Modeling and Simulation of Healthcare 

Systems for Homeland Security 

Applications

Charles McLean

Y. Tina Lee

Dr. Sanjay Jain

Dr. Charles Hutchings

NISTIR 7784
NISTIR 7784

Modeling and Simulation of 

Healthcare Systems for Homeland 

Security Applications

Charles McLean

Y. Tina Lee

Manufacturing Systems Integration Division

Engineering Laboratory

Dr. Sanjay Jain

George Washington University

Dr. Charles Hutchings

U.S. Department of Homeland Security

September 2011

U.S. Department of Commerce

Rebecca M. Blank, Acting Secretary

National Institute of Standards and Technology

Patrick D. Gallagher, Under Secretary for Standards and Technology and Director
ii

ACKNOWLEDGMENTS

The U.S. Department of Homeland Security Science and Technology Directorate sponsored the 

production of this material under Interagency Agreements HSHQDC-09-X-00009 and HSHQDC-09-X00357 with the National Institute of Standards and Technology (NIST). The work described was funded 

by the United States Government and is not subject to copyright.

DISCLAIMERS

The findings expressed or implied in this report do not necessarily reflect the official view or policy of the 

U.S. Department of Homeland Security, U.S. Department of Commerce, or the United States 

Government.

Some software products may have been identified in context in this report. This does not imply a 

recommendation or endorsement of the software products by the authors or NIST, nor does it imply that 

such software products are necessarily the best available for the purpose. 

Comments or questions about this report may be e-mailed to: simresponse@cme.nist.gov.
Contents

1. Document Purpose.................................................................................................................................1

2. Introduction to Healthcare Systems and Associated DHS Guidance ....................................................2

3. Perspectives on Methodologies, Models, and Simulations....................................................................5

4. Needs Analysis Overview....................................................................................................................11

5. Requirements Specifications ...............................................................................................................13

5.1. Intended Use.................................................................................................................................13

5.2. Functional Requirements..............................................................................................................13

5.3. Data Requirements.......................................................................................................................13

5.4. User Interface Requirements........................................................................................................14

5.5. Performance Requirements ..........................................................................................................14

5.6. Credibility and Evaluation Requirements.....................................................................................14

6. Identification of M&S Resources........................................................................................................15

6.1. Projects, Facilities, and Capabilities.............................................................................................15

6.2. Simulations, Models and Tools....................................................................................................16

6.3. Relevant Standards and Guidelines..............................................................................................19

6.3.1. Domain Specific Standards...................................................................................................20

6.3.2. Classification: Operational guidelines ..................................................................................25

6.3.3. Conceptual Modeling Standards...........................................................................................30

6.3.4. Distributed Simulation Standards..........................................................................................31

6.3.5. Selected Geographic Information System (GIS) Standards..................................................32

6.3.6. Selected Communication Standards......................................................................................37

6.4. Data Sources.................................................................................................................................38

7. Discussions and Recommendations.....................................................................................................47

7.1. Best Practices ............................................................................................................................... 47

7.2. Uncertainties, Cautions and Warnings.........................................................................................48

7.3. Research, Development, Standards, and Implementation Issues .................................................49

8. Conclusion...........................................................................................................................................49

9. References ...........................................................................................................................................49
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1

1. Document Purpose

Healthcare System models and simulations may be used to support analysis, planning, and training needs 

for the healthcare institutions, epidemics, and other healthcare-related emergencies. Simulation models 

may be used to understand healthcare systems, interdependencies with other systems, their vulnerabilities, 

and the impact of emergency incidents on the population and healthcare community. These models and 

simulations will also be used to support training exercises, performance measurement, conceptual design, 

impact evaluation, response planning, analysis, acquisition, conceptualizing and evaluating new systems, 

vulnerability analysis, economic impact, and determining interdependencies between healthcare and other 

infrastructure systems. The goal of this document is to capture the current knowledge and information 

resources that can serve as a common baseline for researchers and developers of models and simulations 

of healthcare systems for homeland security applications. This initial version of the document attempts to 

assemble relevant, publicly available information from a number of sources within U.S. Department of 

Homeland Security (DHS) and the modeling and simulation (M&S) communities. 

This document is intended to help initiate the discussion of the current leading research, development, 

standards, and implementation issues within the Healthcare System M&S community, as it relates to 

homeland security. The document will be updated based on the input of domain experts across 

government, research, and commercial organizations. These experts will be invited to join together in a 

workshop to review and extend this document for its final publication. The workshop will focus on 

simulation and modeling activities and needs that support analysis, planning, and training for the 

healthcare systems as well as the integration of M&S applications with each other and other data systems. 

Issues to be addressed within the scope of this workshop include the establishment of consensus on: 

• identification of subject matter experts 

• definition of customer and user needs

• system requirements specifications

• recommended/approved modeling techniques and approaches

• identification of data sources, reference data sets, formats, and standards

• identification of appropriate model evaluation and accreditation practices

The workshop will also help identify the current leading research, development, standards, and 

implementation issues. Such analysis by the workshop participants may be found to be relevant by future 

efforts for developing standards, conducting research and development, and enhancing implementation 

policies and procedures for homeland security applications of M&S to improve the protection of critical 

infrastructure systems. A preliminary workshop that addressed modeling and simulation of healthcare 

systems was held in 2008, see [NIST 2010b] for further information.

This document provides a compendium of information that has been assembled that is relevant to the 

M&S of healthcare systems. Healthcare systems, as pertains to homeland security, are introduced in 

Section 2. Section 3 provides a general background on methodologies, models, and simulations. An initial 

set of high level user and customer needs for M&S applications in the healthcare system domain is 

presented in Section 4. Section 5 translates the high level needs to a representative set of M&S system 

requirements (a more detailed specification is currently under development in a related effort). The 

existing healthcare systems M&S resources and capabilities such as projects, tools, standards, and data 

sets that have been developed over the years to meet the needs and requirements are identified in Section 

6. Section 7 presents a discussion of issues, concerns, and recommendations for advancing M&S for 

healthcare systems emanating from a comparison of current resources and capabilities with the needs and 

requirements. Section 8 concludes the document while section 9 provides list of references used.
2

Three additional documents have been prepared as a part of this effort. The other documents address 

M&S for critical infrastructure and key resources (CIKR), incident management, and releases of 

hazardous materials. To minimize redundancy between the documents, each document focuses on the 

M&S techniques that are most significant to the sectors mission and objectives. The CIKR document 

emphasizes modeling and simulation supporting analysis of systems (e.g., vulnerability, security), 

whereas the incident management document focuses more on training and exercises. The healthcare 

systems document addresses M&S for analysis, training, and exercises, but at a more detailed level than 

the previous two documents. The hazardous material releases document focuses on the more physical 

aspects of M&S associated with explosions, fires, plumes, and the flow of hazardous materials in building 

ventilation systems, bodies of water, and the soil. The authors recognize that each of the domains may 

employ all of the M&S techniques that have been identified in the other documents, but typically to a 

lesser extent.

The authors welcome identification of omissions as well as suggestions for improvements. Please contact 

the authors directly or submit comments or questions by e-mail to simresponse@cme.nist.gov.

2. Introduction to Healthcare Systems and Associated DHS Guidance

The Healthcare and Public Health sector consists of state and local health departments, hospitals, health 

clinics, mental health facilities, nursing homes, blood-supply facilities, laboratories, mortuaries, and 

pharmaceutical stockpiles. The Responsible Agency for the healthcare sector, as designated in the 

relevant DHS documents, is the Department of Health and Human Services. Organizations that may be 

involved in addressing sector issues and as well the development of models and simulations include: 

Center for Disease Control, Food and Drug Administration, Department of Homeland Security (border 

control for foreign viruses, agricultural pests, etc.), Social Security Administration, the U.S. Public Health 

Service, state and local agencies, academic institutions, and research hospitals.

The healthcare systems domain includes modeling of incident victims and existing patients affected by 

incidents; medical symptoms, physiological processes, and behaviors that patients may experience as the 

result of a natural disaster, terrorist attack, or epidemic; disease management operations and procedures; 

the impact of disasters, etc. on the environment as well as the food supply (pollution, contamination, etc.). 

Issues that may be addressed by simulation applications include: analysis of policies, evaluation of 

options and predictions concerning the state of public health, spread of communicable diseases, policies 

for intervention, triage and priority scoring for surgeries or other treatments, vaccination programs, costeffectiveness analysis, medical emergency response, fatalities management, overall readiness of the 

healthcare system, hospitals and other related facilities/organizations, surge capacity, operational 

practices, logistic support systems, and elements of the pharmaceutical/equipment manufacturing sectors 

serving healthcare system needs.

Healthcare system models may be comprised of: representations of medical personnel and hospitals; 

constrained medical resources and work calendars; hospital facilities (operation theatres, intensive care 

units, beds); medical equipment, single use devices, and consumables; administrative documents and 

processes; medical procedures; the routing, status, and location of ambulances as well as other Emergency 

Medical Technician (EMT) resources and processes; the location, cost, status, quality, effectiveness, and 

dispensation of pharmaceuticals; and the logistics of industry practices and processes (climate controlled 

containers, other special needs). Models and simulations may be implemented as computer software, 

simulation-based training facilities (emergency and critical-care, medical/surgical patient care, maternity 

and pediatric rooms), and specialty devices (mannequins for various applications such as trauma, surgery 

and emergency care, disease diagnosis and treatment). 
3

DHS addresses healthcare systems in two contexts: a) as a function included in the response to 

emergencies in the context of incident management, and b) as a critical infrastructure sector that should 

be protected against efforts to affect its operation.

The National Incident Management System (NIMS) [DHS 2008a] and National Response Framework 

(NRF) [DHS 2008b] provide the relevant guidance for the incident management domain. Homeland 

Security Presidential Directive-5 (HSPD-5) [DHS 2003], called upon the Secretary of Homeland Security 

to develop a national incident management system (NIMS). The NIMS provides a systematic approach to 

guide all involved organizations through the entire life-cycle of preventing, protecting against, responding 

to, recovering from, and mitigating the effects of incidents while the NRF focuses on preparing for and 

providing a unified national response to incidents. NIMS, together with NRF and other documents, 

provides the structure needed to coordinate, integrate, and synchronize activities derived from various 

relevant statutes, national strategies, and Presidential directives to create a unified national approach to 

implementing the incident management mission (see Figure 1). 

Figure 1: National Framework for Homeland Security (from [DHS 2009])

NIMS identifies that an incident may have a mix of implications including political, social, economic, 

environmental, public safety, public health, and financial, and hence require a coordinated response. For 

the healthcare systems perspective, the response includes collection of data on public health and 

environmental modeling using standard techniques. The public health information should be maintained 
4

securely given the sensitive nature of data. The information may be collected for investigations and 

analysis to determine the cause, projecting the spread, and selecting countermeasures for public health 

events and disease outbreaks. Typically M&S application will be used for projections based on the 

collected information and for evaluating response strategies. Release of information on public health 

should be carefully managed by a public information officer.

NIMS defines the health and medical resource typing for resource management for incidents. The 

command staff may include a medical advisor for issues of medical and mental health services, mass 

casualty, acute care, vector control, epidemiology, or mass prophylaxis considerations, particularly in 

response to a bioterrorism incident. The command staff may also include public health specialists or 

radiation health specialist depending on the circumstances. Protocols should be developed for 

credentialing of volunteer management agencies such as the Red Cross, Medical Reserve Corps, etc. and 

by organizations such as hospitals. NIMS calls for setting up Area Command for public health 

emergencies since the impact may not be immediately identifiable, may be geographically dispersed and 

evolve over long periods of time.

In addition to concerns for the incident victims, the healthcare systems need to be concerned with the 

health of emergency responders. NIMS defines the need for addressing occupational health and mental 

issues for emergency responders including monitoring of immediate and long term effects of the 

incidents. The command staff should include a safety officer and/or an occupational safety and health 

specialist for monitoring and advising on the health and safety of incident personnel. The logistics 

section should include a medical unit for providing medical services to incident personnel.

The NRF [DHS 2008b] acknowledges that the responsibility for public health and welfare lies with the 

governments of the states, territories and tribal areas, and that they can request federal assistance if they 

anticipate their resources will be exceeded. Several federal departments do have the authority to declare 

disasters or emergencies. The Secretary of Health and Human Services (HHS) can declare a public health 

emergency. In a coordinated response, the states, territories and tribal governments should activate 

special response teams with a public health specialist should the incident warrant such action. The 

response is followed by short term recovery that includes providing essential public health and safety 

services. Restoration of healthcare services would usually include coordinating with private sector 

owner/operators. The NRF emergency support annexes provide primary operation level mechanism to 

provide assistance in functional areas including public health and medical services. 

The NRF Emergency Support Function (ESF)#8-Public Health and Medical Services specifically 

describes the federal coordinated response in case of a public health disaster or potential for one. It 

identifies HHS as the primary coordinator. The response addresses medical needs and other functional 

needs of people in the need of medical care. The ESF briefly describes the concept of operations and the 

organization for the ESF#8 response. It defines initial actions such as, assessment of public health/ 

medical needs, health surveillance, providing medical care personnel, equipment, and supplies, patient 

evacuation and care, and mass fatality management. National Oceanic and Atmospheric Administration 

(NOAA) and Interagency Modeling and Atmospheric Assessment Center (IMAAC) may be called on for 

support in case of hazardous material releases being the cause of the emergency. ESF#6- Mass Care, 

Emergency Assistance, Housing, and Human Services also calls for a large role for healthcare systems 

including emergency first aid and physical and mental health services for those in mass care. A number 

of other ESFs call for support roles dealing with public health. 

The NRF also includes incident annexes that describe the specialized application of the response 

framework to specific situations. The incident annexes include those for biological, nuclear/ radiological, 

catastrophic, food and agriculture, and mass evacuation incidents. The focus of biological incident annex 

is on responding to human disease outbreaks of known and unknown origins with the HHS as the primary 
5

agency coordinating the response. The actions identified in the incident annex include HHS working with 

partner organizations to evaluate the incident. While the annex doesn’t specifically mention it, M&S can 

be used to predict the spread of the disease over time to help determine the areas and population at risk. 

All the other incident annexes include utilization of healthcare systems for caring for incident victims.

