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The Elements Of Public Health

Transforming The Public Health Information Infrastructure

Abstract

 
The public health information infrastructure is undergoing a transformation that is enabled by changes in health care informatics. The implementation of the Health Insurance Portability and Accountability Act (HIPAA) of 1996, the patient medical record information standards, and National Health Information Infrastructure (NHII) recommendations by the National Committee on Vital and Health Statistics provide the basis for improved data reporting to public health agencies. The U.S. Department of Health and Human Services should provide leadership and resources for this transformation. Newly available federal resources will have the greatest effect on improving the information infrastructure if there is a strong commitment to developing and implementing public health data standards that build upon the National Electronic Disease Surveillance System.

The PHII comprises an intricate web of data resources, information systems, epidemiological analysis, and investigation, standards, laws, and values that public health agencies at the local, state, and federal levels use to prevent illness and promote health. It is an integral part of the National Health Information Infrastructure (NHII), which we describe in greater detail below.

Looking at the birth of modern epidemiology gives the best insight into the role of the PHII. In 1854 cholera struck the Soho section of London. John Snow, a physician, conducted an investigation of this outbreak by carefully mapping the location of each of the victims. The mapping revealed a pattern centered on the public water pump on Broad Street. He then proceeded to convince local authorities to remove the handle from the pump, thereby stopping the spread of disease.²

The PHII exists to collect and analyze data, form and confirm hypotheses, and manage interventions. The PHII is independent of software and hardware systems. In fact, much of the current system operates using paper records, telephones, and manual analysis. This paper discusses the state of the PHII and what effect the ongoing transformation of health information management could have on its future.

Public Health Data Sources

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Medical data. Generally, public health data are derived in a number of ways. Medical data are collected on individuals in a clinical setting as part of each patient encounter. Clinical encounters generate data through obtaining past medical history, history of a present illness, and physical findings during an examination. The caregiver is frequently the recorder of that data. Other data are generated when laboratory tests, x-rays, and other clinical tests are ordered and performed. However, much filtering of these findings occurs because of the time costs of recording them. The written medical record contains only that information that the caregiver deems important enough to record. Reporting to the public health system is directed by various local, state, and federal laws. In most instances, data are abstracted from the clinical record as part of the reporting process. Often, the person making the report to public health authorities is not the caregiver.

The reporting of infectious diseases demonstrates the filtering that exists in many public health surveillance systems. Whereas reporting by laboratories tends to be generally complete, clinicians often do not recall that a diagnosis is reportable or are too busy to complete the forms. In 1998 an outbreak of invasive Group A streptococcus occurred in a small metropolitan area in central Illinois. Three months passed during which ten people died before the first case was reported to the public health authority. Invasive Group A streptococcus is just one of more than sixty reportable conditions in Illinois. Few clinicians remember most of them.

Environmental data. Environmental data are gathered through ongoing monitoring systems or as part of a special investigation. These measures range from communitywide measurements of ozone and other pollutants in the atmosphere to measurement of the lead content of paint on walls in individual homes. Birds are trapped and their blood tested for West Nile virus, St. Louis encephalitis, and other arbovirus-related diseases. Positive tests result in public notice and education to take steps to reduce mosquito bites. During an identified or suspected outbreak, focused collections of clinical, laboratory, and interview data are used to determine the extent of the outbreak and identify causative agents, to determine who is at risk and what direct interventions should be taken.

Survey data. Assessing the health of a community cannot be completed using only available clinical data and environmental measures. Data systems do not exist that describe the level of risk for chronic disease in a community, so the level of risk is approximated by the collection of survey data. Surveys are conducted through direct clinical examination (National Health and Nutrition Evaluation Survey, or NHANES), phone interviews (Behavioral Risk Factor Survey System, or BRFSS), and other approaches. Because of the high costs of these surveys, the sample size is too small in most communities to allow for meaningful analysis.

Public Health Analytic Tools

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The base science in public health practice is epidemiology. Epidemiology is defined as the study of the distribution and determinants of health-related states in specified populations and the application of this study to the control of health problems. Most epidemiological studies combine descriptive and analytical approaches. Descriptive studies are epidemiological studies in which data are collected to characterize and summarize a public health event or problem. The goal is to determine who is affected, where, and when. Analytical studies make comparisons between groups of people to determine how and why people are affected by collecting data from large numbers of people to make inferences about causation. To establish the cause-and-effect relationship, five criteria must be present: strength of association (the association must be clear), consistency (observation of the association must be repeatable in different populations at different times), temporality (the cause must precede the effect), plausibility (the explanation must make sense biologically), and biological gradient (there must be a dose–response relationship). With chronic illnesses such as heart disease and cancer, large numbers of cases must be evaluated to determine these relationships.

