardLOS d¾s) (da^s) (days) (days^')

8603 DMMPO Traumatic 2 180 2 180

hemothorax with

open wound into

thorax

860.4 DMMPO Traumatic 2 180 2 180

pnaumohernotb

orax w/o open

wound thorax

8605 DMMPO Traumatic 2 180 2 180

pneumohemoth

orax with open

wound thorax

861.0 DMMPO Injury to heart 3 ISO 2 180

w/o open wound

into thorax

861.10 DMMPO Unspec. injury of 3 180 3 180

heart w/open

wound into

thorax

861.2 DMMPO Injury to lung, 2 180 2 180

nos, closed

861.3 DMMPO Injury to iung 2 180 2 180

nos, open

863.0 DMMPO Stomach injury, 0 180 0 180

w/^'o open wound

into cavity

864.10 DMMPO Unspecified 1 180 1 180

injury to iiver

with open

wound into

cavity

865 DMMPO Injury to spleen 1 180 1 180

866.0 DMMPO Injury kidney w/o 0 180 0 180

open wound

866.1 DMMPO injury to kidney 0 180 0 180

with open

wound into

cavity

867.0 DMMPO Injury to bladder 0 180 0 180

urethra without

open wound into

cavity PC Type Description O iCULOS ORWardLOS NoQRiCULOS NoORWardLOS

(days) (days) (days) (days)

8671 DMMPO Injury to bladder 0

and urethrea

with open

wound into

cavity

867,2 DMMPO Injury to ureter 180

w/o open wound

into cavity

8673 DMMPO Injury to ureter 180

with open

wound into

cavity

867.4 DMMPO Injury to uterus 180 ISO

w/o open wound

into cavity

867.5 DMMPO Injury to uterus 180

with open

wound into

cavity

870 DMMPO Open wound of

ocuiar adnexa

8703 DMMPO Penetrating

wound of orbit

without foreign

body

870.4 DMMPO Penetrating

wound of orbit

with foreign

171.5 DMMPO Penetration of 30

eyebaii with

magnetic foreign

body

§72 DMMPO Open wound of 3

ear

373.4 DMMPO Open wound of 5

face without

mention of

complication

373.8 DMMPO Open head

wound w/o

complication

373.9 DMMPO Open head 13 13

wound with

complications PC Type Description ORJCUL05 O WardLOS NoORICULOS NoORWardLOS

(days) (days) (dsys)

874,8 DMMPO Open wound of

other and

unspecified parts

of neck w/o

complications

875.0 DMMPO Open wound of

chest (wall)

without

complication

876.0 DMMPO Open wound of

back without

complication

877.0 DMMPO Open wound of

buttock without

complication

DMMPO Open wound of 30 30

genital organs

{external}

including

traumatic

amputation

879.2 DMMPO Open wound of

abdominal wall

anterior w/o

complication

879.6 DMMPO Open wound of 14 14

other

unspecified parts

of trunk without

complication

879.8 DMMPO Open wound(s) 14

{multiple} of

unspecified

site(s) w/o

complication

380 DMMPO Open wound of

the shoulder and

upper arm

DMMPO Open wound

elbows, forearm,

and wrist

DMMPO Open wound

hand except

finaers alone PC Type Description ORICULOS O WardLOS NoOR!CULOS NoO WardLOS

(da s) (days) (days) (days)

883.0 DMMPO Open wound of 0 14 0 14

fingers without

complication

884.0 DMMPG Multiple/unspeci 0 180 0 180

fled open wound

upper !imb

without

complication

885 DMMPO Traumatic 0 14 0 14

amputation of

thumb

{complete}

(partial)

886 DMMPO Traumatic 0 180 0 180

amputation of

other finger(s)

(complete)

(partial)

887 DMMPO Traumatic 0 180 0 180

amputation of

arm and hand

(complete)

890 DMMPO Open wound of 0 7 0 7

hip and thigh

891 DMMPO Open wound of 0 7 0 7

knee leg (except

thigh) and ankle

892.0 DMMPO Open wound 0 14 0 14

foot except toes

alone w/o

complication

8940 DMMPO Multiple/unspeci 0 5 a 5

fied open wound

of lower limb

w/o complication

895 DMMPO Traumatic 0 180 0 180

amputation of

toe(s) (complete)

(partial)

896 DMMPO Traumatic 0 180 0 180

amputation of

foot (complete)

(partial) PC Type Description ORICULOS ORWardLOS oO ICULOS NoORWardLOS

(days) (days)

897 DMMPO Traumatic 2 180 2 180

amputation of

leg(s) (complete)

{partial}

903 DMMPO Injury to blood 0 180 0 180

vessels of upper

extremity

904 DMMPO Injury to blood 1 180 1 180

vessels of lower

extremity and

unspec. sites

910.0 DMMPO Abrasion/friction 0 0 0 3

burn ef face,

neck, scalp w/o

infection

916.0 DMMPO Abrasion/friction 0 0 0 3

bum of hip,

thigh,, leg. ankle

w/o infection

916.1 DMMPO Abrasion/friction 0 0 0 10

burn of hip,

thigh, leg, ankle

with infection

916.2 DMMPO Blister hip & leg 0 0 Q 3

916.3 DMMPO Blister of hip 0 0 0 10

thigh leg and

ankle infected

916.4 DMMPO insect bite 0 0 0 3

nonvenom hip,

thigh, leg, ankle

w/o infection

916.5 DMMPO Insect bite 0 0 0 10

nonvenom hip,

thigh, leg, ankle.

with infection

318.1 DMMPO Superficial injury 0 0 0 3

cornea

920 DMMPO Contusion of 0 0 0 2

face scalp and

neck except

eye(s)

921.0 DMMPO Black eye 0 0 0 2

322.1 DMMPO Contusion of 0 0 0 2

chest wall

922.2 DMMPO Contusion of 0 0 0 2

abdominal wall Description O ICULOS O WardLOS NoORJCULOS NoOR ardLOS

[days) (days) (days) (days)

922.4 D MPO Contusion of 0 0 0 3

genital organs

924.1 DMMPO Contusion of 0 0 0 2

knee and lower

leg

924.2 DMMPO Contusion of 0 0 0 2

ankle and foot

9243 DMMPO Contusion of toe 0 0 0 2

925 DMMPO Crushing injury 1 180 1 ISO

of face, scalp &

neck

926 DMMPO Crushing injur)' 2 180 2 180

of trunk

927 DMMPO crushing injury of 1 180 1 180

upper limb

928 DMMPO Crushing injury 1 180 1 180

of lower limb

930 DMMPO Foreign Body on 0 0 0 3

External Eye

935 DMMPO Foreign body in 0 7 0 7

mouth,

esophagus and

stomach

941 DMMPO Burn of face, 2 3 2 3

head, neck

942.0 DMMPO Burn of trunk, 2 30 2 30

unspecified

degree

943.0 DMMPO Burn of upper 1 13 1 13

limb except wrist

and hand

unspec. degree

944 DMMPO Bum of wrist and 0 14 0 14

hand

945 DMMPO Burn of lower 1 13 1 13

limb(s)

950 DMMPO Injury to optic 0 30 Q 30

nerve and

pathways

953.0 DMMPO Injury to cervical 0 10 0 10

nerve root

953.4 DMMPO Injury to brachial 0 30 0 30

plexus

955.0 DMMPO Injury to axillary 0 30 0 30

nerve Description OR!CULOS ORWardLOS NoORICULOS NoO WardLOS

(days) (da^s)_

956.0 DMMPO Injury to sciatic 0 30 0 30 ^"

nerve

959.01 DMMPO Other and 0 14 0 14

unspecified

injur)' to head

959.09 DMMPO Other and 0 14 0 14

unspecified

injury to face and

neck

959.7 DMMPO Other and 0 14 0 14

unspecified

injury to knee leg

ankle and foot

989.5 DMMPO Toxic effect of 0 0 0 3

venom

989.9 DMMPO Toxic effect 0 0 0 7

unspec subst

chiefly

nonmedicinat/so

urce

991,3 DMMPO Frostbite 0 0 0 5

991.6 DMMPO Hypothermia 0 0 1 9

992.0 DMMPO Heat stroke and 0 C 0 180

sun stroke

992.2 DMMPO Heat cramps 0 0 0 1

992.3 DMMPO Heat exhaustion 0 0 0 3

anhydrotic

994.0 DMMPO Effects of 0 0 1 6

lightning

994.1 DMMPO Drowning and 0 0 3 30

nonfatal

submersion

994.2 DMMPO Effects of 0 0 0 30

deprivation of

food

9943 DMMPO Effects of thirst 0 0 0 1

994.4 DMMPO Exhaustion due 0 0 0 7

to exposure

994.5 DMMPO Exhaustion due 0 0 0 7

to excessive

exertion

994.6 DMMPO Motion sickness 0 0 0 1 Description ORICULOS GRWardLQS NoO ICULOS NcGRWardLGS

(days) (days) (days) <¾L<

994.8 DMMPO Electrocution 0 0 1 9

and nonfatal

effects of electric

current

995.0 DMMPO Other 0 0 1 9

anaphylactic

shock not

elsewhere

classified

E991.2 DMMPO Injury due to war 1 180 0 180

ops from other

bullets (not

rubber/pellets)