Related to the incident management context, the Homeland Security Presidential Directive-8 (HSPD-8) 

calls on DHS to develop mechanisms for improved delivery of Federal preparedness assistance to State, 

tribal and local governments [DHS 2008a]. Annex I to HSPD-8 provides guidance for planning and for 

the development of an integrated planning system. Fifteen national planning scenarios have been 

developed that may be used to help focus efforts to prepare for natural disasters, terrorist attacks, and 

other serious incidents. The national planning scenarios are Improvised Nuclear Device; Aerosol 

Anthrax; Pandemic Influenza; Plague; Blister Agent; Toxic Industrial Chemicals; Nerve Agent; Chlorine 

Tank Explosion; Major Earthquake; Major Hurricane; Radiological Dispersal Device; Improvised 

Explosive Device; Food Contamination; Foreign Animal Disease; and Cyber Attack. With the exception 

of cyber attack scenario, the rest of the scenarios will require the participation of the healthcare sector for 

preparedness, response and recovery. Also, a few of the scenarios, such as pandemic influenza and 

plague, require responses primarily involving healthcare systems. M&S tools and applications should, 

wherever possible, support the modeling of healthcare systems in the fifteen national planning scenarios 

defined by DHS. 

DHS has developed specific plans for all the critical infrastructure and key resources sectors. The sector 

specific plan for Healthcare and Public Health (HPH) identifies HHS as the sector specific agency [DHS 

2011]. HPH sector is responsible for 15 percent of the gross national product. About 85% of the sector’s 

assets are privately owned and operated. The public health component of the sector is managed across all 

levels of government from local to national. The HPH sector’s vision has been stated as to achieve 

overall resiliency against all man-made and natural threats. HHS supported establishment of two 

councils, a Health Sector Coordinating Council for private sector component, and a Government 

Coordinating Council for the government sector. The councils have established collaborative workgroups 

on different topics such as, research and development needs and capability gaps for the sector, and 

measures and metrics for progress towards infrastructure protection goals. The HPH sector R&D goals 

include strengthening of surge capacity modeling tools [HHS 2007], a goal that would strongly rely on 

M&S techniques.

3. Perspectives on Methodologies, Models, and Simulations

Concise Oxford Dictionary of Current English, 1996, defines Methodology as “a body of methods used in 

a particular activity.” Methodology is principles of method, and such principles can be used to study and 

inform problem solving and decision-making. [Checkland 2000] describes a useful model linking 

methodology and the user of a methodology to problem solving: 

‘A problem-solving situation with three elements:

• A user of methodology (this assumes that the user is familiar with the methodology)

• Methodology as documented

• Situation as perceived by the user

Relationship and interactions between the three elements are encapsulated in the LUMAS model 

(Learning, User of methodology, Methodology formally described, Actual approach adopted, and 

real world problem Situation) shown in figure 2. A simple example narrative for the diagram 

may be: A user, U, appreciating a methodology, M, as a coherent set of principles and 

perceiving a problem situation, S, asks, “what can I do?” The User then tailors from M a specific 
6

approach, A, judged to be appropriate for S, and uses it in an attempt to improve the situation. 

This generates learning, L, which may change the user, U or the methodology, M.

A methodology is, then, a logical framework that not only brings forth learning for an individual, 

but does so in a consistent and systemic manner so learnings can be shared and passed on.’

Yields

Perceives,

Has a concern for

Tailors “M” to “S” yielding

Used to Guide Inquiry 

and Action in

Modifies, Enriches 

Appreciation of

Changes

Appreciates

Actual Approach 

Adopted

(Situation or User 

Specific)

A

Real World Problem 

Situation

S User of Methodology

U

New Problem Situation

“Improved”

Methodology 

Formally 

Described

M

Learning

L

Yields

Becomes 

Becomes 

Figure 2: The LUMAS Model (from [Checkland 2000])

Another perspective on methodology comes from the International Council on Systems Engineering 

(INCOSE) where methodology is defined as “a collection of related processes, methods and tools” 

[INCOSE 2008]. This is based on definitions from [Martin 1996]:

‘Methodology can be differentiated from other related concepts using the following definitions 

from [Martin 1996]:

• A Process (P) is a logical sequence of tasks performed to achieve a particular objective. A 

process defines “WHAT” is to be done, without specifying “HOW” each task is performed. 

The structure of a process provides several levels of aggregation to allow analysis and 

definition to be done at various levels of detail to support different decision-making needs.

• A Method (M) consists of techniques for performing a task, in other words, it defines the 

“HOW” of each task. (In this context, the words: “method,” “technique,” “practice,” and 

“procedure” are often used interchangeably.) At any level, process tasks are performed 

using methods. However, each method is also a process itself, with a sequence of tasks to be 

performed for that particular method. In other words, the “HOW” at one level of abstraction 

becomes the “WHAT” at the next lower level.

• A Tool (T) is an instrument that, when applied to a particular method, can enhance the 

efficiency of the task; provided it is applied properly and by somebody with proper skills and 

training. The purpose of a tool should be to facilitate the accomplishment of the “HOWs.” In 

a broader sense, a tool enhances the “WHAT” and the “HOW.” Most tools used to support 
7

systems engineering are computer- or software-based, and are also known as Computer 

Aided Engineering (CAE) tools.

Closely associated with methodology is an Environment (E) that consists of the surroundings, the 

external objects, conditions, or factors that influence the actions of an object, individual person 

or group [Martin 1996]. These conditions can be social, cultural, personal, physical, 

organizational, or functional. The purpose of a project environment should be to integrate and 

support the use of the tools and methods used on that project. An environment thus enables (or 

disables) the “WHAT” and the “HOW”.’

The interrelationship of processes, methods, tools, and environments is graphically represented in Figure 

3.

Figure 3: The Process, Methods, Tools, Environments Elements, and Effects of Technology and 

People (from [INCOSE 2008])

“Model” and “simulation” can be defined or classified in many ways. For example, the DHS Lexicon 

[DHS 2010] includes the following definitions: 

• Model: approximation, representation, or idealization of selected aspects of the structure, behavior, 

operation, or other characteristics of a real-world process, concept, or system. 

• Simulation: model that behaves or operates like a given process, concept, or system when provided a 

set of controlled inputs. 

In addition, Department of Defense glossary [DoD 2010] provides the following definition.

• Modeling & Simulation: Modeling and Simulation (M&S): The discipline that comprises the 

development and/or use of models and simulations. M&S is highly dependent upon Information

Technology as defined in DoD Directive 4630.05, Interoperability and Supportability of Information 

Technology (IT) and National Security Systems (NSS), May 5, 2004. 

a. The use of models, including emulators, prototypes, simulators, and stimulators, either statically or 

over time, to develop data as a basis for making managerial or technical decisions. The terms 

"modeling" and "simulation" are often used interchangeably, but simulations generally execute 

models over time, space, events, or other processes.
8

The focus of this document is on computer models and simulations – computer implemented physical, 

mathematical, process, phenomenological or other types of models. One perspective on the way in 

which computer models and simulations support methodology is modeled in Figure 4 (M in the LUMAS 

Model). 

Modeling

Behavioral 

Structural

Mathematical 

Modeling

Data 

Modeling

Computer Modeling

and Simulation 

Conceptual (language, images)

State Charts

Human-in-the-Loop (HITL) 

Hardware-in-the-Loop (HWIL)

Finite Element Model (FEM)

Finite Volume Model (FVM)

System Environment Models

Parametric/Empirical Models

Uncertainty Models

Differential Equation Specified Systems (DESS)

Stochastic Models

Logic Models

Linear Programs

Discrete Event System Specification

Discrete Time System Specification

Agent-Based Models

Cellular Automata

Neural Networks

Object-Oriented Models

Mock-up/Prototype

Scale Models; e.g., ships, airplanes

Maps

General 

Knowledge

(Epistemology)

METHODOLOGY

M

Examples of 

Methodologies:

• Policy Analysis

• Operations 

Research

• Systems 

Engineering

• Experimentation

• Statistics

• Test and 

Evaluation

• Computer 

Modeling 

 and 

 Simulation

Figure 4: Modeling in methodology

Models can broadly be divided into structural and behavior representations of systems, which could 

include mathematical or empirical modeling. Each of these types of models can be implemented using 

computer models for simulation and used to study questions of interest about a particular system. Various 

examples of model types are shown. This list of model types is not complete or exhaustive, but is meant 

to show typical applications of M&S that support methodologies such as operations research, systems 

engineering, experimentation, or other types of analysis.

Although M&S capabilities are tools in many different methodologies, M&S using computers is itself a 

methodology with supporting processes, methods and tools. Figure 5 illustrates a simplified, generic 

process for development of computational M&S capabilities to address a non-trivial engineering or 

scientific problem from the perspective of an M&S developer. The process shown in Figure 5 also maps 

to the LUMAS model as shown in the figure. This process is also applicable to simpler problems where 

trivial steps may be combined. Also, the M&S developer may be the problem solver and consumer of the 

M&S results such as an engineer addressing a systems design question or a program manager doing a 

“what if’ analysis to assess the risk to a program.

The first step in the process includes the model or code developer (U) developing a clear understanding of 

what problem situation (S) the consumer of the M&S results is trying to address. A conceptual model of 

the system or problem serves as a framework in developing and implementing the appropriate computer 
9

modeling capability (A) using the M&S methodology (M) to address the question at hand. With a clear 

conceptual model in mind, developers have a number of choices to make in generating results:

Grounds

Uses

Includes

Informs

Computer Model/

Simulation A

Problem at Hand / 

System S

Model Developer

U

M&S Results

M&S 

Methodology

M

Consumer of Results

Observations and 

Data Conceptual Model

Evaluation Process

(VV&A)

L

Uses

Supports

Supports

Creates 

Produces

Enhances

Address Checks

Data from 

Existing 

Systems

Interprets

Grounds

Creates

Evaluates

Specify Intended

Use to Address

Inform 

Accredit 

Grounds 

Guides Development and Use of

Needs

Figure 5: Computer Modeling and Simulation – Developer’s Perspective

• What data, knowledge, theories, or models are available or applicable to address the problem at hand?

• Is the data, knowledge, or understanding sufficient in both quality and quantity to address the problem 

at hand, or will additional data or observations be required to support development?

• What is the risk of using erroneous results, e.g., will these results be the only input to a decision, or 

will other sources of information be available to support decision making?

• How can the conceptual model be expressed mathematically or physically?

• What boundary and initial condition should be used?

• What modeling paradigm or approach would be most appropriate to implement the analysis?

• Given the developers’ experience, what particular codes or capabilities would be most suitable for 

implementing the model, considering software, hardware, and other constraints and limitations?

• Given the code or computer capability has been developed, have any mistakes or errors been made in 

completing this or in entering the data?

• Given there are no mistakes or errors found in developing the capability or entering the data, are the 

results realistic, and do they make sense?

• What approach should be used to ensure that the results are correct?

• How do uncertainties and approximations affect the computational results?

• Given that everything else is correct, are the results suitable to address the problem at hand?

• How should the results and associated uncertainty be present for use in decision making?
10

M&S capabilities are used to model only selected aspects of a system and the models are implemented in 

a computing environment; therefore, the models need to be critically evaluated to ensure that the results 

are credible for their specific intended use, and this is typically done using an evaluation process (L) 

which is included in the M&S methodology (M) and informs the model developer (U) of the quality of 

the M&S capability and results in addressing the problem at hand (S).

Evaluation of M&S capabilities and results should take into account the many factors that affect the 

quality of the results including the level of understanding or knowledge of the issues being addressed and 

the experience level of model developers. Several organizations have developed processes and guidelines 

to address the credibility of M&S capabilities. For example, DoD has a process for documentation, 

evaluation, and certification of M&S results known as Verification, Validation and Accreditation 

(VV&A) that is defined in a recommended practice guide [DoD 2006]. The DoD process is implemented 

in policy, which develops a common understanding of the major steps in the VV&A process defined as 

below [DoD 2009]:

• Verification. The process of determining that a model implementation and its associated data 

accurately represents the developer’s conceptual description and specifications. 

• Validation. The process of determining the degree to which a model and its associated data are an 

accurate representation of the real world from the perspective of the intended uses of the model. 

• Accreditation. The official certification that a model, simulation, or federation of models and 

simulations and its associated data are acceptable for use for a specific purpose.

All M&S capabilities should complete verification and validation (V&V). M&S capabilities used as the 

primary input to critical decision making, e.g., on cost, schedule, or performance of the system, should be 

formally accredited to certify that the results are credible for their intended use. Analysts and decisionmakers need to be aware of these sorts of issues when presented with computational modeling and 

simulation results.

[Balci 1998] developed a taxonomy and describes the use of different methods to evaluate M&S 

capabilities and results based on software testing approaches. Figure 6 identifies these verification, 

validation, and testing methods or techniques which can be used to support an evaluation process such as 

VV&A. 

In addition to the use of recommended practices for conceptual modeling and ensuring model credibility, 

model developers should employ recommended practices for a number of other aspects. [Jain 2011] 

recommends best practices for modeling, simulation, and analysis for homeland security applications for 

the following aspects:

1. conceptual modeling 

2. innovative approaches 

3. software engineering 

4. model confidence/ verification, validation and accreditation (VV&A) 

5. use of standards 

6. interoperability 

7. execution performance 

8. user friendliness and accessibility 
11

Figure 6: Taxonomy of Verification, Validation, and Testing Techniques (from [Balci 1998])

4. Needs Analysis Overview

Modeling and simulation should be used to support the needs of various managers, analysts, service 

providers, and first responders within the homeland security community. Most importantly, it must 

support the planning and response needs of the National Infrastructure Protection Plan (NIPP) partners 

including the Department of Homeland Security and other federal, state, local, tribal, territorial, and 

private sector organizations. The high level needs identified below have been derived from the National 

Infrastructure Simulation and Analysis Center (NISAC) mission statement, as well as a number of other 

DHS documents, and outside sources. An initial list of high level user/customer needs for healthcare 

M&S follows:
12

• Provide simulation and analysis capabilities to a wide range of users that will enhance the 

understanding of vulnerabilities, risks, and event consequences to healthcare systems.

• Provide M&S capabilities to help establish priorities and potential mitigation strategies for protecting 

and/or isolating the impact of events on the population and healthcare systems.

• Provide models of the normal operations of healthcare systems, as well as the effects of epidemics, 

natural disasters, and terrorist attacks upon them to support analysis, planning, and response activities 

of homeland security healthcare system partners; predict economic impacts of disasters and other 

relevant healthcare events; support planning for facility defense and security, selection and placement 

of healthcare monitoring devices and system sensors to update status information, damage 

assessment, coordinated shutdown, and accelerated recovery of healthcare systems; establish 

healthcare models, simulations, and data sets that support the national planning scenarios.

• Provide decision-makers the ability to assess policy, investment, and resource allocation options that 

address healthcare systems needs – near and long term.

• Provide an integrating function that includes the identification and modeling of healthcare system 

interdependencies; supported interdependencies should include physical, geographic, cyber, and 

logical [Rinaldi 2004] enables the integration of national, regional, local systems and data sources;

brings together disparate users, information providers, and individual infrastructure sector leaders.