Conditions for an epidemic. An epidemic or an outbreak exists when more cases of disease occur than would be normally expected in a specific place, in a group of people, or over time. Although the terms outbreak and epidemic are appropriate for any disease entity or condition, they are used primarily with diseases of infectious or unknown origin. Outbreaks generally occur as a cluster of cases. Public health agencies then have to determine if the cluster represents an increase in cases over what would normally be expected to occur in the population of interest. Public health agencies do this by verifying the diagnosis; defining and identifying cases; describing and orienting the data in terms of time, place, and person; developing and evaluating hypotheses; and implementing control and prevention measures.

Outbreak investigation. Outbreak investigation is not only data intensive, it is also staff intensive. Data must be collected from clinical records, laboratories, and interviews with ill persons and well controls. These data must be rapidly linked by person and then analyzed to determine relationships. Complex calculations including conditional linear logistic regression must be performed to determine the statistical strength of relationships. Public, media, and political pressure frequently becomes a factor if the cause of the outbreak is not rapidly determined. If the outbreak is associated with a product, costly recalls are initiated, which can result in major loss of business.

State Of The Public Health Information Infrastructure

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Automation. Automation of information management systems in the United States began with the 1890 census.³ The first automated system for data installed in state government in Illinois was established to manage the vital statistics system in 1938.⁴ Eleven years after the national Census Bureau used the first computer in U.S. civilian practice in 1951, the Illinois Department of Public Health (IDPH) became one of the first state public health departments to adopt computer technology. In 1962 the department converted all applications from tabulation equipment to an IBM 1401 computer. Within two years of its installation, the system was being used to manage data from the divisions of sanitary engineering, administration, laboratories, communicable disease control, dental health, and maternal and child health.⁵

National databases. The national public health system is composed of a network of local and state public health agencies. For vital records and infectious disease, states work together and with federal agencies to establish the form and content of data submission for national databases. The Council of State and Territorial Epidemiologists (CSTE) reaches agreement with the Centers for Disease Control and Prevention (CDC) on which of the infectious diseases are deemed reportable.⁶ Beginning in 1984 the CDC in cooperation with the CSTE began a pilot system with six states called the Epidemiologic Surveillance System. This system evolved into the National Electronic Telecommunication System for Surveillance (NETSS), which receives electronic reports from all fifty states. The data are derived from reports from clinical caregivers and laboratories and are primarily received on paper cards sent through the mail.

Data integration. The rapid adoption of information technology can enhance public health practice but can also create obstacles for efficient program implementation. An IDPH review of information systems found eight separate systems related to HIV/AIDS. These systems automate different programmatic aspects including the HIV registry, the AIDS registry, the Ryan White program, and the AIDS Drug Assistance Program. Some of the information systems were developed in house, whereas others were "turnkey" systems developed by federal agencies for state use. Two key issues are worth noting here. First, federal systems must be designed to integrate the programmatic needs of local and state public health agencies. In one federal "turnkey" system, AIDS case reports must be edited by hand for completeness before the forms can be optically scanned into the database. A system designed to fit operation patterns would have used the optical scanning process to identify the need for edits. Second, having multiple HIV/AIDS systems means that the systems do not inter-operate. Data entered for one person in one system have to be reentered in another. Data coding and data definitions differ from one system to another; for example, male gender may be recorded as the alpha character "M" in one system and the numeric "1" in another.

Recent Public Health Information Initiatives

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HIPAA. The adoption of uniform standards for the transmission of health information has been a daunting task. Adoption of standards in health care has lagged behind that of other major industries. In the automobile industry, for instance, standards for the interchange and ordering of parts were established by the Big Three automakers (GM, Ford, and Daimler-Chrysler) using their market power. To date, there is no similar predominant force in the health care arena, nor is there an overriding business case for standardization. In fact, the highly competitive nature of the health care and health informatics marketplace encourages the use of proprietary systems to limit providers’ mobility and establish an edge.