E991.3 DMMPO Injury due to war 1 180 0 180

ops from

antipersonnel

bomb fragment

E991.9 DMMPO injury due to war 1 180 0 180

ops other

unspecified

fragments

E993 DMMPO Injury due to war 1 180 0 180

ops by other

explosion

V01.5 DMMPO Contact with or 0 0 0 14

exposure to

rabies

V79.0 DMMPO Screening for 0 0 0 1

depression

001.9 Extended Cholera 0 0 2 5

unspecified

002.0 Extended Typhoid fever 0 0 0 5

004.9 Extended Shigellosis 0 0 2 5

unspecified

055.9 Extended Measles 0 0 3 180

072.8 Extended Mumps with 0 0 2 7

unspecified

complication

072.9 Extended Mumps without 0 0 0 7

complication

110.9 Extended Dermatophytes 0 0 0 1

, of unspecified

site

128.9 Extended Other and 0 0 0 7

unspecified

Helminthiasis PC Type Description ORiCULOS O WardLOS NaO ICULOS NoORWardLOS

(days) (days)

132.9 Extended Pediculosis and 0 0

Phthirus

infestation

133.0 Extended Scabies

184,9 Extended Malignant 180

neoplasm of

other and

unspecified

female genital

organs

239.0 Extended Neoplasms of

Unspecified

Nature

246.9 Extended Unspecified

Disorder of

Thyroid

250.00 Extended Diabetes Mellitus 0 180

w/o complication

264.0 Extended Vitamin A 0

deficiency

269.8 Extended Other nutritional 0

deficiencies

276,51 Extended Volume

Depletion,

Dehydration

277,89 Extended Other and

unspecified

disorders of

metabolism

280.8 Extended iron deficiency 0

anemias

300.00 Extended Anxiety states 0 5

Extended Unspecified 5

disorders of

nervous system

366.00 Extended Cataract ISO 369.9 Extended Blindness and

low vision

372.30 Extended Conjunctivitis,

unspecified

379.90 Extended Other disorders

of eye

380.9 Extended Unspecified

disorder of

external ear

347 PC Type Description O ICULOS ORWardLOS NoORiCULOS NoORWardLOS

(days) (days) (days) (days)

383.1 Extended Chronic Q 0 0 5

mastoiditis

386.10 Extended Other and 0 0 0 5

unspecified

peripheral

vertigo

386.2 Extended Vertigo of 0 0 0 5

centra! origin

388.8 Extended Other disorders 3 7 1 7

of ear

411.81 Extended Acute coronary 0 0 3 180

occlusion

without

myocardial

infarction

428.40 Extended Heart failure 0 0 3 180

437.9 Extended Cerebrovascular 0 0 3 180

disease..

unspecified

443.89 Extended Other peripheral 0 0 3 180

vascular disease

459.9 Extended Unspecified 0 0 3 180

circulatory

system disorder

477.9 Extended Allergic rhinitis 0 0 0 1

519.8 Extended Other diseases of 3 7 3 7

respiratory

system

521.00 Extended Dental caries 0 0 0 1

522.0 Extended Pulpitis 0 0 0 1

S 5 Extended Other diseases 0 0 0 1

and conditions

of the teeth and

supporting

structures

527,8 Extended Diseases of the 0 7 0 7

salivary glands

569.83 Extended Perforation of 3 7 3 7

intestine

571.40 Extended Chronic hepatitis 0 0 0 180

571.5 Extended Cirrhosis of liver 0 0 3 180

without alcohol

594.9 Extended Calculus of lower 3 3 1 5

urinary tract,

unspecified Description Q fCULOS Q WardLOS NoORiCULOS MoORWardLOS

(days) (days) (days) (days)

599.8 Extended Urinary tract 0 0 0 2

infection, site not

specified

600.90 Extended Hyperplasia of 0 Q 0 5

prostate

608.89 Extended Other disorders 3 7 3 7

of male genital

organs

614.9 Extended Inflammatory 3 7 2 10

disease of female

pelvic

organs/tissues

616.10 Extended Vaginitis and 0 0 0 3

vulvovaginitis

623.5 Extended Leukorr ea not 0 0 0 3

specified as

infective

626.8 Extended Disorders of 3 7 0 7

menstruation

and other

abnormal

bleeding from

female genital

tract

629.9 Extended Other disorders 0 0 0 3

of female genital

organs

650 Extended Normal delivery 0 0 0 3

653.81 Extended Disproportion in 0 0 1 5

pregnancy labor

and delivery

690,8 Extended Erythennatosqua 0 0 0 1

rnous dermatosis

691.8 Extended Atopic dermatitis 0 0 0 1

and related

conditions

692.9 Extended Contact 0 0 0 1

Dermatitis,

unspecified

cause

693.8 Extended Dermatitis due 0 0 0 1

to substances

taken internally

696.1 Extended Other psoriasis 0 0 0 1

and similar

disorders C Type Description OR!CULOS O ardLOS NoO ICULDS NoG WardLQS

(days) (days) (days) (days)

709.9 Extended Other disorders 0 7 0

0! SKiii αΠϋ

subcutaneous

tissue

714.0 Extended Rheumatoid 0 0 0

arthritis

733.90 Extended Disorder of bone 3 10 0

and cartilage.

unspecified

779.9 Extended Other and iii- 0 0 1

defined

conditions

originating in the

perinatal period

780.79 Extended Other rna!aise 0 Q 0

and fatigue

780.96 Extended Generalized pain 0 0 0

786.2 Extended Cough 0 0 0

842.00 Extended Sprain of 0 0 0

unspecified site

of wrist

Table 91 EMRE Common Data: RTD Data

005 DMMPO Food poisoning bacterial 0.0013

005 Amebiasis 0.I50Q

007.9 DMMPO Unspecified protozoal intestinal disease 0.0075

008,45 DMMPO intestinal infection due to Clostridium difficile 0.0500

008.8 DMMPO intestinal infection due to other organism not 0.0075 classified

010 DMMPO Primary tb 1.0000

037 DMMPO Tetanus 1.0000

038.9 Unspecified septicemia 1.0000

042 Human immunodeficiency virus [HIV] disease 1.0000

047.9 DMMPO Viral meningitis 0.0600

052 DMMPO Varicella 1.0000

053 DMMPO Herpes zoster 1.0000

054.1 DMMPO Genital herpes 0.0000 Type Description P(Adm)7.0 DM PO Fifth disease 0.00000 DM PO Yellow fever 1.00C01 DMMPO Dengue 1.00002 DMMPO Mosq. borne encephalitis 1.00003.9 DMMPO Tick borne encephalitis 1,00005 DMMPO Arthropod-borne hemorrhagic fever 1.00006.40 DMMPO West niie fever, unspecified 1.00000.1 DMMPO Viral hepatitis 0.06001 DMMPO Rabies 1.00006 DMMPO Trachoma 0.0009S.0 DMMPO Molluscom contagiosa 0.000Q8.1 DMMPO Viral warts 0.00008.4 DMMPO Hand, foot and mouth disease 0.00009.3 DMMPO Rhinovirus infection in conditions elsewhere and of 0.0050 unspecified site