• Move towards predictive capabilities that use science-based tools to understand the behavior and 

expected performance of interrelated infrastructures; predictive capabilities should support various 

conditions, healthcare systems, and event parameters such as time of day for events, level of demand 

for the healthcare system, system weaknesses, capacity of facilities, mobilization resources, surge 

capacity, temporary support organizations, their systems, and functions.

• Provide education and training to public and private decision-makers on how to cope effectively with 

crisis events.

• Establish virtual capabilities that provide portals for nation-wide remote access and communications 

to healthcare-related modeling, simulation, and analysis capabilities; identify data and interfaces 

needed for each healthcare model and event type; provide standard formats for the import and export 

of data between the portal and external data sources; help plan for the backup and/or remote siting of 

critical data sources outside of regions affected by events, e.g., hurricane disaster areas.

Other possible application scenarios that may help to define M&S user needs and system requirements for 

healthcare systems include:

• Resource planning, capacity analysis, & deployment

• Care prioritization and management

• Patient diagnosis, treatment, and other medical processing models

• Emergency medical response operations

• Layout of hospital facilities, departments, and processes

• Flow of health care documentation and information

• Mass preventative measures

• Public health strategies (quarantines, vaccinations)

• Coordination with other government agencies, HMOs, and other organizations

• Laboratory test procedures and identification of biological agents

• Decontamination and treatment for radiation exposure

• Media interactions for healthcare-related preventative activities and emergency incidents
13

5. Requirements Specifications

This section translates the high level needs discussed in the previous section to a set of requirements. The 

requirements are intended to be common across all healthcare systems and hence at a high level. These 

requirements will serve as the starting set that may need to be enhanced for specific healthcare system for 

unique intended use. A separate document with a more detailed set of common requirements is being 

developed in a related effort.

5.1. Intended Use

Healthcare systems models and simulations will be used by healthcare organization managers, emergency 

planners, first responders, doctors and nurses, support and training personnel to:

a) Analyze the resource requirements, behavior, and performance of healthcare systems.

b) Conduct training exercises, drills, emergencies, tests, alerts, and support real world incidents (natural 

disasters, terrorist attacks, and epidemics).

c) Determine the readiness of healthcare systems to respond to various types of emergencies.

d) Model past incidents for education, training, and analysis purposes.

5.2. Functional Requirements

This section identifies possible functions that may be included in healthcare system models and 

simulations.

a) Provide functions to create high level models of healthcare system operations and evolutions over 

time to support system performance and resource analysis.

b) Provide training and exercise simulations for healthcare personnel that provide functionality for 

various incident and exercise parameters, exercise control, and after action reviews.

c) Provide various types of training implementations including tabletop exercises, 2D and 3D computer 

gaming, immersive virtual reality environments, training facilities, and mannequins.

d) Provide capabilities to refine simulations based on actual incident data, hospital usage data, medical 

assessments, and field measurements.

e) Support representations of geography, buildings, disease exposure and spread, lethality levels, 

healthcare institutions, equipment, personnel, victims, patients.

f) Support the integration and/or distributed execution of interrelated models including epidemics, 

hazardous material release exposure and hazard effects, critical infrastructure systems, incident 

management systems, and weather.

g) Identify regions where the exposed population will experience life threatening, serious long-lasting, 

or notable effects from incidents.

5.3. Data Requirements

This section identifies input and output data types that may be supported for healthcare models and 

simulations.

a) Structure of healthcare organizations and inventory of resources

b) Standard healthcare processes and procedures (e.g. triage and treatments)

c) Message logs and incident time lines

d) Specification of the incident area including event types and parameters, timing of events, schedule of 

responder and healthcare personnel activities, population, terrain and buildings in affected areas
14

e) Demographics data: population location, density, and attributes by time of day

f) Meteorological data: observed and forecast weather conditions that may affect an incident including 

wind speed, direction, and precipitation

g) Plume data hazardous material releases and explosions

h) Support of appropriate data standards in model implementations, training and exercise simulations, 

e.g., SCORM – Shareable Content Object Reference Model [ADL 2011]

5.4. User Interface Requirements

This section identifies user interface capabilities that may be supported for healthcare system models and 

simulations.

a) Provide capabilities to configure simulation runs with specific incident types and associated 

parameters, affected populations, responder and healthcare system resources, weather conditions, and 

geographic regions.

b) Generate graphical views of incident, responder, and healthcare system activities over a 2D or 3D 

representation of area of interest at different levels of resolution.

c) Provide user control mechanisms that affect rapid execution/playback of simulation runs to move 

forward and back to desired points in time.

d) Use various DHS standard symbology, maps, and representation schemes to display incident 

parameters, resource locations, and timelines.

e) Provide virtual reality interfaces to support 3d gaming for healthcare exercises.

f) Provide exercise controller interfaces to effect the initiation, execution, as well as playback of 

exercise simulations for after action reviews and hot washes.

g) Provide interfaces to generate still image and video files that can be used to transfer results for 

viewing or playback using other software tools.

5.5. Performance Requirements

This section identifies possible performance considerations for healthcare system models and simulations.

a) Support time scaling of models and simulations and abilities to move forward rapidly in time to focus 

on events of interest (real-time for training and faster than real-time to support analysis during actual 

incidents and planning).

b) Provide for updates from real time epidemic, incident, meteorological databases and observations.

c) Share model predictions with other software applications.

d) Provide capabilities for interoperable networked implementations at different sites by different 

organizations.

5.6. Credibility and Evaluation Requirements

This section identifies approaches that may be used to evaluate and determine the credibility of healthcare 

models and simulations.

a) Conduct walkthroughs of simulation models of healthcare simulations and models with experienced 

healthcare personnel, incident managers and first responders.

b) Compare results and predictions of healthcare system models against past events using historical data.

c) Conduct side by side training exercises using conventional techniques (e.g., tabletop exercises) and 

computer-based simulations to compare effectiveness in achieving intended goals such as training 

objectives, realism, and exercise resource requirements.
15

6. Identification of M&S Resources

This section identifies existing M&S resources that support emergency healthcare systems and are 

possibly relevant to meeting some of the needs and requirements presented in sections 4 and 5. Resources 

that primarily support other M&S areas or domains, e.g., incident command, are not included. The 

section is divided into: 

• Projects, Facilities, and Capabilities (6.1)

• Simulations, Models and Tools (6.2)

• Relevant Standards and Guidelines (6.3)

• Data Sources (6.4)

The term “simulation” is used to include a wide variety of modalities in healthcare area. The Center for 

Immersive and Simulation-based Learning (CISL) at Stanford School of Medicine [Stanford 2010] 

defines the following simulation modalities in the healthcare context: standardized patient actors, parttask physical trainers, virtual reality and visualization, desktop simulation and virtual worlds, and 

mannequin-based simulation. Modeling and simulation (M&S), the focus of this report, has been defined 

to focus on computer based simulation and hence aligns primarily with the desktop simulation and virtual 

worlds and overlaps somewhat with the virtual reality and visualization modalities in CISL list. The subsections below hence primarily provide information relevant to the selected focus.

6.1. Projects, Facilities, and Capabilities

A number of projects and facilities focus on healthcare simulation. However a majority of them focus on 

standardized patient actors, part-task physical trainers, and mannequin-based simulation. A preliminary 

list of projects, facilities and capabilities that include the categories of our interest, i.e., desktop simulation 

and virtual worlds, and virtual reality and visualization, is provided below.

Center for Integration of Medicine and Innovative Technology (CIMIT) – CIMIT focuses on health care 

technologies, providing the resources and infrastructure to address technology application issues at the 

national and international level. CIMIT acts as a bridge between individual investigators and 

implementation of their ideas. It connects the investigators with a team of experts, and provides a 

nurturing collaborative environment to help the idea grow towards multiple uses, multiple partners, and 

multiple programs to address complex patient care problems. The work of simulation group at CIMIT 

includes building desktop simulation tools such as the Real-time Incident Preparedness Simulation (RIPS) 

[CIMIT 2010].

Complex Incident Response Training System (CIRTS)-Combat Medics (CM) project – MYMIC LLC is 

developing CIRTS-CM under a Small Business Innovation Research Phase II contract award in early 

December 2009. CIRTS-CM is a simulation game based training system for scene and patient 

management care following blast injuries sustained from explosives including Improvised Explosive 

Devices (IEDs). Eventually, CIRTS-CM support will expand to other medical domains, such as training 

combat lifesavers, individual soldiers and marines, military combat support hospitals, civilian emergency 

medical technicians, other emergency first responders and incidents other than IEDs [MYMIC 2010a].

NIH Center for Biomedical Computation at Stanford (Simbios) – Simbios is the NIH Center for physicsbased Simulation of Biological Structures. Simbios provides infrastructure, software, and training to help 

biomedical researchers understand biological form and function as they create novel drugs, synthetic 

tissues, medical devices, and surgical interventions. Simbios is investigating a wide scale of biological 

structures – from molecules to organisms. Driving biological problems include RNA folding, protein 
16

folding, myosin dynamics, cardiovascular dynamics, and neuromuscular biomechanics. Simbios is 

developing and disseminating the SimTK core simulation toolkit, an open-source software that includes 

capabilities for modeling the geometry and physics of biological systems. To ensure utility and accuracy, 

the software and training material is being developed and tested in close collaboration with biomedical 

scientists. Simbios has developed OpenSim, an application for advanced neuromuscular modeling that 

uses the SimTK toolkit, and is making it openly available [SIMBIOS 2010]. 

National Capital Area Medical Simulation Center – The SimCenter is part of the Uniformed Services 

University of the Health Sciences (USUHS) located in the Forest Glen Annex Silver Spring, Maryland. It 

has facilities for simulating medical procedures that are high risk or high consequence for patient safety. 

The simulations allow healthcare personnel develop and maintain the cognitive and psychomotor skills 

necessary to perform medical tasks safely and effectively. The Virtual Medical Environment Lab at the 

center includes surgical, emergency room and field hospital simulations, medical gaming as well as largescale simulations designed to train medical teams in battlefield and natural-disaster scenarios [USU 

2010]. 

National Center for Collaboration in Medical Modeling and Simulation – The NCCMMS is a joint 

project of Eastern Virginia Medical School (EVMS) and Old Dominion University (ODU) and a variety 

of academic, governmental and commercial partners. Its mission is to improve both the quality and 

quantity of medical care available to U.S. military forces. This is accomplished by providing a 

collaborative environment where basic and applied medical modeling and simulation research can be 

undertaken by EVMS and ODU researchers within the context of a comprehensive academic medical 

center that provides a convenient clinical test bed for new technologies and approaches. The center has 

access to the expertise of the large U.S. military medical community as represented by the Naval Medical 

Center, Portsmouth, the Uniformed Services University of the Health Sciences, and other military medical 

facilities. Projects at NCMMS include homeland security, emergency training and response, and gaming 

simulations [EVMS 2009].

Medical Emergencies Simulation Lab, Institute for Simulation and Training, University of Central 

Florida – The lab builds on simulators developed by others to create sophisticated medical simulation 

capabilities that can enhance military, civil defense, and crisis management training. For example, the lab 

developed HLA-compliant software packages that allow simulated casualties generated during combat 

exercises to queue up for treatment by combat medics using a human patient simulator. The playing-fieldto-emergency treatment model also has been used to train EMTs in civilian mass casualty exercises [IST 

2009].

6.2. Simulations, Models and Tools

A number of healthcare and epidemic modeling tools have been developed through the efforts of federal 

agencies, universities, research organizations and commercial companies. This section lists existing tools 

that have been identified through Internet searches and site visits to organizations involved in M&S of 

healthcare systems. The tools are arranged alphabetically based on their developer’s acronyms, or in some 

cases, abbreviations assigned by the authors for purposes of the readability of this document. Similar to 

the previous sub-section, the focus is on models and tools for desktop simulation and virtual worlds, and 

virtual reality and visualization.

Tool Acronym Brief Description

Code Orange BreakAway developed a training simulation called ”Code Orange” for the 

Washington Hospital Center to train staff in the job roles they would have to assume 

in a mass casualty incident. Based on job descriptions and tasked outlined in the 
17

Hospital Emergency Incident Command System (HEICS) protocol, this simulation 

allows users to assume roles in triaging patients outside the hospital and inside the 

ER [Breakaway 2010].

CVMDM Community Vaccination and Mass Dispensing Model (CVMDM) simulates the 

allocation and distribution of pharmaceutical materials across a jurisdiction and the 

dispensing of those materials through points of dispensing (PODs). Given a request 

time for initial supplies from the Center for Disease and Prevention Control’s 

Strategic National Stockpile, estimated resupply intervals, population size and age 

distribution, and POD personnel resources, the model calculates the estimated start 

time for public vaccinations, POD queue times and throughput, and operation 

closure. Linked with a disease progression submodel, CVMDM tracks and reports the 

number of infections and fatalities based on disease characteristics and the 

performance of prophylaxis supply logistics and PODs [ANL 2011].

EDS ED Simulator (EDS) is a tool for Emergency Department throughput, staffing, patient 

flow, and efficiency analysis. EDS combines the power and analytical capabilities of 

simulation with database and data analysis technologies. It is designed to be used at 

the unit Manager level as a tool for ongoing process analysis, continuous process 

improvement, and accurate, objective internal benchmarking. It is based on 

MedModel simulation “engine” [ProModel 2010a].

Edsim Edsim is a semi-reusable product to quickly model and test alternative design 

scenarios for existing and proposed hospital emergency departments. It meets the 

needs of hospital administrators to improve Key Performance Indicators (KPIs), such 

as patient length of stay (LOS), bed utilization, elimination of bottlenecks, etc. 

Edsim is also useful for predicting performance of proposed emergency departments 

before finalizing architectural designs [Ferrin 2007].

EDSIM Emergency Department SIMulation (EDSIM) was developed through a cooperative 

effort involving the University of California, Davis, Medical Center (UCDMC) 

Department of Emergency Medicine and the UCDMC billing department using the 

Extend Suite v.5 modeling platform developed by Imagine-That, Inc. It provides 

modules that are connected by conduits that carry data elements representing 

patients, staff, orders, laboratory results, images, etc. It combines continually updated 

job queue prioritization and mid-task preemption capabilities that together allow the 

model to capture the chaotic nature of ED staff activity [Connelly 2004].

ED Simulation ED Simulation is a desktop application designed specifically for quickly modeling 

and simulating Emergency Departments. It reduces the programming by pre-building 

Emergency Department workflow processes. Its applications include: minimizing

patient waiting times and ED overcrowding, identifying workflow “bottlenecks,” 

evaluating the effect of patient arrival and symptom mix, and testing disaster 

preparedness scenarios [Loud Squirrel 2011].