Uniform data standards. Congress, through the adoption of the Health Insurance Portability and Accountability Act (HIPAA) of 1996 administrative simplification provisions, directed the U.S. Department of Health and Human Services (HHS) to adopt standards for health care data. On 11 August 2000 the first set of rules establishing standards for administrative transactions became final. These standards were developed by private-sector standards-development organizations. This first set of HIPAA rules mandates that health plans, insurance companies, and other payers modify their systems to receive these standardized electronic transactions. Payers will increasingly require providers to submit claims electronically to reduce costs. Under the provisions of the HIPAA Administrative Simplification Compliance Act of 2001, the Centers for Medicare and Medicaid Services (CMS) will be prohibited from paying claims that are not submitted electronically after 16 October 2003.⁷ Therefore, caregivers need to have practice management and other billing systems that will transmit claims and other administrative data. The consistent format and content for each payer enables providers to reduce costs.

The adoption of the first HIPAA standards lays the groundwork for the further development of the PHII. These standards establish a uniform definition, data content, and format for more than 400 health data fields. Further, the adoption of electronic data interchange (EDI) by the health care industry provides the infrastructure for other EDI transactions including the production and transmittal of standardized reports to public health agencies.

Standards for patient medical records. HIPAA also mandated that the National Committee on Vital and Health Statistics (NCVHS) study the adoption of uniform data standards for patient medical record information and the electronic exchange of such information. The NCVHS in its 6 July 2000 recommendations to Donna Shalala, then secretary of HHS, outlined the criteria and the process for adoption of rules for patient medical record information.⁸ The NCVHS noted that the movement of patient medical record information requires interoperability, comparability, and assurance of data quality. Interoperability refers to the ability of one computer system to exchange data with another computer system. Comparability requires that the meaning of data is consistent when shared among different parties. The NCVHS has recommended adoption of interoperability standards based upon those developed by Health Level Seven (HL7), Digital Imaging and Communications in Medicine (DICOM), the National Council for Prescription Drug Programs (NCPDP), and the Institute of Electrical and Electronic Engineers (IEEE).⁹ The committee is deliberating the adoption of codeset and vocabulary standards to facilitate comparability—standards that are essential for a fully functional PHII.

Privacy regulations. HIPAA also mandates the adoption of regulations to protect patients’ privacy. These standards have a major impact on the ways in which health care providers conduct their business. However, these standards recognize the important role of data reporting to public health. Reporting to a public health agency is exempted from authorization and consent requirements.

National Health Information Infrastructure. After years of working on HIPAA standards, the NCVHS realized that a comprehensive approach to national health information policy was needed. The committee determined that an overarching vision would help to put the administrative standards and patient medical record information standards into proper perspective. Further, an overarching vision was needed to identify gaps in the standards-development process. These concerns were put in writing in a 1998 letter from Don Detmer, then chairman of the NCVHS, to then Secretary Shalala. With Shalala’s approval, the NCVHS began a four-year effort to define the overarching vision in the form of the NHII. To be meaningful, the NHII has to be independent of any database, operating system, or hardware system. It is not a centralized database that stores data and information about individuals. Rather, it is the "set of technologies, standards, applications, systems, values and laws that support individual health, health care, and public health."¹⁰ The NHII does not exist in a comprehensive way; however, many pieces are well-developed and in use. Others are under development, and still others have yet to be fully envisioned.

Three dimensions. The committee’s report identifies three dimensions that must be operational for this vision to be realized: health care provider, population health, and personal health.¹¹ The health care dimension is the most fully developed of the three. The HIPAA administrative simplification regulations and recommendations for patient medical record information fill in a number of gaps. Full realization of the health care dimension depends upon a fully functional computerized medical record. The population health dimension is embodied in the PHII; it is dependent on developments in the other dimensions.

The personal health dimension is the least well developed. Fully developed, this dimension would provide personal health data management and decisional support to assist individuals with making the many health-related decisions they face. Personal health information systems would help to make sense of complex quality and patient-safety measures and report cards of health plans, facilities, and other providers. Such systems also would assist patients in making complex decisions in areas where there is no clear choice based on the available science. They would provide only the information and knowledge that an individual wants or needs. Finally, the systems would enable individuals to manage and control their health information based upon a clear balance between their concern for privacy and their providers’ desire to deliver comprehensive, informed care.