9.99 DMMPO Unspecified viral infection 0.00152 DMMPO Tick-borne rickettsiosis 1.00004 DMMPO Malaria 1.00005 DMMPO Leishmaniasis, visceral 1,00006 DMMPO Trypanosomiasis 1.00001 DMMPO Eariy primary syphilis 0.00851.9 DMMPO Secondary syphilis, unspec 0.00024 DMMPO Neurosyphilis 0.02008.5 DMMPO Gonococcal arthritis 1.00009.4 DMMPO ongonnococcal urethritis 0.00000 DMMPO Leptospirosis 0.90004 DMMPO Gout 0.00206 DMMPO Disorder of fiuid, electrolyte + acid base balance 0.00006.0 DMMPO Bipolar disorder, single manic episode 0.40008.9 DMMPO Unspecified psychosis 0.40009.0 DMMPO Adjustment disorder with depressed mood 0,06009.81 DMMPO Ptsd 0.40009.9 DMMPO Unspecified adjustment reaction 0.09600.2 DMMPO Post concussion syndrome 0.26255.2 DMMPO Epilepsy petit mal 1,0000

155 PC Type Description P{Adm) D MPO Epilepsy grand mal 1.0000

DMMPO Migraine 0.0035

361 DMMPO Retinal detachment 1.0000

3643 DMMPO Uveitis nos 0.0005

365 Glaucoma 0.5000

370.0 Cornea! uicer 0.0064

379.31 DMMPO Aphakia 0.0800

380.1 DMMPO Infective otitis externa 0.0000

380.4 DMMPO Impacted cerumen 0.0125

381 DMMPO Acute nonsuppurative otitis media 0.0005

381.9 DMMPO Unspecified eustachian tube disorder 0.0005

384.2 DMMPO Perforated tympanic membrane 0.0008

388.3 DMMPO Tinnitus, unspecified 0.0005

389.9 DMMPO Unspecified hearing loss 0.4000

401 Essential hypertension 0.0006

DMMPO Myocardial infarction 1,0000

413.9 DMMPO Other and unspecified angina pectoris 1.0000 427.9 DMMPO Cardiac dysryhthmia unspecified 1.0000 453.4 DMMPO Venous embolism/thrombus of deep vessels lower 1.0000 extremity

462 DMMPO Acute pharyngitis 0.0011 465 DMMPO Acute uri of multiple or unspecified sites 0,0002

DMMPO Acute bronchitis & bronchiolitis 0.0003 DMMPO Peritonsillar abscess 0.3375

Pneumonia, organism unspecified 0,0055

491 DMMPO Chronic bronchitis 0.0080

492 DMMPO Emphysema 0.0800

493.9 DMMPO Asthma 0.0025

523 DMMPO Gingiva! and periodontal disease 0.0000

530.2 DMMPO Uicer of esophagus 0.0006

530.81 DMMPO Gastroesophageal reflux 0.0008

531 DMMPO Gastric ulcer 0,0048

DMMPO Duodenal ulcer 0.0048 DMMPO Acute appendicitis without mention of peritonitis 1.0000

541 DMMPO Appendicitis, unspecified 1.0Q00 PC Type Description P(Adm)

550.9 DM PO Unilateral inguinal hernia 0.2633

553.1 DMMPO Umbilical hernia 0.1688

553.9 DMMPO Hernia nos 0.1800

564.0 DMMPO Constipation 0.00Q0

564.1 DMMPO Irritable bowel disease 0.0028

566 DMMPO Abscess of anal and rectal regions 0.4500

567.9 DMMPO Unspecified peritonitis 0.4500

574 DMMPO Cholelithiasis G.1875

577.0 DMMPO Acute pancreatitis 0.7500

577,1 DMMPO Chronic pancreatitis 0.7500

578.9 DMMPO Hemorrhage of gastrointestinal tract unspecified 0.4050

584.9 DMMPO Acute renal failure unspecified 0.2200

592 DMMPO Calculus of kidney 0.0616

S99.0 DMMPO Unspecified urinary tract infection O.O0Q0

599.7 DMMPO Hematuria 0.0275

608.2 DMMPO Torsion of testes 0.2100

608.4 DMMPO Other inflammatory disorders of male genital organs 0.0788

611.7 DMMPO Breast Sump 0,2100

633 DMMPO Ectopic preg 1.0000

634 DMMPO Spontaneous abortion 1.0000

681 DMMPO Cellulitis and abscess of finger and toe 0.0108

682.0 DMMPO Cellulitis and abscess of face 0.0108

682,6 DMMPO Cellulitis and abscess of leg except foot 0.0108

682,7 DMMPO Cellulitis and abscess of foot except toes 0.0153

682.9 DMMPO Cellulitis and abscess of unspecified parts 0.0153

719.41 DMMPO Pain in joint shoulder 0.0008

719.46 DMMPO Pain In joint tower leg 0.0008

719.47 DMMPO Pain in joint ankle/foot 0.0008

722.1 DMMPO Displacement lumbar intervertebral disc w/o 0,0135 myelopathy

723.0 DMMPO Spina! stenosis in cervical region 0.0135

724.02 DMMPO Spinal stenosis of lumbar region 0.0135

724.2 DMMPO Lumbago 0.0023

724.3 DMMPO Sciatica 0.0135 Type Description P(Adm)

724,4 DM PO Lumbar sprain (ihoracic/!umbosacral) neuritis or 0,0149 radiculitis, unspec

724.S DMMPO Backache unspecified 0,0023 726.10 DMMPO Disorders of bursae and tendons in shoulder 0.0008 unspecified

726.12 DMMPO Bicipital tenosynovitis 0.0008

7263 DMMPO Enthesopathy of elbow region 0.0008

726.4 DMMPO Enthesopathy of wrist and carpus

726.5 DMMPO Enthesopathy of hip region

726.6 DMMPO Enthesopathy of knee 0.0008

726.7 DMMPO Enthesopathy of ankle and tarsus 0,0008

729.0 DMMPO Rheumatism unspecified and fibrositis 0.0008

729.5 DMMPO Pain in limb 0.0008

780.0 DMMPO Alterations of consciousness 0.0113

780.2 DMMPO Syncope 0,0090

780.39 DMMPO Other convulsions 0.0113

780.5 DMMPO Steep disturbances 0.0050

780.6 DMMPO Fever 0.0010

782.1 DMMPO Rash and other nonspecific skin eruptions 0.0050

782.3 DMMPO Edema 0.0375

783.0 DMMPO Anorexia 0.0050

784.0 DMMPO Headache 0.0113

784.7 DMMPO Epistaxis 0.0050

784.8 DMMPO Hemorrhage from throat 0.0113

786.5 DMMPO Chest pain 0.0113

787.0 DMMPO Nausea and vomiting 0.0050

787.91 DMMPO Diarrhea nos 0.0013

789.00 DMMPO Abdominal pain unspecified site 0.0113

800.0 DMMPO Closed fracture of vault of skul! without intracranial 1.0000 injur)'

801.0 DMMPO Closed fracture of base of skull without intracranial 1.0000 injury

801.76 DMMPO Open fracture base of skull with subarachnoid, 1.0000 subdural and extradural hemorrhage with loss of

consciousness of unspecified duration

802.0 DMMPO Closed fracture of nasal bones 1.0000

DMMPO Open fracture of nasal bones 1.0000 PC Type Description P(Adm;