EpiSimS The epidemic simulation engine, EpiSimS is a C++ application that runs on highperformance computing clusters. It is stochastic agent-based discrete event model 

that explicitly represents every person in a city, and every place within the city where 

people interact. A city or region is represented physically by a set of road segment 

locations and a set of business locations. EpiSimS can simulate various 
18

pharmaceutical and non-pharmaceutical interventions, including panic-based stayhome behavior, therapeutic and prophylactic use of antivirals, contact tracing, 

vaccination, wearing of masks, social distancing behaviors (increased inter-personal 

separation, hand washing, cough etiquette, etc.), household quarantine, and closures 

of schools [LANL 2010].

GameTT Games For Team Training (GaMeTT) is an immersive avatar based, virtual 

environment designed for distributed medical team training. Participants log in to 

GaMeTT from their own office or homes to work collectively towards team training 

objectives, optimizing the time available for training and the opportunity for team 

interaction. GaMeTT utilizes game-based technology to produce visually engaging 

scenes, user friendly interfaces, and intuitive user commands. The tool is suitable for 

distributed medical teams such as the Disaster Medical Assistance Teams (DMAT) 

that are comprised of 35 volunteers who come together from different parts of the 

country to form a team in case of a disaster [MYMIC 2010b].

HMS Healthcare Modeling Studio. A simulation modeling solution, is used to build custom 

analysis tools for a variety of healthcare facilities, including emergency departments, 

operating rooms, admissions, clinical labs and ancillary services. The tool can be 

tailored to each client’s specific processes, organization, terminology and metrics, 

HMS helps healthcare professionals improve administrative and operational 

efficiency, reduce cost and maximize ROI, validate process change or facility 

expansion, and predict the impact of staffing changes or equipment upgrades [AAI 

2007].

LES Learning Environment Simulator (LES) developed at Los Alamos National Labs has 

been built as an interface to Critical Infrastructure Protection Decision Support 

System (CIPDSS). It is designed to engage decision makers at the grass-roots level 

(local/city/state), deepen their understanding of an evolving crisis, enhance intuition 

and let them test their own strategies. The initial version is based on a pandemic 

influenza outbreak and has been tested with a group of hospital administrators and 

first responders. LES is a simulated environment allowing the user to experience the 

complexities of a crisis before it happens, including impacts to critical infrastructures 

with their interdependencies and estimating human health & safety and economic 

impacts [LeClaire 2009].

MEDMODEL MedModel is a simulation tool designed specifically for the healthcare industry for 

evaluation, planning and redesign of hospitals, clinics, and other healthcare systems. 

MedModel models can be used to identify inefficiencies in an existing process and 

test a variety of scenarios. Typical applications include: department specific 

productivity improvement, facilities design (labs, clinics, radiology, emergency 

rooms, etc.), planning for future changes, staff planning, analyzing patient capacity, 

equipment planning and logistical analysis, emergency preparedness, and bed 

capacity management [ProModel 2010b].

MUSTER MUSTER is a simulation tool for Multi-user Emergency Response training. 

MUSTER supports training of doctors, nurses, Paramedics, EMT’s, rescue workers, 

disaster medicine rescue teams and others in disaster medicine and management. The 

core of the training simulator is the patient model. The model has been developed by 

Danish doctors, and is able to simulate a patient’s condition dynamically based on the 
19

injuries and the treatment he receives. Patients in a scenario can be defined 

individually [IFAD 2011].

Optima Predict Optima predict is an interactive strategic planning solution for emergency services 

that provides a platform for effective planning and simulation of requirements of 

resources such as ambulances. Optima Predict takes into account key performance 

indicators such as response times, vehicle types and coverage, shift rosters, post 

locations and hospital ramp times to enable users to quickly build scenarios that make 

logistical and business sense [Optima 2011].

PLAN C Planning with Large Agent-Networks against Catastrophes (PLAN C) is an agent 

based simulation tool for emergency managers, urban planners and public health 

officials to prepare and evaluate Pareto-optimal plans to respond to urban 

catastrophic situations. PLAN C has been used to simulate emergency responses in 

different urban catastrophic scenarios (e.g., chemical agent, bomb explosion, food 

poisoning, small pox). It can devise plans that optimize multiple objective functions 

(e.g., number of casualties, economic impact, time to recovery, etc.) in terms of their 

Pareto frontier in a high-dimensional space; for this purpose, it uses an evolutionary 

genetic search algorithm [NYU-CCPR 2009].

RIPS Real-time Incident Preparedness Simulation developed by the SimGroup at the 

Center for the Integration of Medicine and Innovative Technology (CIMIT) is a 

training tool for emergency response personnel. It is an incident simulator with game 

like qualities and it provides a platform for creating disaster scenarios, sharing them, 

and then training on them with other professionals. It is based on the NIMS hierarchy 

[CIMIT 2002]. 

SimCare SimCare Process Simulator 9.0 is a process simulation software for the healthcare 

industry. SimCare pro healthcare simulation includes support for hospitals, clinics, 

and blood centers. It allows for importing CAD files for the facilities such as 

emergency departments, and historical data for rapid model development of the 

model [CreateASoft 2011].

6.3. Relevant Standards and Guidelines

This section identifies standards and guidelines that are potentially relevant to the development of M&S 

applications for healthcare systems. The standards and guidelines may include mechanisms and formats 

for the interchange of data, data storage, generation of information displays, integration of systems, and/or 

conceptualization and design of healthcare M&S applications. Subsection 1 includes the standards that 

are specific to healthcare domain. The following subsections list standards that are common across the 

homeland security applications of M&S and focus on conceptual modeling, distributed simulation, 

geographical information system (GIS), and communications respectively.
20

6.3.1. Domain Specific Standards

Standard Title Overview

After a Terrorist Bombing: Health 

and Safety Information for the 

General Public

Description: A document contains “Immediately after the 

event” and “Hours or days after the event” for helping people 

who have been affected by the blast and will provide updated 

information as soon as they learn more [CDC 2010a].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Bioterrorism Readiness Plan: A 

Template for Healthcare Facilities

Description: A Bioterrorism Readiness Plan to serve as a 

reference document and initial template to facilitate preparation 

of bioterrorism readiness plans for individual institutions [CDC 

2010b].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC), The Association for Professionals in Infection Control 

and Epidemiology (APIC) Bioterrorism Task Force

Classification: Operational guidelines

Business Continuity/Disaster 

Recovery Plan

Description: The business continuity/disaster recovery plan is 

to identify the most critical information needs for patient care, 

treatment, and services and business processes, and the impact 

on the hospital if these information systems were severely 

interrupted. The plan identifies alternative means for processing 

data, providing for recovery of data, and returning to normal 

operations as soon as possible [JCAHOSTD 2010].

Standard Type: IM.2.30 (2008)

Organization: The Joint Commission 

Classification: Operational guidelines

Common Biometric Exchange 

Formats Framework (CBEFF)

Description: The standard specifies a common set of data 

elements necessary to support multiple biometric technologies 

and to promote interoperability of biometric-based application 

programs and systems by allowing for biometric data exchange. 

These common data elements can be placed in a single file, record, or data object used to exchange biometric information 

between different system components and applications. This 

standard specifies the biometric data elements [ANSI 2010].

Standard Type: ANSI INCITS 398-2008

Organization: American National Standards Institute (ANSI)

Classification: Document Format

Communicating in the First Hours 

for Anthrax: Short and Extended 

Messages

Description: These messages can be used by public health 

officials during the first hours after a suspected anthrax 

emergency. The short messages include essential information to 

help minimize the immediate risk to the public from an attack. 

The extended messages also include general information that 
21

can be used as a resource for officials in developing messages 

tailored to a specific situation [CDC 2010c].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Community-Based Mass 

Prophylaxis: A Planning Guide for 

Public Health Preparedness

Description: Planning guide to help state, county, and local 

officials meet federal requirements to prepare for public health 

emergencies [AHRQ 2010a]. Outlines five components of mass 

prophylaxis response to epidemic outbreaks. Addresses 

dispensing operations using a comprehensive operational 

structure for Dispensing/Vaccination Centers (DVCs) based on 

the National Incident Management System (NIMS). 

Standard Type: N/A

Organization: The Agency of Healthcare Research & Quality 

(AHRQ)

Classification: Operational guidelines

Digital Imaging and 

Communications in Medicine 

(DICOM)

Description: A specification for exchange of radiology images 

and other medical information between computers. It enables 

digital communication between diagnostic and therapeutic 

equipment and systems from various manufacturers. DICOM is 

a global Information-Technology that is used in virtually all 

hospitals worldwide. Its current structure is designed to ensure 

the interoperability of systems to produce, store, display, 

process, send, retrieve, query or print medical images and 

derived structured documents as well as to manage related 

workflow [NEMA 2010].

Standard Type: DICOM 3.0

Organization: American College of Radiology (ACR), and 

National Electrical Manufacturers Association (NEMA)

Classification: General purpose integration interfaces

Disaster Privileges Description: A plan that identifies the option to grant privileges 

during disaster situations to doctors and other licensed 

practitioners [JCAHOSTD 2010].

Standard Type: MS.4.110; HR.4.35

Organization: The Joint Commission Resources 

Classification: Operational guidelines

Drawing Interchange File (DXF) 

Formats

Description: The DXF format is a tagged data representation of 

all the information contained in an AutoCAD drawing file. 

Tagged data means that each data element in the file is preceded 

by an integer number that is called a group code. A group code’s 

value indicates what type of data element follows. This value 

also indicates the meaning of a data element for a given object 

(or record) type. Virtually all user-specified information in a 

drawing file can be represented in DXF format [AUTODESK 

2010]. DXF can be used for exchange of radiology images and 
22

other medical information between computers.

Standard Type: AutoCAD 2009, v.u.23.1.01 

Organization: Autodesk, Inc.

Classification: General purpose integration interfaces

Emergency Electrical Power Source Description: A plan that describes the requirements of a 

hospital’s emergency power system [JCAHOSTD 2010].

Standard Type: EC.7.20

Organization: The Joint Commission Resources 

Classification: Operational guidelines

Emergency Management Drills Description: A plan that describes a hospital’s approach to 

conduct drills to test emergency management [JCAHOSTD 

2010].

Standard Type: EC.4.20

Organization: The Joint Commission Resources 

Classification: Operational guidelines

Emergency Management Planning Description: An emergency management plan that 

comprehensively describes the approach to emergencies in the 

hospital or its community [JCAHOSTD 2010].

Standard Type: EC.4.10

Organization: The Joint Commission Resources 

Classification: Operational guidelines

Environment of Care Crosswalk Description: The Joint Commission Resources, a not-for-profit 

affiliate of The Joint Commission, released the Environment of 

Care Crosswalk. The 2009 Environment of Care Crosswalk 

helps hospitals to simplify their compliance activities and 

recognize when there is a duplication of requirements between 

the Joint Commission 2009 Environment of Care, Emergency 

Management, and Life Safety Standards, and the regulations of 

the Occupational Safety and Health Administration (OSHA), the 

Environmental Protection Agency (EPA) [JCR 2010].

Standard Type: 2009 Environment of Care

Organization: The Joint Commission Resources 

Classification: Operational guidelines

Facts About the Laboratory 

Response Network

Description: Description of the network of labs that respond to 

biological & chemical terrorism. In 1999, the Centers for 

Disease Control and Prevention (CDC) established the 

Laboratory Response Network (LRN). The LRN’s purpose is to 

run a network of labs that can respond to biological and 

chemical terrorism, and other public health emergencies. The 

LRN has grown since its inception. It now includes state and 

local public health, veterinary, military, and international labs. 

This fact sheet provides a brief description of the LRN, and how 

it works [CDC 2010d].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 
23

(CDC)

Classification: Operational guidelines

Guidance for Protecting Building 

Environments from Airborne 

Chemical, Biological, or 

Radiological Attacks

Description: This document identifies actions that a building 

owner or manager can implement without undue delay to 

enhance occupant protection from an airborne chemical, 

biological, or radiological attack [CDC 2010e].

Standard Type: N/A

Organization: The National Institute for Occupational Safety & 

Health (NIOSH); The Centers for Disease Control and 

Prevention (CDC)

Classification: Operational guidelines

Guidance for Public Health 

Departments and Clinicians Caring 

for Individuals Who May Have Been 

Recently Exposed to Polonium -210

Description: Clinical guidance recommendations for public 

health departments and clinicians to care people who may have 

been recently exposed to Polonium -210 (Po-210). Po-210 is 

considered to be one of the most hazardous radioactive materials 

known, but it must be inhaled or ingested to exert its toxic 

effects. It is found naturally in the environment, and the general 

population is internally contaminated with small but measurable 

amounts of it on a regular basis through food, water, and air 

[CDC 2010f]. 

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention

(CDC)

Classification: Operational guidelines

Guidance on Initial Responses to a 

Suspicious Letter/Container With a 

Potential Biological Threat

Description: Guidelines for local responders, based on existing 

procedures, on the initial response to letters, packages, or 

containers containing suspicious powders, liquids, or other 

materials [DHS 2010b].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC), Federal Bureau of Investigation (FBI), Department of 

Homeland Security (DHS)

Classification: Operational guidelines

Guidelines for Handling Decedents 

Contaminated with Radioactive 

Materials

Description: Detonation of a nuclear weapon or activation of a 

radiological dispersal device could cause radioactively 

contaminated decedents. These guidelines are designed to 

address both of these scenarios. They could also be applicable in 

other instances where decedents’ bodies are contaminated with 

radioactive material (e.g., reactor accidents, transportation 

accidents involving radioactive material, or the discharge of a 

decedent from a hospital after injection or implantation of a 

radiopharmaceutical). These guidelines suggest ways for 

medical examiners, coroners, and morticians to deal with loose 

surface contamination, internal contamination, or shrapnel on or 

in decedents’ bodies [CDC 2010g].

Standard Type: N/A
24

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Health Insurance Portability and 

Accountability Act (HIPAA) 

Description: The Health Insurance Portability and 

Accountability Act (HIPAA) is a federal law that provides rights 

and protections for participants and beneficiaries in group health 

plans. HIPAA includes protections for coverage under group 

health plans that limit exclusions for preexisting conditions; 

prohibit discrimination against employees and dependents based 

on their health status; and allow a special opportunity to enroll 

in a new plan to individuals in certain circumstances [DOL 

2010]. The Administrative Simplification provisions of the 

Health Insurance Portability and Accountability Act of 1996 

(HIPAA, Title II) required the Department of Health and Human 

Services (HHS) to establish national standards for electronic 

health care transactions and national identifiers for providers, 

health plans, and employers. As the industry has implemented 

these standards, and increased the use of electronic data 

interchange, the nation’s health care system will become 

increasingly effective and efficient [HHS 2010a]. 