Need for HHS leadership. The NCVHS final report on the NHII reflects the consistent messages received from the public, the industry, and provider organizations following a series of hearings. The NCVHS recommendations that address the role of HHS in bringing about the NHII are perhaps the most crucial. HHS must take a leadership role to assure a consistent and concerted advancement toward fulfilling the NHII vision. As such, HHS should establish a secretary-level position with responsibility for overseeing the development of the NHII. HHS should lead by example, supporting an accelerated health information standards-development process and adopting standards within HHS agencies. These recommendations are consistent with those made by the President’s Information Technology Advisory Committee.¹²

National Electronic Disease Surveillance System (NEDSS). The CDC has been an active participant in the standards-development process, recognizing that health care–related standards facilitate public health reporting. The public health community needs enhanced standards to assure that community health data can be collected, analyzed, and acted upon. In response, the CDC developed the Public Health Conceptual Data Model and NEDSS.¹³ According to a CDC Web site, "The vision of NEDSS is to have integrated surveillance systems that can transfer appropriate public health, laboratory, and clinical data efficiently and securely over the Internet. NEDSS will revolutionize public health by gathering and analyzing information quickly and accurately. This will help to improve the nation’s ability to identify and track emerging infectious diseases and potential bioterrorism attacks as well as to investigate outbreaks and monitor disease trends."¹⁴

In the wake of the terrorist attacks with anthrax in 2001, the Bush administration made $1.1 billion available for improvements of states’ public health infrastructures. A key deliverable was the adoption and implementation of NEDSS in every state. NEDSS has two components: the NEDSS architecture, and the NEDSS base system. The NEDSS architecture is based upon national standards including those adopted under HIPAA, HL7 standards, and vendor-independent de facto commercial standards. The system relies upon Internet technologies for electronic data interchange.¹⁵ State-specific NEDSS systems were directed to follow the NEDSS architecture to ensure interoperability. Recognizing that many states did not have the resources to develop a complex system on their own, the CDC has contracted with an outside vendor to develop a NEDSS base system.¹⁶ This system implements the NEDSS architecture in a generic way. States that adopt the base system will have to modify their workflow patterns to fit the system’s design.

Implications Of Improved Data Collection Methods

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The role of the PHII is the collection of data, analysis of the data, hypothesis formation and confirmation, and management of interventions. Standards for HIPAA-designated transactions and for patient medical record information will facilitate the movement of critical clinical information from the health care setting to the public health system. Expecting busy clinicians to take time out of their patient-care duties to fill out public health reporting documents is a major flaw in the current system. All the data that are needed for each public health report are located in the medical record. In an automated environment, reporting could be as simple as a few keystrokes. Health care information management systems would create and transmit an HL7 message to the public health system. The data in the HL7 message would populate the database and, depending on the logic of the system, initiate action by a local or state public health agency.

Benefits of automated reporting. The automated reporting from the health care setting will lead to improvements in the completeness, timeliness, and quality of the data reported. Automated clinical information systems would compare each clinical record with case definitions for required reports and prompt the caregiver to hit the proper key combination to report the case. This would make our public health system independent of the actions and memory of very busy caregivers.

Automated reporting would improve the quality of the data that are reported. Paper reports are frequently submitted to public health agencies with incomplete or inaccurate information. Even the most diligent person makes mistakes when transferring information from one document to another. Range checks and other real-time error-detection algorithms will help automated clinical reporting systems to dramatically reduce data-entry errors. The electronic transfer of data also eliminates multiple opportunities for data-entry errors.

Finally, automated reporting would dramatically reduce the time delay between the occurrence, diagnosis, or laboratory finding of an event and its report. System reports now are mailed from the clinician to the local public health department and then on to the state public health department. Electronically transmitting the message to a centralized public health data repository makes the data instantly and simultaneously available to local and state authorities.

Efficient use of hospital discharge data. While these improvements are dependent on the adoption of automated clinical records, some public health databases will benefit immediately from the HIPAA administrative simplification provisions. States use hospital discharge data to monitor health status and evaluate the performance of their health care systems. These data sets are populated by subsets of the UB92 Uniform Discharge form as approved by the National Uniform Billing Committee of the American Hospital Association.¹⁷ When HHS adopts the ANSI ASC X12 837 billing transaction standard under HIPAA in October 2003, these data sets can be populated with minimal cost to the reporting institutions. Hospitals and other reporters will be able to send to the state public health agency a copy of the same X12 837 message that they send to third-party payers. The electronic collection of the discharge abstract as part of the billing process would require fewer state agency staff to edit or correct. A number of states, including California and New York, are already developing systems based on this standard.