802.6 DMMPO Fracture orbital floor closed (blowout) 1.0000

802.7 DMMPO Fracture orbital floor open (blowout) 1.0000

802.8 DMMPO Closed fracture of other facial bones 1,0000

802.9 DMMPO Open fracture of other facial bones 1.0000

805 DMMPO Closed fracture of cervical vertebra w/o spinal cord 1.0000 injury

806,1 DMMPO Open fracture of cervical vertebra with spinal cord 1.0000 injury

806.2 DMMPO Closed fracture of dorsal vertebra with spinal cord 1.0000 injury

806.3 DMMPO Open fracture of dorsal vertebra with spinal cord 1.0000 injury

806.4 DMMPO Closed fracture of lumbar spine with spina! cord 1.0000

injury

806.5 DMMPO Open fracture of lumbar spine with spina! cord injury 1,0000

806.60 DMMPO Closed fracture sacrum and coccyx w/unspec, spinal 1,0000 cord injury

806.70 DMMPO Open fracture sacrum and coccyx w/unspec. spina! 1,0000 cord injury

807.0 DMMPO Closed fracture of rib(s) 1.0000

807.1 DMMPO Open fracture of rib(s) 1.0000

807.2 DMMPO Closed fracture of sternum 1.0000

8073 DMMPO Open fracture of sternum 1,0000

808.8 DMMPO Fracture of pelvis unspecified, closed 1.0000

808.9 DMMPO Fracture of pelvis unspecified, open 1.0000

810.0 DMMPO Clavicle fracture, closed 1,0000

810.1 DMMPO Clavicle fracture, open 1.0000

810.12 DMMPO Open fracture of shaft of clavicle 1.0000

811.0 DMMPO Fracture of scapula, closed 1.0000

811,1 DMMPO Fracture of scapula, open 1.0000

812.00 DMMPO Fracture of unspecified part of upper end of 1.0000 humerus, closed

813.8 DMMPO Fracture unspecified part of radius and ulna closed 1.0000

813.9 DMMPO Fracture unspecified part of radius and ulna open 1.0000

815.0 DMMPO Closed fracture of metacarpal bones 1.0000

816.0 DMMPO Phalanges fracture, closed 1.0000

816.1 DMMPO Phalanges fracture, open 1,0000

817.0 DMMPO Multiple closed fractures of hand bones 1.0000

817.1 DMMPO Multiple open fracture of hand bones 1.0000 PC Type Description P(Adm)

820.8 D MPO Fracture of femur neck, closed 1,0000

820,9 DMMPO Fracture of femur neck, open 1.0000

821.01 DMMPO Fracture shaft femur, dosed 1.0000

821.11 DMMPO Fracture shaft of femur, open 1.0000

822.0 DMMPO Closed fracture of patella 1.0000

822.1 DMMPO Open fracture of patella 1.000Q

823.82 DMMPO Fracture tib fib, closed 1.0000

823.9 DMMPO Fracture of unspecified part of tibia and fibula open 1.0000

824.8 DMMPO Fracture ank!e, nos, closed 1.0000

824.9 DMMPO Ank!e fracture, open 1.0000

825.0 DMMPO Fracture to calcaneus, closed 1.0000

826.0 DMMPO Closed fracture of one or more phalanges of foot 1.0000

82S.0 DMMPO Fracture of unspecified bone, closed 1.0000

830.0 DMMPO Closed dislocation of jaw 1.0000

830.1 DMMPO Open dislocation of jaw 1.0000

831 DMMPO Dislocation shoulder 0.6750

831.04 DMMPO Closed disiocation of acromioclavicular joint 1.0000

831.1 DMMPO Dislocation of shoulder, open 1.0000

832,0 DMMPO Dislocation elbow, closed 1.0000

832.1 DMMPO Dislocation elbow, open 1.00QO

833 DMMPO Disiocation wrist closed 1.0000

833.1 DMMPO Dislocated wrist, open 1.0000

834.0 DMMPO Dislocation of finger, closed 0.0000

834.1 DMMPO Dislocation of finger, open 1.0000

835 DMMPO Closed dislocation of hip 1,0000

835.1 DMMPO Hip dislocation open 1.0000

835.0 DMMPO Medial meniscus tear 0,0750

836.1 DMMPO Lateral meniscus tear 0.0750

836.2 DMMPO Meniscus tear of knee 0.0750

836.5 DMMPO Disiocation knee, closed 1.0000

836.6 DMMPO Other disiocation of knee open 1.0000

839.01 DMMPO Closed dislocation first cervical vertebra 1.0000

840.4 DMMPO Rotator cuff sprain 0.0375

840.9 DMMPO Sprain shoulder 0.0375 PC Type Description P(Adm)

§43 DMMPO Sprains and strains of hip and thigh 0.0375

§44.9 DM PO Sprain, knee 0.0250

§45 DMMPO Sprain of ankle 0.0125

§46 DMMPO Sprains and strains of socroiliac region 03750

§46.0 DMMPO Sprain of lumbosacral (joint) (ligament) 0.3750

§47.2 DMMPO Sprain lumbar region 0.0375

§47.3 DMMPO Sprain of sacrum 0.0375

§481 DMMPO Jaw sprain 0.0375

§48,3 DMMPO Sprain of ribs 0.0375

§50.9 DMMPO Concussion 0.8000

§51.0 DMMPO Cortex (Cerebral) contusion w/o open intracranial 1.0000 wound

§51.01 DMMPO Cortex (Cerebral) contusion vv/o open wound no loss 1.0000 of consciousness

§52 DMMPO Subarachnoid subdural extradural hemorrhage injury 1.0000

§53 DMMPO Other and unspecified intracranial hemorrhage injury 1.0000 w/o open wound

§53.15 DMMPO Unspecified intracranial hemorrhage with open 1.0000 intracranial wound

§60.0 DMMPO Traumatic pneumothorax w/o open wound into 1.0000 thorax

§60.1 DMMPO Traumatic pneumothorax w/open wound into thorax 1.0000

§60.2 DMMPO Traumatic hemothorax w/o open wound into thorax 1.0000

§60.3 DMMPO Traumatic hemothorax with open wound into thorax 1.0000

§60.4 DMMPO Traumatic pneumohemothorax w/o open wound 1.0000 thorax

§60.5 DMMPO Traumatic pneumohemothorax with open wound 1.0000 thorax

§61.0 DMMPO Injury to heart w/o open wound into thorax 1.0000

§61.10 DMMPO Unspec. injury of heart w/open wound into thorax 1.0000

§61.2 DMMPO Injury to lung, nos, closed 1.0000

§61.3 DMMPO Injury to lung nos, open 1.0000

563.0 DMMPO Stomach injury, w/o open wound into cavity 1.0000

§64.10 DMMPO Unspecified injury to liver with open wound into 1.0000 cavity

§65 DMMPO Injury to spleen 1.0000

366.0 DMMPO Injury kidney w/o open wound 1.0000

566.1 DMMPO Injury to kidney with open wound into cavity 1.0000

S 57 Type Description P(Adm)

867.0^{' "} DMMPO Injury to bladder urethra without open wound into ^" OOOQ cavity

867.1 DM PO Injury to bladder and urethrea with open wound into 1.0000 cavity

867.2 DMMPO Injury to ureter w/o open wound into cavity 1.0000

867.3 DMMPO Injury to ureter with open wound into cavity 1.0000

867.4 DMMPO Injury to uterus w/o open wound into cavity 1.0000

867.5 DMMPO Injury to uterus with open wound into cavity 1.0000

870 DMMPO Open wound of ocular adnexa 0.9405

870.3 DMMPO Penetrating wound of orbit without foreign body 0.9405

870.4 DMMPO Penetrating wound of orbit with foreign body 0.9405

871.5 DMMPO Penetration of eyeball with magnetic foreign body 1.0Q00

872 DMMPO Open wound of ear 0.0250

873.4 DMMPO Open wound of face without mention of 0.3000 complication

873.8 DMMPO Open head wound w/o complication 0.6840

873.9 DMMPO Open head wound with complications 1.0000

874.8 DMMPO Open wound of other and unspecified parts of neck 0.6840 w/o complications

875.0 DMMPO Open wound of chest (wail) without complication 0.3Q00

875.0 DMMPO Open wound of back without complication 0.8000

877.0 DMMPO Open wound of buttock without complication 0.0100

878 DMMPO Open wound of genital organs (external) including 1.0000 traumatic amputation

879.2 DMMPO Open wound of abdominal wall anterior w/o 0.3000 complication

879.6 DMMPO Open wound of other unspecified parts of trunk 0.8000 without complication

879.8 DMMPO Open woundis) (multiple) of unspecified site{s) w/o 0.8000 complication

880 DMMPO Open wound of the shoulder and upper arm. 0.0400

881 DMMPO Open wound elbows, forearm, and wrist 0.0040

882 DMMPO Open wound hand except fingers alone 1.0000

883.0 DMMPO Open wound of fingers without complication 0.8000

884.0 DMMPO Multiple/unspecified open wound upper limb 1.000Q without complication

885 DMMPO Traumatic amputation of thumb (complete) (partial) 0.8000

886 DMMPO Traumatic amputation of other finger(s) (complete) 1.0000 Type Description P(Adm)

887 DMMPO Traumatic amputation of arm and hand (complete) 1.0000

(partial)