Standard Type: HIPAA of 1996 (P.L.104 – 191) 

Organization: Department of Health and Human Services 

(HHS)

Classification: Operational guidelines

Health Insurance Portability and 

Accountability Act (HIPAA) Security 

Rule

Description: The HIPAA Security Rule establishes national 

standards to protect individuals’ electronic personal health 

information that is created, received, used, or maintained by a 

covered entity. The Security Rule requires appropriate 

administrative, physical and technical safeguards to ensure the 

confidentiality, integrity, and security of electronic protected 

health information [HHS 2010b].

Standard Type: HIPAA Security Rule 164.308 (a)(7)(i)

Organization: National Institute of Standards and Technology 

(NIST) 

Classification: Operational guidelines

Health Level Seven (HL7) Standards Description: Health Level Seven is one of several American 

National Standards Institute (ANSI) –accredited Standards 

Developing Organizations (SDOs) operating in the healthcare 

arena. Health Level Seven’s domain is clinical and 

administrative data [HL7 2010]. HL7 standards are used for the 

exchange, management, and integration of electronic healthcare 

information.

Standard Type: ANSI/HL7 V2 XML-2003; ANSI/HL7 V2.5-

2003; ANSI/HL7 V3 DSR, R1-2005, ..... ANSI/HL7 V3 PM, 

R1-2005; ANSI/HL7 V3 CR, R3-2005; ANSI/HL7 V3 MFRI, 

R1-2006

Organization: Health Level Seven (HL7); American National 

Standards Institute (ANSI)
25

Classification: Domain-specific integration interfaces

Infection Control Description: A plan that is used by the hospital to respond to an

influx, or the risk of an influx, of infectious patients 

[JACHOSTD 2010].

Standard Type: IC.6.10

Organization: The Joint Commission Resources 

Classification: Operational guidelines

Interim Guidelines for Hospital 

Response to Mass Casualties from a 

Radiological Incident

Description: The guidance focuses on six key areas: (1) 

notification and communication, which emphasizes the 

importance of hospitals working with their communities and 

public health agencies on developing emergency communication 

plans; (2) triage; (3) patient management, including 

decontamination, treatment, care of special populations, 

discharge and follow up, and patient mental health concerns; (4) 

healthcare provider protection, including staff training and 

practitioner mental health concerns; (5) surveillance, and (6) 

community planning [CDC 2010h].

Standard Type: N/A

Organization: the Centers for Disease Control and Prevention 

(CDC) 

Classification: Operational guidelines

Interim Life Safety Measures (ILSM) Description: Guidelines for Design and Construction of 

Hospital and Health Care Facilities to minimize the possibility 

of injury or damage due to fire, smoke & fumes, or other threat. 

ILSM are health and safety measures that are put in place to 

protect the safety of patients, visitors, and staff who work in the 

hospital [BMET 2010].

Standard Type: ILSM

Organization: The Joint Commission Resources 

Classification: Operational guidelines

Interim Recommendations for 

Firefighters & Other First 

Responders for the Selection & Use 

of Protective Clothing & Respirators 

Against Biological Agents

Description: This interim statement of selection and use of 

protective clothing and respirators against biological agents is 

based on current understanding of the potential threats and 

existing recommendations issued for biological aerosols. The 

approach to any potentially hazardous atmosphere, including 

biological hazards, must be made with a plan that includes an 

assessment of hazard and exposure potential, respiratory 

protection needs, entry conditions, exit routes, and 

decontamination strategies [CDC 2010i]. 

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC)

6.3.2. Classification: Operational guidelines

International Classification of 

Diseases

Description: The International Classification of Diseases (ICD) 

is designed to promote international comparability in the 

collection, processing, classification, and presentation of 
26

mortality statistics. This includes providing a format for 

reporting causes of death on the death certificate. The reported 

conditions are then translated into medical codes through use of 

the classification structure and the selection and modification 

rules contained in the applicable revision of the ICD, published 

by the World Health Organization. These coding rules improve 

the usefulness of mortality statistics by giving preference to 

certain categories, by consolidating conditions, and by 

systematically selecting a single cause of death from a reported 

sequence of conditions. The single selected cause for tabulation 

is called the underlying cause of death, and the other reported 

causes are the non-underlying causes of death. The combination 

of underlying and non-underlying causes is the multiple causes 

of death. The ICD has been revised periodically to incorporate 

changes in the medical field. To date, there have been 10 

revisions of the ICD. [CDC 2010j].

Standard Type: ICD-10; ICD-10-CM (ICD-10 Clinical 

Modification) 

Organization: The National Center for Health Statistics 

(NCHS); Centers for Medicare and Medicaid Services 

Classification: Operational guidelines

Introductory Resource Guide for 

Implementing the Health Insurance 

Portability and Accountability Act 

(HIPAA) Security Rule 

Description: A publication discusses security considerations 

and resources on security terms and concepts used and presented 

in the HIPAA security rule [NIST 2010a].

Standard Type: N/A

Organization: National Institute of Standards and Technology 

(NIST) 

Classification: Operational guidelines

Maintenance, Testing, and 

Inspection Requirements for Hospital 

Emergency Power System 

Description: A plan that identifies how a hospital maintains, 

tests, and inspects its emergency power system [JCAHOSTD 

2010].

Standard Type: EC.7.40

Organization: The Joint Commission Resources 

Classification: Operational guidelines

Managing Hazardous Material 

Incidents (MHMI)

Description: The MHMI series is a three volume set (with a 

video) comprised of recommendations for on-scene (prehospital), and hospital medical management of patients exposed 

during a hazardous materials incident [CDC 2010k]. 

Standard Type: N/A

Organization: The Agency for Toxic Substances and Disease 

Registry (ATSDR)

Classification: Operational guidelines

Mass Casualty Event Preparedness 

and Response

Description: This document provides information of 

preparedness and response for preparing for a terrorist bombing, 

after a terrorist bombing, coping with a traumatic event, 

emergency wound care, injuries, brain injuries, and burns, etc. 
27

[CDC 2010l].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Medical Management Guidelines for 

Unidentified Chemicals

Description: Basic victim management recommendations to 

follow when the chemical is not known [CDC 2010n].

Standard Type: N/A

Organization: The Agency for Toxic Substances and Disease 

Registry (ATSDR)

Classification: Operational guidelines

NIOSH Pocket Guide to Chemical 

Hazards (NPG)

Description: The NIOSH Pocket Guide to Chemical Hazards 

(NPG) is intended as a source of general industrial hygiene 

information on several hundred chemicals/classes for workers, 

employers, and occupational health professionals. The NPG 

does not contain an analysis of all pertinent data, rather it 

presents key information and data in abbreviated or tabular form 

for chemicals or substance groupings (e.g., cyanides, fluorides, 

manganese compounds) that are found in the work environment. 

The information found in the NPG should help users recognize 

and control occupational chemical hazards [CDC 2010m].

Standard Type: N/A

Organization: The National Institute for Occupational Safety & 

Health (NIOSH)

Classification: Operational guidelines

Patient Flow Management Description: Plans that identify and mitigate impediments to 

efficient patient flow throughout the hospital [JCAHOSTD 

2010].

Standard Type: LD.3.15

Organization: The Joint Commission Resources 

Classification: Operational guidelines

Population Monitoring in Radiation 

Emergencies: A Guide for State and 

Local Public Health Planners

Description: This planners’ guide presents an introduction to 

population monitoring in radiation emergencies for public health 

officials and emergency preparedness planners at the state and 

local levels. It describes how to plan for population monitoring 

and provides practical suggestions to address the many 

challenges it presents when a large population is potentially 

impacted. Population monitoring is the process of identifying, 

screening, and monitoring people for exposure to radiation or 

contamination from radioactive materials [CDC 2010o].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Preparing for a Terrorist Bombing: Description: This document focuses on common sense 
28

A Common Sense Approach principles that will be useful in a bombing event [CDC 2010p].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Public Health Response to Biological 

& Chemical Terrorism: Interim 

Planning Guidance for State Public 

Health Officials

Description: This Planning Guidance is designed to help state 

public health officials determine the roles of their departments in 

response to biological and chemical terrorism and to understand 

the emergency response roles of local health departments and 

the emergency management system. The Planning Guidance 

also can be used to help state health departments coordinate their 

efforts with the many agencies and organizations at all levels of 

government that ultimately would respond to a biological or 

chemical terrorism event [CDC 2010q].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Recognition of Illness Associated 

with the Intentional Release of a 

Biologic Agent

Description: The guidance provides healthcare providers & 

public health personnel for recognizing illnesses or patterns of 

illness that might be associated with intentional release of 

biologic agents [CDC 2010r].

Standard Type: MMWR 2001

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Roundtable on Population 

Monitoring Following a 

Nuclear/Radiological Incident

Description: Recommendations & comments from participants 

in CDC’s roundtable (Jan. 11-12, 2005) on challenges associated 

with monitoring people affected by a nuclear or radiological 

incident [CDC 2010s].

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Sheltering in Place during a 

Radiation Emergency

Description: A fact sheet, prepared by the Centers for Disease 

Control and Prevention, used during a radiation emergency to 

help protect individuals and family and to help prepare a safe 

and well-stocked shelter from exposure to radiation [CDC 

2010t]. 

Standard Type: N/A

Organization: The Centers for Disease Control and Prevention 

(CDC)

Classification: Operational guidelines

Standard for Competence of Description: The standard identifies the minimum levels of 
29

Responders to Hazardous 

Materials/Weapons of Mass 

Destruction Incidents

competence required by responders to emergencies involving 

hazardous materials/weapons of mass destruction (WMD). It is 

based on the operational philosophies that emergency 

responders should be trained to perform their expected tasks, 

and that a responder cannot safely and effectively respond to a 

terrorism or criminal scenario involving hazmats/WMD if they 

don’t first understand basic hazardous materials response 

[NFPA 2010].

Standard Type: NFPA 472-2008

Organization: The National Fire Protection Association 

(NFPA)

Classification: Operational guidelines

Standard for Competencies for EMS 

Personnel Responding to Hazardous 

Materials/Weapons of Mass 

Destruction Incidents 

Description: The standard includes qualifications for EMS 

responders to terrorism incidents that involve hazardous 

materials. It identifies the levels of competence required of 

emergency medical services (EMS) personnel who respond to 

hazardous materials incidents. It specifically covers the 

requirements for Basic Life Support (BLS) and Advanced Life 

Support (ALS) personnel in the pre-hospital setting [NFPA 

2010]. 

Standard Type: NFPA 473-2008

Organization: The National Fire Protection Association 

(NFPA)

Classification: Operational guidelines

Standard Guide for Assessing the 

Health Hazard of Pesticides to 

Applicators and Others with 

Potential Exposure

Description: This guide covers a stepwise process for using 

information concerning biological, chemical, physical, and 

toxicological properties of a pesticide or other chemical(s), or of 

a formulation to identify adverse effects that may occur to 

pesticide applicators or others with potential exposure [ASTM 

2011].

Standard Type: E1429 – 91(2004)

Organization: ASTM International

Classification: Operational Guideline

Standard Guide for Hospital 

Preparedness and Response

Description: A guide intended to assist the leaders of hospitals 

in the design, planning, and response to be undertaken by 

hospitals and health care organizations to an event that 

necessitates the activation of an emergency operations plan 

[ASTM 2011].

Standard Type: ASTM E2413 – 04 (2009)

Organization: ASTM International

Classification: Operational guidelines

Standard Practice for Radiological 

Emergency Response 

Description: This practice provides decision-making 

considerations for response to incidents that involve radioactive 

materials. It provides information and guidance for what to 

include in response planning, and what activities to conduct 

during a response. It should be used in emergency services 
30

response such as law enforcement, fire department, and 

emergency medical response actions. This practice assumes that 

implementation begins with the recognition of a radiological 

incident and ends when emergency response actions cease or the 

response is assumed by specialized regional, state, or federal 

response teams [ASTM 2011].

Standard Type: ASTM E2601-08

Organization: ASTM International

Classification: Operational guidelines

6.3.3. Conceptual Modeling Standards

Standard Title Overview

Discrete Event System Specification 

(DEVS) 

Description: DEVS is a systems-theoretic approach to 

modeling. More specifically, it is state-centered formalism. A 

system consists of interconnected subsystems. A subsystem is a 

system. Leaf systems (atomic DEVSes) are state machines. 

DEVS can be viewed as a framework unifying a number of 

other formalisms in a consistent, systems theoretic, state 

centered fashion [DEVS 2011].

Standard Type: Specification

Organization: Simulation Interoperability Standards 

Organization (SISO); Society for Modeling and Computer 

Simulation International (SCS)

Classification: Domain-specific integration interface

Systems Modeling Language 

(SysML)

Description: SysML is a general purpose modeling language for 

systems engineering applications. It is a dialect of UML, the 

industry standard for modeling software-intensive systems. It 

supports the specification, analysis, design, verification and 

validation of a broad range of systems and systems-of-systems. 

These systems may include hardware, software, information, 

processes, personnel, and facilities [OMG 2011]. 

Standard Type: SysML 1.2

Organization: Object Management Group, Inc. (OMG)

Classification: Document format

Unified Modeling Language (UML) Description: A graphical language for visualizing, specifying, 

constructing and documenting the artifacts of a softwareintensive system. The UML offers a standard way to write a 

system’s blueprints, including conceptual things such as 

business processes and system functions, as well as concrete 

things such as programming language statements, database 

schemas, and reusable software components [ANSI 2011c]. 

Standard Type: UML 2.0, UML 2.1.1; UML 2.1.2; UML 2.2; 

UML 2.3; ISO/IEC 19501:2004

Organization: ISO; ANSI; Object Management Group, Inc. 

(OMG)
31

Classification: Document format

6.3.4. Distributed Simulation Standards

Standard Title Overview

Distributed Interactive Simulation Description: Distributed Interactive Simulation (DIS) is a 

government/industry initiative to define an infrastructure for 

linking simulations of various types at multiple locations to 

create realistic, complex, virtual worlds for the simulation of 

highly interactive activities. A series of IEEE standards to 

support information exchange between simulation applications 

participating in the DIS environment are defined. IEEE Std 

1278.1 defines the format and semantics of data messages, also 

known as Protocol Data Units (PDUs), that are exchanged 

between simulation applications and simulation management. 

IEEE Std 1278.2 defines the communication services required to 

support the message exchange described in IEEE Std 1278.1. 

IEEE 1278-3 provides guidelines for establishing a DIS 

exercise, managing the exercise, and providing proper feedback. 

IEEE 1278-4 establishes guidelines for the verification, 

validation, and accreditation (VV&A) of Distributed Interactive

Simulation (DIS) exercises [IHS 2011a].