890 DMMPO Open wound of hip and thigh 0.7200

891 DMMPO Open wound of knee leg (except thigh) and ankle 0.7200

892.0 DMMPO Open wound foot except toes alone w/o 0.8000 complication

894.0 DMMPO Multiple/unspecified open wound of lower limb w/o

complication

895 D O Traumatic amputation of toe{s) (complete) (partial) 1.0000

896 DMMPO Traumatic amputation of foot (compiete) (partial) 1.0000

897 DMMPO Traumatic amputation of fsg(s) (complete) (partial) 1,0000

903 DMMPO Injury to blood vessels of upper extremity 1.0000

904 DMMPO Injury to blood vessels of tower extremity and 1.0000 unspec. sites

910.0 DMMPO Abrasion/friction burn of face, neck, scalp w/o 0.0000 infection

916.0 DMMPO Abrasion/friction burn of hip, thigh, leg, ankle w/o

infection

916.1 DMMPO Abrasion/friction burn of hip, thigh, leg, ankle with

infection

916.2 DMMPO Blister hip & leg 0.0Q00

9163 DMMPO Blister of hip thigh leg and ankie infected 0.9000

916.4 DMMPO Insect bite nonvenom hip, thigh, !eg, ankie w/o 0.0000 infection

916.5 DMMPO Insect bite nonvenom hip, thigh, leg, ankle, with 0.9000 infection

918.1 DMMPO Superficial injury cornea 0.0000

920 DMMPO Contusion of face scalp and neck except eye(s) 0.0000

921.0 DMMPO Black eye 0.0000

922.1 DMMPO Contusion of chest wall 0.0000

922.2 DMMPO Contusion of abdominal wall 0.0000 922.4 DMMPO Contusion of genital organs 0.0010

924.1 DMMPO Contusion of knee and lower leg 0.0000

924.2 DMMPO Contusion of ankie and foot 0.00QQ 9243 DMMPO Contusion of toe 0.0000

925 DMMPO Crushing injury of face, scalp & neck 1.0000

926 DMMPO Crushing injury of trunk 1.0000

927 DMMPO crushing injury of upper limb 1.0000

928 DMMPO Crushing injury of lower limb PC Type Description P(Adm)

930 DMMPO Foreign Body on External Eye 0,0000

935 DMMPO Foreign body in mouth, esophagus and stomach 1.0000

941 DMMPO Burn of face, head, neck 0.0000

942.0 DMMPO Burn of trunk, unspecified degree 1.0000

943.0 DMMPO Burn of upper limb except wrist and hand unspec. 1.0000 degree

944 DMMPO Bum of wrist and hand 1.0000

945 DMMPO Burn of lower limb(s) 1.0000

950 DMMPO Injury to optic nerve and pathways 1.0000

953.0 DMMPO Injury to cervical nerve root 1,0000

953,4 DMMPO Injury to brachial plexus 1.0000

955.0 DMMPO Injury to axillary nerve 1.Q000

956.0 DMMPO Injury to sciatic nerve 1.0000

959.01 DMMPO Other and unspecified injur)' to head 0.7600

959.09 DMMPO Other and unspecified injury to face and neck 0,7600

959.7 DMMPO Other and unspecified injury to knee leg ankle and 0.7600 foot

989.5 DMMPO Toxic effect of venom 0.0050

989.9 DMMPO Toxic effect unspec subst chiefly 1.0000 nonmedicinai/source

991.3 DMMPO Frostbite 1.0000

991.6 DMMPO Hypothermia 1.0000

992.0 DMMPO Heat stroke and sun stroke 1.0000

992.2 DMMPO Heat cramps 0.0000

992.3 DMMPO Heat exhaustion anhydrotic 0.0000

994.0 DMMPO Effects of lightning 03800

994.1 DMMPO Drowning and nonfatal submersion 1.0000

DMMPO Effects of deprivation of food 1.0000

994.3 DMMPO Effects of thirst 0,0000

994.4 DMMPO Exhaustion due to exposure 0.3800

994.5 DMMPO Exhaustion due to excessive exertion 0.3800

994.6 DMMPO Motion sickness 0.0000

994.8 DMMPO Electrocution and nonfatal effects of electric current 1.0000

995.0 DMMPO Other anaphylactic shock not elsewhere classified 1.0000

E991.2 DMMPO Injury due to war ops from other bullets (not 1.0000 rubber/peliets) Type Description P(Adm)

E991.3 DMMPO Injury due to war ops from antipersonnel bomb 1.0000 fragment

E991.9 DMMPO injury due to war ops other unspecified fragments 1.0000

E393 DMMPO Injury due to war ops by other explosion 1.0000

VOLS DMMPO Contact with or exposure to rabies 1.0000

V79.0 DMMPO Screening for depression 0.0000

001.9 Extended Cholera unspecified 1.0000

002.0 Extended Typhoid fever 1.0000

004.9 Extended Shigellosis unspecified 1.0000

055,9 Extended Measles 1.0000

072.8 Extended Mumps with unspecified complication 1.0000

072.9 Extended Mumps without complication 1.0000

110.9 Extended Dermatophytosis, of unspecified site 0.0000

128.9 Extended Other and unspecified Helminthiasis 0.0013

132,9 Extended Pediculosis and Phthirus infestation 0.0000

133.0 Extended Scabies 0.0000

184.9 Extended Malignant neoplasm of other and unspecified female 1.0000 genital organs

239.0 Extended Neoplasms of Unspecified Nature 0.1400

246,9 Extended Unspecified Disorder of Thyroid 1.0000

250.00 Extended Diabetes Meliitus w/o complication 0.3500

264.0 Extended Vitamin A deficiency 0.0000

269.8 Extended Other nutritional deficiencies 0.0375

276.51 Extended Volume Depletion, Dehydration 0.0000

277.89 Extended Other and unspecified disorders of metabolism 0.0400

280.8 Extended Iron deficiency anemias 1,0000

300,00 Extended Anxiety states 0.1500

349.9 Extended Unspecified disorders of nervous system 1.0000

366.00 Extended Cataract 1.0000

369.9 Extended Blindness and low vision 1.0000

372,30 Extended Conjunctivitis, unspecified 0.00G0

379.90 Extended Other disorders of eye 0.0684

380.9 Extended Unspecified disorder of external ear 0.0038

383.1 Extended Chronic mastoiditis 1.0000

386.10 Extended Other and unspecified peripheral vertigo 0.9000 PC Type Description P(Adm)

386.2 Extended Vertigo of central origin 1,0000

388.3 Extended Other disorders of ear 0.0180

411.81 Extended Acute coronary occlusion without myocardial 1.0000 infarction

428.40 Extended Heart failure 1.0000

437.9 Extended Cerebrovascular disease, unspecified 1.0000

443.89 Extended Other peripheral vascular disease 0.8550

459.9 Extended Unspecified circulatory system disorder 0.8550

477.9 Extended Allergic rhinitis 0,0000

519.8 Extended Other diseases of respiratory system 0.9000

521.00 Extended Dental caries 1.0000

522.0 Extended Pulpitis 1.0000

525.19 Extended Other diseases and conditions of the teeth and 1.0000 supporting structures

527.8 Extended Diseases of the salivary glands 0.3375

569,83 Extended Perforation of intestine 1.0000

571.40 Extended Chronic hepatitis 1.0000

571.5 Extended Cirrhosis of liver without alcohol 1.0000

594,9 Extended Calculus of lower urinary tract, unspecified 1.0000

599.8 Extended Urinary tract infection, site not specified 0.2200

600.90 Extended Hyperplasia of prostate 1.0000

608.89 Extended Other disorders of male genital organs 0.2100

614.9 Extended Inflammatory disease of female pelvic organs/tissues 0.2040

616.10 Extended Vaginitis and vulvovaginitis 0.0000

623.5 Extended Leukorrhea not specified as infective 0.7125

626.8 Extended Disorders of menstruation and other abnormal 0.7125 bleeding from female genital tract

629.9 Extended Other disorders of female genital organs 0.1496

650 Extended Normal delivery 1.0000

653.81 Extended Disproportion in pregnancy labor and delivery 1.0000

690.8 Extended Erythematosquamous dermatosis 0.0090

691.8 Extended Atopic dermatitis and related conditions 0.0015

692.9 Extended Contact Dermatitis, unspecified cause 0.0001

693.8 Extended Dermatitis due to substances taken internally 0.0140

696,1 Extended Other psoriasis and similar disorders 0.4500

709.9 Extended Other disorders of skin and subcutaneous tissue 0.0135 PC Type Description P(Adm)

714.0 Extended Rheumatoid arthritis 1.0000

733.90 Extended Disorder of bone and cartilage, unspecified 0.0900

779,9 Extended Other and ill-defined conditions originating in the 1,0000 perinatal period