Standard Type: IEEE 1278-1993, IEEE 1278.1-1995, IEEE 

1278.1A-1998, IEEE-1278.2-1995, IEEE 1278.3-1996, IEEE 

1278.4-1997

Organization: IEEE; IHS, Inc.

Classification: Domain-specific integration interface

Extensible Modeling and Simulation 

Framework (XMSF) 

Description: The Extensible Modeling and Simulation 

Framework (XMSF) is defined as a set of Web-based 

technologies and services, applied within an extensible 

framework, that enables a new generation of modeling & 

simulation (M&S) applications to emerge, develop and 

interoperate [DODCCRP 2011]. XMSF provides a framework 

which allows both Department of Defense (DoD) and non-DoD 

Modeling and Simulation (M&S) projects to take advantage of 

Web-based technologies.

Standard Type: XMSF 1.0

Organization: Naval Postgraduate School MOVES Institute; 

George Mason University NetLab; Science Applications 

International Corporation; Old Dominion University

Classification: Domain-specific integration interface

High Level Architecture (HLA) Description: This standard defines the HLA, its components, 

and the rules that outline the responsibilities of HLA federates 

and federations to ensure a consistent implementation [IEEE 

2011c].

Standard Type: IEEE 1516-2000, IEEE 1516.1-2000, 1516.2-
32

2000, ANSI/IEEE 1516.3-2003; IEEE 1516.4-2007

Organization: IEEE/Simulation Interoperability Standards 

Organization (SISO); ANSI

Classification: Domain-specific integration interface

6.3.5. Selected Geographic Information System (GIS) Standards

Standard Title Overview

CityGML – Exchange and Storage of 

Virtual 3D City Models

Description: A standard for the representation, storage, and 

exchange of virtual 3D city and landscape models. CityGML is 

implemented as an application schema of the Geography 

Markup Language version 3.1.1. It is based on a rich, general 

purpose information model in additional to geometry and 

appearance information. For specific domain areas, CityGML 

also provides an extension mechanism to enrich the data with 

identifiable features under preservation of semantic 

interoperability [OGC 2011a].

Standard Type: OGC 06-057r1; ISO TC211

Organization: Open Geospatial Consortium, Inc. (OGC)

Classification: Domain-specific integration interface

American National Standard for 

Information Technology –

Geographical Information Systems –

Spatial Data Standard for Facilities, 

Infrastructure, and Environment 

(SDSFIE)

Description: This standard provides a means to model and 

categorize real-world geographic phenomena of interest to the 

Facilities, Infrastructure, and Environment (FIE) Domain(s) into 

a set of geographic data that can be represented in a spatial 

database and presented to a user in digital form. This SDSFIE 

standard is intended to provide the enterprise spatial database 

schema to support multiple FIE applications. This National 

Standard is applicable to the federal, state, county, and city 

agencies; private companies; and any other organizations that 

perform AM & FM functions for facilities and other types of 

infrastructure (such as roads, waterways, utility systems, etc,) 

and/or perform environmental compliance, restoration, and/or 

pollution prevention activities [ANSI 2011a]. 

Standard Type: ANSI INCITS 353-2006

Organization: American National Standards Institute (ANSI); 

International Committee for Information Technology Standards 

(INCITS)

Classification: Domain-specific integration interface

Content Standard for Digital 

Geospatial Metadata (CSDGM)

Description: The standard is often referred to as the FGDC 

Metadata Standard. The objectives of the standard are to 

provide a common set of terminology and definitions for the 

documentation of digital geospatial data. The standard 

establishes the names of data elements and compound elements 

(groups of data elements) to be used for these purposes, the 

definitions of these compound elements and data elements, and 

information about the values that are to be provided for the data 
33

elements [FGDC 2011a].

Standard Type: FGDC-STD-001-1998; FGDC-STD-001.1-

1999; FGDC-STD-001.2-2001

Organization: Federal Geographic Data Committee (FGDC)

Classification: Domain-specific integration interface

Content Standard for Digital 

Geospatial Metadata (CSDGM) –

Extensions for Remote Sensing 

Metadata

Description: The standard of Extensions for Remote Sensing 

Metadata standard provides a common terminology and set of 

definitions for documenting geospatial data obtained from 

remote sensing, within the framework of the FGDC Content 

Standard for Digital Geospatial Metadata (CSDGM) standard. 

The extensions provide a means to use standard FGDC content 

to describe geospatial data derived from remote sensing 

measurements. This standard is intended to support the 

collection and processing of geospatial metadata for data derived 

from remote sensing. It is intended to be used by all levels of 

government and the private sector [FGDC 2011b].

Standard Type: FGDC-STD-012-2002

Organization: The Federal Geographic Data Committee 

(FGDC)

Classification: Domain-specific integration interface

GeoAPI SWG Standard Description: The GeoAPI Standard Working Group (SWG) 

aims to create the GeoAPI 3.0 Standard, which will define a set 

of Java language interfaces along with an associated test suite, to 

provide a standardized, programming language level realization 

of some core Open Geospatial Consortium (OGC) 

specifications. These interfaces will facilitate the creation of 

accurate, coherent, interoperable, and verifiable implementations 

of those OGC standards [GEOAPI 2011].

Standard Type: OGC GeoAPI 3.0 SWG

Organization: OGC

Classification: Domain-specific integration interface

Geographic Information – Encoding Description: The standard specifies the requirements for 

defining encoding rules to be used for interchange of geographic 

data within the ISO 19100 series of International Standards [ISO 

2011b]. 

Standard Type: ISO 19118:2005

Organization: ISO

Classification: Domain-specific integration interface

Geographic Information – LocationBased services – Multimodal Routing 

and Navigation

Description: The standard specifies the data types and their 

associated operations for the implementation of multimodal 

location-based services for routing and navigation. It is designed 

to specify web services that may be made available to wireless 

devices through web-resident proxy applications, but is not 

limited to that environment [ISO 2011b].

Standard Type: ISO 19134:2007

Organization: ISO
34

Classification: Domain-specific integration interface

Geographic Information – Locationbased Services – Tracking and 

Navigation

Description: ISO 19133:2005 describes the data types, and 

operations associated with those types, for the implementation 

of tracking and navigation services. It is designed to specify web 

services that can be made available to wireless devices through 

web-resident proxy applications, but is not restricted to that 

environment [ISO 2011b].

Standard Type: ISO 19133:2005 

Organization: ISO

Classification: Domain-specific integration interface

Geographic Information – Portrayal Description: The standard defines a schema describing the 

portrayal of geographic information in a form understandable by 

humans. It includes the methodology for describing symbols and 

mapping of the schema to an application schema. It does not 

include standardization of cartographic symbols, and their 

geometric and functional description [ISO 2011b].

Standard Type: ISO 19117:2005 

Organization: ISO

Classification: Domain-specific integration interface

Geographic Information –

Procedures for Item Registration 

Description: ISO 19135:2005 specifies procedures to be 

followed in establishing, maintaining and publishing registers of 

unique, unambiguous and permanent identifiers, and meanings 

that are assigned to items of geographic information. In order to 

accomplish this purpose, ISO 19135:2005 specifies elements of 

information that are necessary to provide identification and 

meaning to the registered items and to manage the registration of 

these items [ISO 2011b].

Standard Type: INCITS/ISO/IEC 19135-2005 

Organization: ISO; International Committee for Information 

Technology Standards (INCITS); International Electrotechnical 

Commission (IEC)

Classification: Domain-specific integration interface

Geographic Information – Schema 

for Moving Features 

Description: The standard defines a method to describe the 

geometry of a feature that moves as a rigid body [ISO 2011b]. 

Standard Type: ISO 19141:2008 

Organization: ISO

Classification: Domain-specific integration interface

Geographic Information – Services Description: ISO 19119:2005 identifies and defines the 

architecture patterns for service interfaces used for geographic 

information, defines its relationship to the Open Systems 

Environment model, presents a geographic services taxonomy 

and a list of example geographic services placed in the services 

taxonomy. It also prescribes how to create a platform-neutral 

service specification, how to derive conformant platformspecific service specifications, and provides guidelines for the 
35

selection and specification of geographic services from both 

platform-neutral and platform-specific perspectives [ISO 

2011b].

Standard Type: INCITS/ISO 19119-2005

Organization: ISO; International Committee for Information 

Technology Standards (INCITS)

Classification: Domain-specific integration interface

Geographic Information – Simple 

Feature Access

Description: ISO 19125-1:2004 establishes a common 

architecture for geographic information and defines terms to use 

within the architecture. It also standardizes names and geometric 

definitions for Types for Geometry. INCITS/ISO 19125-2-2004 

specifies an Structured Query Language (SQL) schema that 

supports storage, retrieval, query and update of simple 

geospatial feature collections via the SQL Call Level Interface 

(SQL/CLI) and establishes an architecture for the 

implementation of feature tables. INCITS/ISO 19125-2-2004 

defines terms to use within the architecture of geographic 

information and defines a simple feature profile of ISO 19107. 

In addition, this part of ISO 19125:2004 describes a set of SQL 

Geometry Types together with SQL functions on those types. 

The Geometry Types and Functions described represent a profile 

of ISO 13249-3. INCITS/ISO 19125-2-2004 standardizes the 

names and geometric definitions of the SQL Types for 

Geometry and the names, signatures and geometric definitions 

of the SQL Functions for Geometry [ISO 2011b].

Standard Type : INCITS/ISO 19125-1-2004 ; INCITS/ISO 

19125-2-2004 

Organization: ISO; International Committee for Information 

Technology Standards (INCITS)

Classification: Domain-specific integration interface

Geographic Information Framework 

Data Standard

Description: The standard establishes common data 

requirements for the exchange of National Spatial Data 

Infrastructure (NSDI) framework data [FGDC 2011c].

Standard Type: FGDC-STD-014.0-2008; FGDC-STD-014.1-

2008; FGDC-STD-014.2-2008; FGDC-STD-014.3-2008; 

FGDC-STD-014.4-2008; FGDC-STD-014.5-2008; FGDC-STD014.6-2008; FGDC-STD-014.7-2008; FGDC-STD-014.7b2008; FGDC-STD-014.7c-2008; FGDC-STD-014.7d-2008; 

FGDC-STD-014.7e-2008

Organization: Federal Geographic Data Committee (FGDC)

Classification: Domain-specific integration interface

GeoTIFF Description: GeoTIFF is a metadata format, which provides 

geographic information to associate with the image data. 

GeoTIFF implements the geographic metadata formally, using 

compliant Tagged Image File (TIFF 6.0) tags and structures. 

“GeoTIFF” refers to TIFF files, which have geographic (or 

cartographic) data embedded as tags within the TIFF file. The 

geographic data can then be used to position the image in the 
36

correct location and geometry on the screen of a geographic 

information display [GEOTIFF 2011].

Standard Type: GeoTIFF/Revision 1.0

Organization: geotiff.osgeo.org

Classification : Document format

Governmental Unit and Other 

Geographic Area Boundaries

Description: A specification for establishing of content 

requirements for the collection and interchange of Government 

units and legal entity boundary data and for facilitating the 

maintenance and use of that information [FGDC 2010].

Standard Type: FGDC-STD-014.5-2008 

Organization: Federal Geographic Data Committee (FGDC)

Classification: Domain-specific Integration Interfaces

GRIdded Binary (GRIB) Description: Format specifications for representing 

meteorological, gridded-point data [WMO 2010a].

Standard Type: FM 92-IX Ext. GRIB; FM 92-VIII EXT. GRIB

Organization: World Meteorological Organization (WMO) 

Classification: Domain-specific Integration Interfaces

Homeland Security Mapping 

Standard – Point Symbology for 

Emergency Management

Description: The primary purpose of this standard is to 

establish a common set of symbols for use by mapmakers in 

support of emergency managers and first responders. It will 

allow users to rapidly interpret map data and to be able to 

disseminate consistent, usable information. This American 

National Standard is applicable to all organizations that create 

maps or otherwise display features for the Emergency 

Management or First Responder communities. It is limited at 

this time to support portrayal of point features that relate to the 

emergency management and hazard mapping disciplines [ANSI 

2011b].

Standard Type: ANSI INCITS 415-2006 

Organization: American National Standards Institute (ANSI); 

International Committee for Information Technology Standards 

(INCITS)

Classification: Domain-specific integration interface

OpenGIS Implementation 

Specification for Geographic 

Information – Simple Feature Access

Description: The OpenGIS Simple Features Interface Standard 

(SFS) provides a well-defined and common way for applications 

to store and access feature data in relational or object-relational 

databases, so that the data can be used to support other 

applications through a common feature model, data store, and 

information access interface. OpenGIS Simple Features are 

geospatial features described using vector data elements such as 

points, lines, and polygons [OGC 2011c].

Standard Type: OGC 06-103r4 Version 1.2.1, OGC 05-126 

Organization: Open Geospatial Consortium, Inc (OGC)

Classification: Domain-specific integration interface

Spatial Data Transfer Standard Description: The Spatial Data Transfer Standard (SDTS) base 
37

(SDTS) specification (Parts 1, 2, and 3) describes the underlying 

conceptual model and the detailed specifications for the content, 

structure, and format for exchange of spatial data. Additional 

parts (4, 5, 6, and potentially others) are added as profiles, each 

of which defines specific rules and formats for applying SDTS 

for the exchange of particular types of data [FGDC 2011d] 

Standard Type: FGDC-STD-002.1; FGDC-STD-002.5; FGDCSTD-002.6; FGDC-STD-002.7-2000

Organization: Federal Geographic Data Committee (FGDC)

Classification: Domain-specific integration interface

Standard for a U.S. National Grid 

(USNG)

Description: A standard is used to define the U.S. National Grid 

and supports Universal Transverse Mercator (UTM) 

coordinates, Military Grid Reference System (MGRS) grids, and 

the specific grid presentation requirements. It is used for 

acquisition/production of printed map and acquisition of 

location service appliances with printed map products [FGDC 

2011e]

Standard Type: FGDC-STD-011-2001

Organization: Federal Geographic Data Committee (FGDC)

Classification: Domain-specific integration interface

6.3.6. Selected Communication Standards

Standard Title Overview

Common Alerting Protocol (CAP) Description: The Common Alerting Protocol (CAP) is a simple, 

flexible data interchange format for collecting and distributing 

“all-hazard” safety notifications and emergency warnings over 

information networks and public alerting systems. In Webservices applications, CAP provides a lightweight standard for 

exchanging urgent notifications. CAP can also be used in databroadcast applications and over legacy data networks. CAP is 

fully compatible with the existing national broadcast Emergency 

Alert System (EAS) [OASIS 2011a]. It is an XML-related data 

interchange standard for alerting and event notification 

applications. The standard supports two functions: a standalone 

protocol and a payload for Emergency Data Exchange Language 

(EDXL) messages.