780,79 Extended Other malaise and fatigue 0.9310

780.96 Extended Generalized pain 0.7600

786.2 Extended Cough 0.0760

842,00 Extended Sprain of unspecified site of wrist 0,0750

Claims

What is claimed is:

1) A medical modeling system, comprising:

A) at least one processor;

B) at least one database storing common data; and

C) at least one computer readable storage device coupled to the at least one processor, the storage device storing program instructions executable by the at least one processor to implement a plurality of modules to generate estimates of casualty, mortality and medical requirements of a planned medical mission based at least partially on common data stored on the at least one database, the plurality of modules comprising:

i) a patient condition occurrence frequency (PCOF) module that

a) receives information regarding a plurality of missions with

predefined scenario including a PCOF data represented as a plurality sets of baseline PCOF distributions for the plurality of missions;

b) selects a set of baseline PCOF distributions for a future medical mission based on a PCOF scenario defined by a user;

c) determines and presents to the user PCOF adjustment factors applicable to the user defined PCOF scenario;

d) modi fies said selected set of baseline PCOF distributions manually or using one or more PCOF adjustment factors defined by the user to create a set of customized PCOF distributions for the user defined PCOF scenario; and e) provides the set of customized PCOF distributions and the corresponding the user defined PCOF scenario and PCOF adjustment factors for storage and presentation; and

ii) a Casualty Rate Estimation Tool (CREsT) module thai

a) allows the user to select one of six mission types for a planned medical mission, comprising ground combat, fixed base, shipboard, humanitarian assistance (HA), disaster relief (DR) or combined;

b) defines a CREstT scenario for a planned medical mission based on user inputs;

c) generates daily casualty counts for the duration of the planned medical mission of the user defined CREstT scenario; d) assigns a iCD-9 code to each count of casualties of each day of the planned medical mission creating a patient stream with a plurality of casualty counts; and

iii) a Expeditionaiy Medicine Requirements Estimator (EMRE) module that a) establishes a patient stream in EMRE composing a plurality of casualties:

b) determines casualties who need initial surgery from the patient stream of step iii) a) using a EMRE common data;

c) determines if a casualty count from the patient stream of step iii) b) would need follow-up surgery based on recurrence interval, evacuation delay and amount of time of stay for that casualty count using EMRE common data;

d) calculates daily time in surgery for casualties who needs initial or follow-up surgery from step iii) b) and c) for each day of the mission duration;

e) calculates the number of daily required operation table;

f) determines daily evacuation status, and length of stay in both an ICU and an ward for each casualty from the patient stream;

g) calculates the number of required beds both in the ICU and the ward to support the casualties on a given day;

h) calculates the number of evacuations from both the ICU and the ward on any given day:

i) calculates daily number of units of red blood cells, fresh frozen plasma, platelets, and cryoprecipitate required for each day of the mission.

2) The medical modeling system of claim 1, wherein said common data comprises CREstT Common Data, EMRE common data and PCOF common data.

3) The medical modeling system of claim 1, wherein the set of baseline PCOF distributions can be modified at a patient type category level, a iCD-9 category level or a ICD-9 subcategory, whereas the sum of the proportions of all applicable patient type categories, the ICD-9 categories or the ICD-9 subcategories for the user defined scenario is equal to 1, respectively. 4) The medical modeling system of claim 1 , wherein the PCOF adjustment factors comprises: Age, Gender, OB/GYN Correction; Geographic Region, Response Phase, Season or Country.

5) The medical modeling system of claim 4, wherein one or more PCOF adj ustment factors that can be applied to a selected set of baseline PCOF distributions is restricted based on the patient type and the user defined scenario according to table 1,

6) The medical modeling system of claim 4, wherein said PCOF adjustment factors are calculated based at least partially on user inputs.

7) The medical modeling system of claim I, wherein the planned mission is a combat

mission, the CREstT module produces a daily casualty counts by:

A) calculates a wounded in action (WIA) baseline rate for the user defined CREstT scenario;

B) calculates a disease and nonbattle injur}' (DNBI) baseline rate for the user defined CREstT scenario; and

C) generate daily casualty counts for each day of the planned medical mission by: i) applies one or more CREstT adjustment factors defined by the user to the WIA baseline rate and DNBI baseline rate to generate a WIA adjusted rate and a DNBI adjusted rate;

ii) generates a daily WIA casualty counts using the WIA adjusted rate for each day of the planned mission;

iii) generates a daily killed in action (ΚΪΑ) counts for each day of the mission; iv) decrements a daily population at risk (PAR) by subtracting corresponding daily WIA casualty counts and daily KIA counts; v) generates daily DNBI counts including disease casualty counts and NBI casualty counts for each day of the planned mission;

vi) decrements the daily PAR of step iv) by subtracting daily DNBI counts; and

vii) stores daily WIA counts, daily DNBI counts as daily casualty counts,

8} The medical modeling system of claim 7, wherein said WIA baseline rate is directly set by the user or is determined based on a troop type, a battle intensity and a service type defined by user.

9) The medical modeling system of claim 7, wherein said DNBI baseline rate is determined based on the troop type.

10) The medical modeling system of claim 8 or 9, wherein said troop type comprises combat arms, combat support and service support.

1 l) The medical modeling system of claim 8, wherein said battle intensity can he selected from none, peace ops, light, moderate, heavy, or intense.

12) The medical modeling system of claim 8, wherein said service types comprises marine and army.

13) The medical modeling system of claim 7, wherein said CREsiT adjustment factors for WIA baseline rates comprises region, terrain, climate, and troop strength,

14) The medical modeling system of claim 7, wherein said CREsiT adjustment factor for DNBI baseline rate is region,

15) The medical modeling system of claim 7, wherein daily WIA casualty counts are

calculated by A) determines according to table 22 if a Gamma or Exponential Probability distribution should be used for WIA casualty counts generation based on troop type and WIA baseline rate;

B) generates daily casualty rates for the combat arms with an autocorrelation to numbers of casualties sustained in the three immediate preceding days;

C) generates daily casualty rates for combat support and for service support;

D) generates daily casualty counts for combat amis based on based on a poisson distribution; and

E) generates daily casualty counts for combat support and service support based on a poisson distribution.

16) The medical modeling system of claim 1 , wherein the planned mission is disaster relief, the CREstT module produce a daily casualty counts for each day of the mission by:

A) selectes the type of the disease based on user inputs;

B) calculates a total number of direct casualties of the disaster;

C) calculates a daily number of direct casualties who is awaiting treatments starting on the day of arrival of the disaster relief mission using lambda values from CREstT common data for the selected type of disaster;

D) calculates a residual casualties not directly resulted from the disaster; and

E) generates daily casualty counts based on the daily number of direct casualties waiting treatments and daily residual casualties,

17) The medical modeling system of claim 16, wherein said total number of direct casualties of a disaster is calculated by A) calculates an expected number of kills;

B) calculates an expected injur -to-kills ratio, and

C) calculates an expected number of casualties.

18) The medical modeling system of claim 17, wherein the disaster is an earthquake, the CREslT module calculates the total number of the direct casualties based on a magnitude of the earthquake defined by the user, an economy regression coefficient selected from table 33 by the user; a population density regression coefficient selected from table 34 by the user; and a lambda value from table 37.

19) The medical modeling system of claim 17, wherein the disaster is an hurricane, the

CREslT module calculates the total number of the direct casualties based on a category of the hurricane as defined by the user; an economy regression coefficient selected from table 45 by the user; and a population density regression coefficient selected from table 44 by the user; and a the lambda value selected from table 48,

20) The medical modeling system of claim 1, wherein the planned mission is humanitarian assistance, the CREstT module calculates daily casualty counts by

A) calculates parameters of a lognormal distribution based on user inputs from table 52;

B) determines if the planned mission is in transit, whereas if

i) planned mission is in transit, daily casualty counts is zero; and ii) plarmed mission is not in transit, daily casualty counts is generated by a) generates a lognormal random variate; and

b) generates a daily trauma casualty counts using a poisson random variate; c) generates a daily disease casualty counts using a poisson random variate; and

d) calculates daily total casualty counts.