Standard Type: CAP-V1.1

Organization: Organization for the Advancement of Structured 

Information Standards (OASIS)

Classification: Domain-specific integration interface

Common Incident Management 

Message Sets for use by Emergency 

Management Centers 

Description: This standard is the Base Standard for a family of 

related standards that address the intercommunication needs of 

emergency management centers and other types of centers 

engaged in transportation incident management [IEEE 2010].

Standard Type: IEEE 1512-2000, IEEE 1512.1, IEEE 1512.2, 
38

IEEE 1512.3

Organization: Institute of Electrical and Electronics Engineers 

(IEEE)

Classification: Document Format

Emergency Data Exchange 

Language (EDXL)

Description: Several organizations are collaborating on the 

design and development of a suite of specifications under the 

name “Emergency Data Exchange Language (EDXL)” [OASIS 

2011b]. EDXL is an integrated framework for a wide range of 

emergency data exchange standards to support operations, 

logistics, planning, and finance.

Standard Type: EXDL Distribution Element, V. 1.0 (EDXLDE-V1.0); EDXL Resource Message Specification 1.0 Working 

Draft Version 26 (EDXL-RM 1.0 v0026); EDXL Hospital 

Availability Exchange v1.0 Public Review Draft 02 (EDXLHAVE-1.0-spec-pr02)

Organization: Organization for the Advancement of Structured 

Information Standards (OASIS); Department of Homeland 

Security (DHS); Emergency Interoperability Consortium (EIC)

Classification: Domain-specific integration interface

National Information Exchange 

Model (NIEM)

Description: NIEM is designed to develop, disseminate, and 

support enterprise-wide information exchange standards and 

processes that can enable jurisdictions to effectively share 

critical information in emergency situations, as well as support 

the day-to-day operations of agencies throughout the nation 

[NIEM 2011].

Organization: A partnership of the U.S. Department of Justice, 

the U.S. Department of Homeland Security, and the U.S. 

Department of Health and Human Services.

Classification: Domain-specific integration interface

6.4. Data Sources

This section identifies databases and other sources of data that may be used to develop or run healthcare 

models and simulations. The name of data source, a brief description of its contents, its access location, 

responsible organization, data formats used, as well as classification of the type of data is given below.

Data Source Title Overview

Ambulatory Health Care Data Description: The National Ambulatory Medical Care Survey 

(NAMCS) is a national survey designed to meet the need for 

objective, reliable information about the provision and use of 

ambulatory medical care services in the United States. Findings 

are based on a sample of visits to non-federal employed officebased physicians who are primarily engaged in direct patient 

care. The National Hospital Ambulatory Medical Care Survey 

(NHAMCS) is designed to collect data on the utilization and 

provision of ambulatory care services in hospital emergency and 
39

outpatient departments. Findings are based on a national sample 

of visits to the emergency departments and outpatient 

departments of non-institutional general and short-stay hospitals 

[CDC 2010y].

Data Source: NAMCS/NHAMCS

Organization: National Center for Health Statistics (NCHS) of 

the Centers for Disease Control and Prevention (CDC)

Format: Report

Classification: Demographic and Behavior, Resources

American Hospital Association 

(AHA) Database

Description: American Hospital Association (AHA) Database 

contains data for every hospital in the U.S. The data is collected 

from AHA annually survey. Non-responding hospital data are 

estimated using advanced methods to approximate specific data 

elements. Multiple data sets power this database, including the 

latest edition of the AHA Annual Survey of Hospitals, primary 

research into the organizational structures of Systems and 

Networks conducted by Health Forum, and information from 

Health Forum subscriber lists [AHADATA 2010a].

Data Source: American Hospital Association (AHA) Database. 

Five tools are provided: Hospital Statistics Wizard; Hospital 

Market Analysis Wizard; Health Care Systems and Networks 

Wizard; Hospital Detail Report Wizard; Mailing List Wizard

Organization: American Hospital Association (AHA)

Format Used: PDF, Excel table, Chart

Classification: Resources, Demographic and Behavior

American Housing Survey (AHS) Description: The American Housing Survey (AHS) collects data 

on the Nation’s housing, including apartments, single-family 

homes, mobile homes, vacant housing units, household 

characteristics, income, housing and neighborhood quality, 

housing costs, equipment and fuels, size of housing unit, and 

recent movers. National data are collected in odd numbered 

years, and data for each of 47 selected Metropolitan Areas are 

collected currently about every six years. The national sample 

covers an average 55,000 housing units. Each metropolitan area 

sample covers 4,100 or more housing units. The Data Access 

includes three categories: National Data, Metropolitan Data, and 

Dates metropolitan Areas are Survey [CENSUS 2010]. 

Data Source: AHS Data Access

Organization: U.S. Census Bureau (USCS)

Format Used: Excel; PDF

Classification: Demographic and Behavioral

Behavioral Risk Factor Surveillance 

System (BRFSS)

Description: The Behavioral Risk Factor Surveillance System 

(BRFSS) is a state-based system of health surveys that collects 

information on health risk behaviors, preventive health practices, 

and health care access primarily related to chronic disease and 

injury. For many states, the BRFSS is the only available source of 

timely, accurate data on health-related behaviors [CDC 2010u].

Data Source: BRFSS Maps, BRFSS GIS Data, BRFSS Datasets
40

Organization: Centers for Disease Control and Prevention, 

National Center for Chronic Disease Prevention and Health 

Promotion/Division of Adult and Community Health

Format: SHP, RTF, SAS, XPT, PDF, TXT, CSV, SAS7BCAT, 

SAS7BDAT, ZIP

Classification: Demographic and Behavior, Controlling 

Documents, Incidents

CDC Wide-ranging Online Data for 

Epidemiologic Research 

(WONDER)

Description: The Centers for Disease Control and Prevention 

(CDC) WONDER – Wide-ranging Online Data for 

Epidemiologic Research – is an integrated information and 

communication system for public health. It speeds and simplifies 

access to public health information for state and local health 

departments, the public health service, and the academic public 

health community. CDC WONDER allows accessing statistical 

research data and reports published by CDC and querying 

numeric data sets on CDC’s computers [CDC 2010w]. 

Data Source: WONDER Online Databases

Organization: The Centers for Disease Control and Prevention 

(CDC)

Format: HTML, chart and map images (bitmaps), ASCII, 

spreadsheet 

Classification: Resources, Controlling Documents, Demographic 

and Behavioral

CDC.gov Widgets and Gadgets Description: CDC.gov provides content in several useful ways, 

via our e-mail updates, podcasts and RSS feeds. Our newest 

features are the Flu Updates, Emergency Text Messages and the 

CDC Data and Statistics Widget. Widgets are online applications 

built by one Web site that can be displayed onto another Web 

site. A widget is a CDC.gov application that displays the featured 

content directly on your web page. You can embed content in 

personalized home pages, blogs, and other sites. Once you’ve 

added the widget, there’s no technical maintenance. CDC.gov 

will update the content automatically. Available widgets include 

Adult BMI Calculator, H1N1 (Swine Flu), Fraudulent H1N1 

Products, H1N1 School Guidance, Pet Health and Safety, Public 

Health Image Library Image of the Day, Five Minutes or Less for 

Health, Smoking and Tobacco Use, Flu IQ, Seasonal Flu 

Updates, National Environmental Public Health Tracking 

Program, CDC Text Messages, etc. [CDC 2010v].

Data Source: CDC.gov

Organization: Centers for Disease Control and Prevention

Format: TXT, RSS

Classification: Incidents, Demographic and Behavior, 

Environment, Controlling Document

Clinical Data Repository (CDR) Description: The Clinical Center installed a hospital-wide, realtime computerized medical information system (MIS) in 1976. 

This system supports the Clinical Center’s dual responsibilities of 

providing quality patient care and collecting research data. The 
41

Clinical Data Repository (CDR) is a new facility that will house 

all electronic data collected at the clinical center from the time 

MIS was installed (1975) until today. The CDR will be 

continually updated with current data and will be the single place 

to find information for clinical, research, and administrative use 

[NIH 2010a]. 

Data Source: CDR Version 1.4, CCMIS (Mac/MIS, Web/MIS 

3.0)

Organization: National Institute of health (NIH)

Format: Clinical Data Repository (CDR)

Classification: Demographic and Behavior

Directory of Information Resources 

Online (DIRLINE)

Description: DIRLINE (Directory of Information Resources 

Online) is the National Library of Medicine’s online database 

containing location and descriptive information about a wide 

variety of information resources including organizations, research 

resources, projects, and databases concerned with health and 

biomedicine. DIRLINE contains over 8,500 records and focuses 

primarily on health and biomedicine, although it also provides 

limited coverage of some other special interests. These 

information resources fall into many categories including federal, 

state, and local government agencies; information and referral 

centers; professional societies; self-help groups and voluntary 

associations; academic and research institutions and their 

programs; information systems and research facilities. Topics 

include HIV/AIDS, maternal and child health, most diseases and 

conditions including genetic and other rare diseases, health 

services research and technology assessment. Each record may 

contain information on the publications, holdings, and services 

provided [NIH 2010b].

Data Source: DIRLINE 

Organization: The National Library of Medicine (NLM)

Format: Report

Classification: Resources, Controlling Documents

Drug Information Portal Description: The Drug Information Portal, a free web resource, 

provides an informative, user–friendly portal to current drug 

information for over 15,000 drugs. Links to sources span the 

breadth of the National Library of Medicine (NLM), the National 

Institutes of Health (NIH) and other government agencies. 

Current information regarding consumer health, clinical trials, 

AIDS–related drug information, MeSH pharmacological actions, 

PubMed biomedical literature, and physical properties and 

structure can be retrieved by searching on a drug name. A varied 

selection of focused topics in medicine and drug–related 

information is also available from displayed subject headings 

[NIH 2010c].

Data Source: Drug Information Portal

Organization: The National Library of Medicine (NLM)

Format: Report

Classification: Resources, Controlling Document
42

FedStats Description: FedStats provides access to the full range of official 

statistical information produced by the Federal Government 

without having to know in advance which Federal agency 

produces which particular statistic. With convenient searching 

and linking capabilities to more than 100 agencies that provide 

data and trend information on such topics as economic and 

population trends, crime, education, health care, aviation safety, 

energy use, and farm production [FEDSTATS 2010].

Data Source: www.fedstats.gov

Organization: The Federal Interagency Council on Statistical 

Policy

Format: HTML, spreadsheets

Classification: Resources, Demographic and Behavior, 

Environment, Controlling Documents

Haz-Map Description: Haz-Map is an occupational health database 

designed for health and safety professionals and for consumers 

seeking information about the health effects of exposure to 

chemicals and biological agents at work. Haz-Map links jobs and 

hazardous tasks with occupational diseases and their symptoms. 

It is one of the products and services made available by the 

National Library of Medicine’s (NLM) Toxicology and 

Environmental Health Information Program. Haz-Map includes 

three categories: hazardous agents, occupational diseases, and 

high risk jobs [NIH 2010d]. 

Data Source: Haz-Map

Organization: The National Library of Medicine (NLM)

Format: Report

Classification: Demographic and Behavior, Environment, 

Controlling Documents

Healthcare Cost and Utilization 

Project (HCUP) Databases

Description: Healthcare Cost and Utilization Project (HCUP) 

databases bring together the data collection efforts of State data 

organizations, hospital associations, private data organizations, 

and the Federal government to create a national information 

resource of patient-level health care data (HCUP Partners). 

HCUP includes the largest collection of longitudinal hospital care 

data in the United States, with all-payer, encounter-level 

information beginning in 1988. These databases enable research 

on a broad range of health policy issues, including cost and 

quality of health services, medical practice patterns, access to 

health care programs, and outcomes of treatments at the national, 

State, and local market levels [AHRQ 2010b].

Data Source: Nationwide Inpatient Sample (NIS), Kids’ 

Inpatient Database (KID) , Nationwide Emergency Department 

Sample (NEDS), State Inpatient Databases (SID), State 

Ambulatory Surgery Databases (SASD), and State Emergency 

Department Databases (SEDD)

Organization: The Agency for Healthcare Research and Quality 

(AHRQ)
43

Format: PDF, HTML

Classification: Demographic and Behavior, Resources, 

Controlling Documents

Healthy People 2010 Database Description: DATA2010 is an information system developed by 

staff of the division of Health Promotion Statistics of the National 

Center for Health Statistics, CDC, and contains the most recent 

monitoring data for tracking Healthy People 2010. With this 

system, world-wide users have the ability to view the data 

collected to track Healthy People 2010 objectives, with national 

baseline and monitoring data for each Healthy People 2010 

objective. Users can select data options to create and browse realtime tables and graphs of the baseline and tracking year data for 

all 28 health focus areas, as well as the leading health indicators. 

This interactive system allows users to query an updated database 

and construct tables. Tables can be constructed for specific 

objectives, or objectives identified by focus areas, data source, or 

by select population [CDC 2010x]. 

Data Source: DATA2010

Organization: National Center for Health Statistics (NCHS) of 

the Centers for Disease Control and Prevention (CDC)

Format: Table and Graph

Classification: Controlling Documents, Demographic and 

Behavior

Hospital Compare Description: Hospital Compare is used to find information on 

how well hospitals care for patients with certain medical 

conditions or surgical procedures, and results from a survey of 

patients about the quality of care they receives during a recent 

hospital stay. The data provided includes process of care, 

mortality, and readmission quality measures. The collection 

period for the measures is generally 12 months. However, some 

measures may be based upon fewer than 12 months. Generally, 

the Hospital Compare quality measures are refreshed the third 

month of each quarter [CMS 2010].

Data Source: Medicare Hospital Compare

Organization: Centers for Medicare and Medicaid Services 

(CMS) of Department of Health and Human Services, Hospital 

Quality Alliance

Format: CSV, dbf

Classification: Resources, Controlling Documents

Hospital Electronic Health Records 

(HER) Adoption Database

Description: The Hospital HER Adoption Database 2010 is 

based on a survey of U.S. hospitals tracking the adoption of 

electronic health records (HER), also known as electronic 

medical records (EMR). The data included are hospital specific. 

The database is used to determine where hospitals are along the 

technology adoption curve regarding electronic clinical 

documentation, results viewing, computerized provider order 

entry, decision support, and bar coding; find out where these 

functions are implemented in the hospital: emergency 
44

department, ICU, general medical/surgical, specialty, onsite 

ambulatory practices, and offsite ambulatory practices; and 

understand the capabilities of hospital’s electronic systems 

[AHADATA 2010b]. 

Data Source: Database

Organization: American Hospital Association (AHA)

Format: PDF, Microsoft Excel file

Classification: Demographic and Behavior, Resources, 

Controlling Documents

National Emergency Medical 

Services (EMS) Information System 

(NEMSIS)

Description: The Hazardous Substances Emergency Events 

Surveillance (HSEES) system was established to collect and 

analyze information about acute releases of hazardous substances 

and threatened releases that result in a public health action such 

as an evacuation. The goal of HSEES is to reduce the morbidity 

(injury) and mortality (death) that result from hazardous 

substances events, which are experienced by first responders, 

employees, and the general public. The HSEES system data and 

prevention outreach are critical for identifying, preventing, and 

mitigating the consequences of terrorist threats against our 

chemical infrastructure. Fourteen state health departments 

currently have cooperative agreements with ATSDR to 

participate in HSEES: Colorado, Florida, Iowa, Louisiana, 

Michigan, Minnesota, New Jersey, New York, North Carolina, 

Oregon, Texas, Utah, Washington, and Wisconsin [NEMSIS

2010].

Data Source: NEMSIS NHTSA Dataset Version 3

Organization: National Highway Traffic Safety Administration 

(NHTSA); Health Resources and Services Administration 

(HRSA); CDC; University of Utah; University of North Carolina

Format Used: XSD

Classification: Demographic and Behavioral

National Incident Management 

System – Incident Resource 

Inventory System (NIMS-IRIS)

Description: National Incident Management System – Incident 

Resource Inventory System (NIMS-IRIS) is a database 

management tool that allows emergency responders to enter 

typed resources and select specific resources for mutual aid 

purposes based upon mission requirements, capability of 

resources, and response time. NIMS-IRIS tracks equipment, 

communications, contracts, facilities, responders, services, 

supplies, and teams [FEMA 2010]. 

Data Source: NIMS-IRIS Version 2.2

Organization: Federal Emergency Management Agency 

(FEMA)

Format: EDXL

Classification: Resources

Rand Public Health Preparedness 

Database

Description: The Rand Corporation database, funded by the U.S.

Department of Health and Human Services, provides access to 

numerous public health preparedness exercises. It is primarily 

intended for state and local public health officials. The database 
45

provides a list of possible exercises performed along with criteria 

rating the success of each exercise. There are fourteen design 

criteria used to rate each exercise. These criteria are: 1) clearly 

stated goals; 2) clearly stated objectives; 3) the objectives are 

appropriate given the goals; 4) each objective is addressed during 

the exercise; 5) objectives are measurable; 6) the scenario is 

appropriate given the goals and objectives; 7) the scenario is 

internally consistent; 8) scenario is “a realistic depiction of the 

capabilities and resources likely to be available to a participating 

health jurisdiction;” 9) clear guidance about participants; 10) all 

participants are engaged; 11) exercise can be replicated; 12) 

results in action items; 13) feedback is solicited from participants; 

14) can be completed within the given timeframe. The goal of 

this database is “to identify the best exercises to help local and 

state public health departments prepare for public health 

emergencies.” [RAND 2010]

Data Source: Rand Public Health Preparedness Exercise 

Database

Organization: RAND Corporation, Department of Health and 

Human Services (HHS)

Format: 

Classification: Training, Resources

Risk Group Database for Risk 

Group Classification for Infectious 

Agents

Description: In many countries, including the United States, 

infectious agents are categorized in risk groups based on their 

relative risk. Depending on the country and/or organization, this 

classification system might take the following factors into 

consideration: pathogenicity of the organism, mode of 

transmission and host range, availability of effective preventive 

measures (e.g., vaccines), availability of effective treatment (e.g., 

antibiotics), and other factors. The Risk group classifications 

used in the Risk Group Database are primarily used in the 

research environment as part of a comprehensive bio-safety risk 

assessment. The Risk Group database provides four search 

engines: search bacteria, search virus, search fungi, and search 

parasites [ABSA 2010]. 

Data Source: ABSA Risk Group Database

Organization: American Biological Safety Association (ABSA)

Format: 

Classification: Controlling Documents, Demographic and 

Behavior

The Emergency Response Safety 

and Health Database

Description: The Emergency Response Safety and Health 

Database is a rapidly accessible occupational safety and health 

database developed by NIOSH for the emergency response 

community. The ERSH-DB contains accurate and concise 

information on high-priority chemical, biological and radiological 

agents that could be encountered by personnel responding to a 

terrorist event. The information contained in the ERSH-DB 

represents a compilation of material from a diverse array of 

sources, and is intended to address the safety and health 
46

information needs of a wide range of emergency response 

personnel, including, but not limited to, the fields of fire and 

rescue, emergency medicine, law enforcement, emergency 

management, public health, safety and health, and mortuary and 

funeral. As a central source of information, the ERSH-DB allows 

diverse segments of the emergency response community to share 

a wealth of information that is not readily accessible and to avoid 

duplication of effort [CDC 2010aa].

Data Source: ERSH-DB

Organization: The Centers for Disease Control and Prevention 

(CDC); The National Institute of Occupational Safety & Health 

(NIOSH)

Format Used: text, table

Classification: Controlling Documents

TheDataWeb Browser Description: TheDataWeb is a network of online data libraries 

that the DataFerrett accesses the data through. DataFerrett is a 

unique data analysis and extraction tool—with recoding 

capabilities—to customize federal, state, and local data to suit the 

user’s requirements. (FERRETT stands for Federated Electronic 

Research, Review, Extraction, and Tabulation Tool.) Data topics 

of TheDataWeb include census data, economic data, health data, 

income and unemployment data, population data, labor data, 

cancer data, crime and transportation data, family dynamics, vital 

statistics data, etc. [THEDATAWEB 2010]

Data Source: BetaDataFerrett

Organization: U.S. Census Bureau

Format: XML/CAP 1.1, ATOM, RSS

Classification: Controlling Documents, Demographic and 

Behavior, Resources

TOXicology Data NETwork 

(TOXNET)

Description: TOXNET (TOXicology Data NETwork) is a cluster 

of databases covering toxicology, hazardous chemicals, 

environmental health and related areas. It is managed by the 

Toxicology and Environmental Health Information Program 

(TEHIP) in the Division of Specialized Information Services 

(SIS) of the National Library of Medicine (NLM). Toxicology 

databases include Hazardous Substances Data Bank (HSDB), 

Integrated Risk Information System (IRIS), International Toxicity 

Estimates for Risk (ITER), Chemical Carcinogenesis Research 

Information System (CCRIS), Genetic Toxicology (GENETOX), Toxicology interactive guide (Tox Town), Household 

Products Database, Occupational Toxicology Database (HazMap), toxic chemicals released on map (TOXMAP), Drugs and 

Lactation (LacMed), and Carcinogenic Potency Database 

(CPDB) [NIH 2010e].

Data Source: TOXNET

Organization: The National Library of Medicine (NLM)

Format: Report, XML

Classification: Controlling Documents, Demographic and 

Behavior, Environment
47

Weapons of Mass Destruction 

(WMD), Emergency Management 

and Medical Websites 

Description: A comprehensive list of internet sites of use for 

emergency planning and in particular Weapons of Mass 

Destruction (WMD) and medical emergency planning [YNHHS 

2010]. 

Data Source: Yale New Haven Center for Emergency 

Preparedness and Disaster Response Yale New Haven Health 

System

Organization: Yale New Haven Health System

Format Used: N/A

Classification: Controlling Documents 

Web-based Injury Statistics Query 

and Reporting System (WISQARS)

Description: The Web-based Injury Statistics Query and 

Reporting System (WISQARS) is an interactive database system 

that provides customized reports of injury-related data. The 

database includes fatal injury data (from the National Vital 

Statistics System), nonfatal injury data (from the National 

Electronic Injury Surveillance System), and violent deaths (from 

the National Violent Death Reporting System (NVDRS) [CDC 

2010z]. 

Data Source: WISQARS 

Organization: Centers for Disease Control and Prevention 

(CDC)

Format: CSV

Classification: Incidents

7. Discussions and Recommendations

This section is intended to capture practices and issues relevant to program sponsors, project managers, 

researchers, developers, and implementers of M&S of healthcare systems for homeland security 

applications. The resources presented in section 6 and research, development and implementation 

experiences are used to identify the best practices to be followed for future efforts and to provide 

uncertainties, cautions and warnings for use of such applications. Further, the resources in section 6 are 

compared with the information in sections 4 and 5 to identify the unmet needs and requirements. These 

unmet needs and requirements are used to identify and prioritize the research, development, standards, 

and implementation issues that should be addressed going forward. This section hence provides a 

summary of discussion topics and recommendations that are divided into three major areas: 

• Identification of best practices (Section 7.1)

• Uncertainties, cautions and warnings regarding expectations of these models and simulations (Section 

7.2)

• Research, development, standards and implementation issues that may need to be addressed by the 

research community, program sponsors, and stakeholders to improve the quality and utility of 

incident management models and simulations (Section 7.3)

7.1. Best Practices
48

Best practices are really only effective if a methodology is well defined for a given problem solving 

approach. For example, the LUMAS model shows how learning influences a documented methodology, 

and the link between L and M in the LUMAS model is where best practice is encountered by the user of a 

methodology. Computer models and simulations are tools in a variety of problem solving methodologies 

such as operations research, systems engineering, and management science, where methodology is 

defined as a collection of related processes, methods, and tools. Methodologies evolve as they are used 

by practitioners to address new problems and as new technologies and tools are developed to support 

them. Methodological advances are encouraged by documenting existing methods, processes and tools 

and by updating these periodically based on lessons learned and best practice from practical experience. 

This section will identify recommended approaches and best practices for solving different types of 

hazardous material release modeling problems.

A variety of M&S approaches, methodologies, and tools are currently available. Some are more suitable 

to solving certain classes of problems than others. This section will identify recommended approaches 

and best practices for solving different types of healthcare modeling problems.

• Provide tools that can be used at the local level for healthcare systems analysis, evaluation, or 

training purposes

• Use various test and validation methods

• Provide tools that do not require sophisticated and expensive system support

• Provide distributed web-based tools that allow health care organizations to develop and run custom 

exercises.

7.2. Uncertainties, Cautions and Warnings

This sub-section is intended to highlight and document the limitations associated with M&S applications 

to minimize improper use and highlight potential areas for further development. M&S application 

requires significant effort and hence they should be utilized only when appropriate, i.e., they should be 

considered for complex problems that cannot be addressed using other analytical options. The level of 

detail and specificity achieved by using the most sophisticated models and simulations may not be 

practical or necessary for all assets, systems, or networks. In these circumstances, a simplified 

dependency and interdependency analysis based on expert judgment may provide sufficient insight to 

make informed risk management decisions in a timely manner [DHS 2009].

For applications that are identified as suitable for M&S applications, it should be recognized that models 

provide results with varying levels of error and uncertainty. Analysts should ensure that decision-makers 

understand the uncertainties in M&S results and other limitations such as the ones listed below. Models 

provide results with varying levels of error and uncertainty. This sub-section is intended to highlight and 

document the limitations associated with M&S applications to minimize improper use and highlight 

potential areas for further development.

• Epidemic models are particularly susceptible to variations in predicted results due to difficulties in 

precisely modeling human behaviors and random occurrences of transmission of diseases. 

• Training exercises may not create the stress conditions and state of mind in the healthcare systems 

personnel that would occur during a real incident or epidemic.

• Data inconsistencies between simulated exercises and real incidents may affect the results and 

perceptions.

• Communication difficulties and incompatibilities between systems may not be accurately reflected in 

training exercises.
49

7.3. Research, Development, Standards, and Implementation Issues

A number of research, development, standards, and implementation issues remain to be addressed. An 

initial straw man list follows:

• Identification of appropriate models, simulations, tools, and databases to address healthcare system 

analysis and training needs

• Increasing reality in healthcare M&S training exercises and devices

• Identification of common models, simulations, tools, and databases that can be shared by the user 

community

• Identification of technical gaps and needs for models, simulations, tools, and databases

• Development of system requirements specifications for healthcare models, simulations, tools, and 

databases

• Development of systems dynamics models for addressing strategic issues for different healthcare 

systems and incident scenarios

• Development of mechanisms to enable access to and usage of healthcare M&S applications by the 

healthcare providers, partners, and emergency response personnel

• Development of simulation application architectures to enable module integration and standard data 

interfaces to import data from external databases

• Use of a system-of-systems engineering approach to the development of applications

• Use of UML/SysML in specification of healthcare systems and M&S applications

• Development of M&S applications as open systems

• Use of object-oriented models in healthcare M&S

• Integration of healthcare models and simulations

• Establishment of security and protection mechanisms for sensitive data

• Ownership and usage of publicly vs. privately developed models, simulations, tools, and databases

• Return on investment to stakeholders and sponsors for research projects

8. Conclusion

This initial version of the document is the starting point of an effort to capture the current knowledge 

relevant to M&S of healthcare for homeland security applications. It identifies the needs, translates them 

into requirements and provides summary information on resources available to meet the needs and 

requirements. The information on needs, requirements, and resources is used together with research, 

development, and implementation experiences to distill practices and issues for future efforts.

This version will be used to facilitate input from domain experts in a workshop setting. It is hoped that 

the next version updated with such input will provide value as a reference for program managers, project 

managers, researchers, developers, and implementers of M&S for healthcare for homeland security 

applications. Use of the updated document as a common reference may help increase the awareness

across the associated communities and help enhance collaborative efforts for homeland security 

applications of M&S for healthcare.

9. References

[AAI 2007] Healthcare Modeling Studio. Automation Associates Inc. Available via: 

http://www.blueminegroup.com/aai/pos_healthcare_modeling_studio.asp 
50

[accessed Jan. 3, 2011]

[ABSA 2010] Risk Group Classification for Infectious Agents. American Biological 

Safety Association (ABSA). Available via: 

http://www.absa.org/riskgroups/bacteria.html [Accessed Dec. 12, 2010]

[ADL 2011] Advanced Distributed Learning Sharable Content Object Reference Model 

(SCORM). Available via: 

http://www.adlnet.gov/Technologies/scorm/default.aspx [accessed Jan. 

10, 2011].

[AHADATA 2010a] Health Care Statistics and Market Research: AHA Data. American 

Hospital Association (AHA). Available via: 

http://www.ahadata.com/ahadata_app/index.jsp [Accessed Dec. 12, 2010]

[AHADATA 2010b] Hospital Electronic Health Records (HER) Adoption Database. American 

Hospital Association (AHA). Available via: 

http://www.ahadata.com/ahadata/html/EHRdatabase.html [Accessed Dec. 

12, 2010]

[AHRQ 2010a] Community-Based Mass Prophylaxis. Agency for Healthcare Research 

and Quality (AHRQ). Available via: 

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