21) The medical modeling system of claim 1, wherein the planned mission is in response to a fixed base weapon strikes, the CREstT module calculates daily casualty counts by

A) determines the area of the base;

B) calculates total casualty area, lethal area, and wound area based on user inputs;

C) splits total area and a PAR into a plurality of sectors;

D) assigns hits (weapon strikes) to selected sectors;

E) calculates WIA and KIA for each weapon strike;

F) calculates daily WIA and ΪΑ counts.

22) The medical modeling system of claim 1 , wherein the planned mission in response to a shipboard attack; the CREstT module calculates daily casualty counts by

A) defines a ship category and a weapon type using user inputs;

B) calculates WIA rate and ΚΪΑ rate based on the ship category and the weapon type by dividing an expected number of casualties by an PAR of the ship;

C) simulates hit of ships;

D) generates casualty counts using exponential distribution for each hit; and

E) calculates total daily casualty counts,

23) The medical mission of claim 1, wherein the planned mission is combined, the CREstT module calculate daily casualty counts by;

A) Defines a plurality of missions based on user inputs; B) calculates dail casualty counts of each of the plurality of mission; and

C) calculates daily casualty counts for the combined mission as the sum of each daily causally counts of the plurality of missions.

24) The medical mission of claim 1, wherein said EMRE moduie establish a patient stream by

A) imports a patient stream from the CREstT module;

B) modifies a patient stream imported from the CREstT module

i) as a percentile of daily casualties of the patient stream imported from the CREstT; or

ii) using mean daily casualties of the patient stream imported from the

CREstT; or

C) generates a patient stream using a casualty rate defined by the user.

25) The medical modeling system of claim 24, the EMRE module determines casualties requiring initial surgery by randomly assign surgery to a casualty count from the patient steam based on a probability of surgery value from EMRE common data for the iCD-9 assigned to the casualty count.

26) The medical modeling system of claim 25, the EMRE module calculates time in surgery by

A) calculates time in surgery for each daily casualty count requiring initial surgery or follow-up surgery by;

i) simulates the amount of time required to complete the surgery assigned to each daily casualty count using EMRE common data; and

Ϊ 72 ii) adds OR set up time to the simulated time required to complete the surgery for each daily casualty count; and

B) calculates total daily time in surgery by summing daily time in surgery for the daily casualties counts.

27) The medical system of claim 26, wherein the EMRE module calculates daily required number of OR tables by dividing total daily time in surgery by number of hours each OR will be operational on that day,

28) The medical system of claim 1, wherein the EMRE module determines daily evacuation status by

A) splits a daily patient stream into casualty counts needing surgery and casualty counts who do not need surgery;

B) calculates a length of stay for ICU and a length of stay for ward for each daily casualty count for casualty count needing surgery;

C) calculates a total length of stay for each casualty count by adding length of stay for ICU and length of stay for ward for that casualty count; and

D) determines evacuation status for each daily casualty count, whereas if

i) total length of stay is greater than evacuation policy from EMRE common data, the daily casualty count is designated for evacuation; or

ii) the daily casualty count is designated for returned to duty (RTD).

29) The medical modeling system of 1, wherein EMRE model calculates daily blood

planning factor by:

A) calculates total daily WIA, NBI, and trauma casualty counts; B) muliipiizes iota! daily WIA, NBI, and trauma casualty counts and blood factors for red blood cells, fresh frozen plasma, platelets, and cryoprecipitate defined by the user.

30) A non-transitory computer-readable storage medium having stored thereon a program that when executed causes a computer to implement a plurality of modules for generate estimates of casualty, mortality and medical requirements of a future medical mission based at least partially on historical data stored on the at least one database, the plurality of modules comprising:

A) at least one processor;

B) at least one database storing common data; and

C) at least one computer readable storage device coupled to the at least one

processor, the storage device storing program instructions executable by the at least one processor to implement a plurality of modules to generate estimates of casualty, mortality and medical requirements of a planned medical mission based at least, partially on common data stored on the at least one database, the plurality of modules compri sing:

i) a patient condition occurrence frequency (PCOF) module that

f) receives information regarding a plurality of missions with

predefined scenario including a PCOF data represented as a plurality sets of baseline PCOF distributions for the plurality of missions;

g) selects a set of baseline PCOF distributions for a future medical mission based on a PCOF scenario defined by a user; h) determines and presents to the user PCOF adjustment factors applicable to the user defined PCOF scenario;

i) modifies said selected set of baseline PCOF distributions manually or using one or more PCOF adjustment factors defined by the user to create a set of customized PCOF distributions for the user defined PCOF scenario; and

j^") provides the set of customized PCOF distributions and the

corresponding the user defined PCOF scenario and PCOF adjustment factors for storage and presentation: and ii) a Casualty Rate Estimation Tool (CREsT) module that

a) allows the user to select one of six mission types for a planned medical mission, comprising ground combat, fixed base, shipboard, humanitarian assistance (HA), disaster relief (DR) or combined;

b) defines a CREstT scenario for a planned medical mission based on user inputs;

c) generates daily casualty counts for the duration of the planned medical mission of the user defined CREstT scenario; d) assigns a 1CD-9 code to each count of casualties of each day of the planned medical mission creating a patient stream with a plurality of casualty counts; and

iii) a Expeditionary Medicine Requirements Estimator (EMRJE) module that ) establishes a patient stream in EMRE composing a plurality of casualties;

) determines casualties who need initial surgery from the patient stream of step iii) a) using a EMRE common data;

) determines if a casualty count from the patient stream of step iii) b) would need follow-up surgery based on recurrence interval, evacuation delay and amount of time of stay for that casualty count using EMRE common data;

d) calculates daily time in surgery for casualties who needs initial or follow-up surgery from step iii) b) and c) for each day of the mission duration;

e) calculates the number of daily required operation table;

detennines daily evacuation status, and length of stay in both an ICU and an ward for each casualty from the patient stream;

) calculates the number of required beds both in the ICU and the ward to support the casualties on a given day;

calculates the number of evacuations from both the ICU and the ward on any given day;

calculates daily number of units of red blood cells, fresh frozen plasma, platelets, and cryopreeipitate required tor each day of the mission. 31) The non-transitory computer-readable storage medium of claim 30, wherein said common data comprises CREstT Common data, EMRE common data and PCOF common data.

32) The non-transitory computer-readable storage medium of claim 30, wherein the set of baseline PCOF distributions can be modified at a patient type category level, a ICD-9 category level or a ICD-9 subcategory, whereas the sum of the proportions of all applicable patient type categories, the ICD-9 categories or the ICD-9 subcategories for the user defined scenario is equal to 1 , respectively.

33) The non- ransitory computer-readable storage medium of claim 30, wherein the PCOF adjustment comprises: Age, Gender, OB/GYN Correction; Geographic Region, Response Phase, Season or Country.

34) The non-transitory computer-readable storage medium of claim 30, one or more PCOF adjustment factor is applied to a selected set of baseline PCOF distributions based on patient type and the user defined scenario according to table 1.

35) The non-transitory computer-readable storage medium of claim 30, wherein said PCOF adjustment factors are calculated at least, partially based on user inputs,

36) The non-transitory computer-readable storage medium of claim 30, wherein the planned mission is combat, the CREstT module produces daily casualty counts by;

A) calculates a wounded in action (WIA) baseline rate for the user defined CREstT scenario;

B) calculates a disease and nonbattle injury (DNBI) baseline rate for the user defined CrestT scenario; and

C) generates daily casualty counts for each day of the planned medical mission by: i) applies one or more CREstT adjustment factors defined by the user to the WIA baseline rate and DNBI baseline rate generating a WIA adjusted rate and a DNBI adjusted rate;

ii) generates a daily WIA casualty counts using WIA adjusted rate for each day of the mission;

iii) generates a daily killed in action (KIA) counts based on WIA casualty counts and user input for each day of the mission;

iv) decrements daily population at risk (PAR) by subtracting corresponding daily WIA casualty counts and daily KIA counts from the daily PAR; v) generates daily DNBI counts including disease patient counts and NBI patient counts for each day of the mission;

vi) decrements the daily PAR by subtracting daily DNBI counts from the daily PAR; and

vii) stores daily WIA counts, daily DNBI counts as daily casualty counts. 37) The non-transitory computer-readable storage medium of claim 36, wherein said WIA baseline rate is directly set by the user or is determined based on troop type, battle intensity and service predefined by user.

38) The non-transitory computer-readable storage medium of claim 36, wherein said DNBI baseline rate is determined based on troop type,

39) The non-transitory computer-readable storage medium of claim 38 or 37, wherein said troop type comprises combat arms, combat and service support,

40) The non-transitory computer-readable storage medium of claim 37, wherein said battle intensity can be set at none, peace ops, light, moderate, heavy, or intense.

3 7S 41) The non-transitory computer-readable storage medium of claim 37. wherein said services is marine or army,

42) The non-transitory computer-readable storage medium of claim 37, wherein said CREstT adjustment factors for WIA baseline rates comprises region, terrain, climate, or troop strength.

43) The non-transitory computer-readable storage medium of claim 36, wherein said CREstT adjustment factor for DNBi baseline rate is region.

44) The non-transitory computer-readable storage medium of claim 36, wherein daily WIA casualty counts are calculated by

A) determines according to table 22 if a Gamma or Exponential Probability

distribution should be used for WIA casualty counts generation based on troop type and baseline WIA distribution;

B) generates daily casualty rates for combat arms with autocorrelation to numbers of casualties sustained in the three immediate preceding days;

C) generates daily casualty rates for combat support and for service support;

D) generates daily casualty counts for combat arms based on poisson distribution; and

E) generates daily casualty counts for combat support and service support based on poisson distribution.

45) The non-transitory computer-readable storage medium of claim 30, wherein the planned mission is disaster relief the CREstT module produce a daily casualty counts for each day of the mission by:

A) selects the type of the disease based on user inputs; B) calculates a total number of direct casualties of the disaster;

C) calculates a daily number of direct casualties who is awaiting treatments starting on the day of arrival of the disaster relief mission using lambda values from CREstT common data for the selected type of disaster;

D) calculates a residual casualties not directly resulted from the disaster; and

E) generates daily casualty counts based on the daily number of direct casualties waiting treatments and daily residual casualties.

46) The non-transitory computer-readable storage medium of claim 45 , wherein said total number of direct casualties of a disaster is calculated by

A) calculates the expected number of kills:

B) calculates the expected injury-to-kills ratio, and

C) calculates the expected number of casualties.

47) The non-transitory computer-readable storage medium of claim 46, wherein the disasier is an earthquake, the CREstT module calculates the total number of the direct casualties based on a magnitude of the earthquake defined by the user, an economy regression coefficient selected from table 33 by the user; a population density regression coefficient selected from table 34 by the user; and a lambda value from table 37.

48) The non-transitory computer-readable storage medium of claim 46, disaster is an

hurricane, wherein the disaster is an hurricane, the CREstT module calculates the total number of the direct casualties based on a category of the hurricane as defined by the user; an economy regression coefficient selected from table 45 by the user; and a population density regression coefficient selected from table 44 by the user: and a the lambda value selected from table 48. 49) The non-transitory computer-readable storage medium of claim 30, wherein the planned mission is humanitarian assistance, the CREstT module calculates daily casualty counts by

A) calculates parameters of a lognormal distribution based on user inputs from table

B) determines if the planned mission is in transit, whereas if

i. planned mission is in transit, daily casualty counts is zero; and ii. planned mission is not in transit, daily casualty counts is generated by

1 , generates a lognormal random variate; and

2, generates a daily trauma casualty counts using a poisson random variate for trauma;

3, generates a daily disease casualty counts using a poisson random variate for disease: and

4, calculates daily total casualty counts,

50) The non-transitor}' computer-readable storage medium of claim 30, wherein the planned mission is in response to a fixed base weapon strikes; the CREstT module calculates daily casualty counts by

A) determines the area of the base;

B) calculates total casualty area, lethal area, and wound area based on user inputs;

C) splits total area and PAR into a plurality of sectors;

D) assigns hits (weapon strikes) to selected sectors;

E) calculate WIA and KIA for each weapon strike; F) calculates daily WIA and KIA counts.

51) The non-transitory computer-readable storage medium of claim 30, wherein the planned mission in response to a shipboard attack; the CREstT module calculates daily casualty counts by

A) calculates WIA rate and KIA rate for based on the ship category and the weapon type by dividing the expected number of casualties by the PAR of the ship;

B) simulates hit of ships;

C) generates casualty counts for using exponential distribution each hit; and

D) calculates total daily casualty counts.

52) The non-transitory computer-readable storage medium of claim 30, wherein the planned mission is a combined mission, the CREstT module calculate daily casualty counts by;

A) Defines a plurality of missions based on user inputs;

B) calculates daily casualty counts of each of the plurality of mission; and

C) calculates daily casualty counts for the combined mission as the sum of each daily casualty counts of the plurality of missions,

53) The non-transitory computer-readable storage medium of claim 30, wherein said EMRE module establish a patient stream by

A) imports a patient stream from a CREstT module;

B) modifies a patient stream imported from the CREstT module

i. as a percentile of daily casualties of the patient stream imported from the CREstT; or

ii. by using mean daily casualties of the patient stream imported from the CREstT; or

382 C) generates a patient stream using a rate defined by the user,

54) The non-transitory computer-readable storage medium of claim 53, the EMRE module determines casualties requiring Initial surgery by randomly assign surgery to a casualty count based on probability of surgery value from EMRE common data for each ICD-9 code assigned to the casualty count,

55) The non-transitory computer-readable storage medium of claim 54, the EMRE module calculates time in surgery by

A) calculates time in surgery for each daily casualty count requiring initial surgery or follow-up surgery by;

i. simulates the amount of time required to complete surgery assigned to each daily casualty count using EMRE common data; and ii. adds OR set up time to the simulated time required to complete the

surgery for each daily casualty count; and

B) calculates total daily time in surgery by summing daily time in surgery for each daily casualty counts,

56) The non-transitory computer-readable storage medium of claim 55, wherein the EMRE module calculates daily required number of OR tables by dividing total daily time in surgery by number of hours each OR will be operational on that day.

57) The non-transitory computer-readable storage medium of claim 30, wherein the EMRE module determines daily evacuation status by

A) splits daily casualty counts into casualty counts needing surgery and casualty counts who do not need surgery; B) calculates length of stay for ICU and length of stay for ward for each daily casualty count needing surgery;

C) calculates total length of stay for each casualty count by adding length of stay for ICU arid length of stay for ward for that casualty count; and

D) determines evacuation status for each daily casualty count, if

i. total length of stay is greater than evacuation policy from EMRE common data, the daily casualty count is designated for evacuation; or

ii the daily casualty count is designated for returned to duty (RTD).

58) The non-transitory computer-readable storage medium of claim 30, wherein EMRE

model calculates daily blood planning factor by:

A) calculates total daily WIA, NBI, and trauma casualty counts:

B) multiplies total daily WIA, NBI, and trauma casualty counts and blood factors for red blood cells, fresh frozen plasma, platelets, and cryoprecipitate defined by the user.

59) A method for assessing medical risks of a planned mission comprising;

A) establishes a PCOF scenario for a planned mission;

B) stimulates the planned mission to create a set of mission-centric PCOF

distributions;

C) stores and presents the mission-centric PCOF distributions,

D) Ranks patient conditions based on their mission-centric PCOF distribution,

60) A method for assessing adequacy of a medical support plan for a mission, comprising

A) establish a mission scenario for a planned mission in MPTk; B) stimulate the planned mission to:

i. create a set of mission-centric PCOF;

ii. generate estimated estimate casualties for the planned mission; and iii. calculate estimated medical requirements for the planned mission; and

C) Assess the adequacy of the medical support plan using mission-centric PCOF distributions, estimated casualties and calculated estimated medical requirements.

61) A method of estimating medical requirement of a planned mission,

A) establish a scenario for a planned mission in MPTk;

B) stimulate the planned mission to generate estimated medical requirements;

C) stores and presents the estimate medical requirements for the planned mission.

62) The method of claim 61 , wherein the medical requirements comprising:

A) the number of hours of operating room time needed;

B) the number of operating room tables needed;

C) the number of intensive care unit beds needed;

D) the number of ward beds needed;

E) the total number of ward and ICU beds needed;

F) the number of staging beds needed;

G) the number of patients evacuated after being treated in the ward;

H) the total number of patients evacuated from the ward and ICU;

I) the number of red blood cell units needed;

J) the number of fresh frozen plasma units needed;

K) the number of platelet concentrate units needed; and

L) the number of Cryoprecipitate units needed.