More rapid investigation of disease outbreaks. The NHII, as proposed by the NCVHS, will have an important impact on data systems that are dependent on surveys now. Just as the phone survey greatly reduced costs over door-to-door surveys, Internet-based surveys completed on a home health information system would allow a larger segment of the population to be contacted at any given time. Applying this same approach to investigation of outbreaks would allow local or state epidemiologist to "interview" many more people in a short time. In June 1998, 961 people from forty-four states and seven countries participated in a triathlon that included a swim in Lake Springfield, Illinois. Afterward, 110 triathlon participants and 228 residents of Springfield developed symptoms consistent with leptospirosis infection. After days of calling, only 72 percent of the participants were interviewed.¹⁸ With the adoption of personal health information systems with electronic notification, each participant would be notified immediately and asked to complete the investigation questionnaire. Automated acknowledgements would have allowed investigators to confirm receipt of the alert even if the questionnaire request were refused. With the electronic completion of outbreak investigation surveys, more rapid analysis of a cluster of disease cases to determine if an outbreak is occurring would be possible. The time from diagnosis of an unusual case to determination of an outbreak to identification of necessary interventions would be greatly reduced.

Obstacles To Improving The Public Health Information Infrastructure

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Slow adoption of data standards. To reach this next level of performance of the PHII, a number of obstacles have to be overcome. The first is the development and implementation of standards-based data collection and reporting from the clinical setting to the public health system. Although there has been major progress in the clinical area, the rate of standards implementation has been slower on the public health side. NEDSS standards have yet to be fully enforced in the development of information systems within the CDC. Other HHS agencies have yet to adopt the NEDSS standards and will not do so without clear direction from the HHS secretary. Application of the HIPAA and NEDSS standards to other health-related data collection efforts, such as the Fatality Analysis Reporting System (FARS) of the U.S. Department of Transportation’s National Highway Traffic Safety Administration and the National Electronic Injury Surveillance System (NEISS) of the Consumer Product Safety Commission, is also needed. There is increasing organized support for the adoption of public health standards as demonstrated by the eHealth Initiative’s Public-Private Sector Collaboration for Public Health and the work of the Public Health Data Standards Consortium.¹⁹

Proliferation of stand-alone systems. The second major obstacle is the disconnected process of developing a public health information system. As Phil Lee, former HHS assistant secretary for health, once noted, "I always knew that data was a four letter word, I just never knew it was spelled T-U-R-F."²⁰ Federal program managers who want to ensure accountability restrict their funding to narrow program activities. This results in a proliferation of stand-alone, program-specific public health information systems. In response to states’ concerns, the CDC and the Health Resources and Services Administration (HRSA) have agreed to allow states to use up to 5 percent of categorical funding for the development of integrated public health information systems. Many states have developed more integrated public health information systems using a combination of state and federal funds.²¹

Lack of coordination between city and state systems. Third, with available technology, public health information systems can and should be developed using software reuse models. Yet each public health jurisdiction often proceeds to implement its own separate system. In the current round of funding for public health preparedness, New York City and Chicago are developing NEDSS systems independent of their state system. Many states are developing separate implementations of NEDSS despite similarities in the processes that are being automated. A solution needs to found to the very inefficient approach of having each public health jurisdiction develop separate versions of disease surveillance systems. The areas in which business practices differ are much smaller than the areas in which they are the same. Resources should be focused on the development of a prototype system that each public health jurisdiction could modify to meet its specific workflow needs. The current urgency to fill in the public health infrastructure gaps will not allow a more collaborative approach; however, future rollouts of federally funded information systems should involve more coordination in development between local and state jurisdictions and between states.

Time delays in reporting. The limits of public health science create the last barrier. As the ability to dramatically reduce time delays in reporting is realized, real-time surveillance becomes possible. The window of opportunity to treat inhalation anthrax exposure or exposure to inhalation of Yersinia pestis (the bacterium causing plague) is very short.²² Early symptoms for many of the organisms considered to be potential bioterrorism agents are difficult to differentiate from influenza symptoms. Since the events of fall 2001, the potential role for syndromic surveillance has been aggressively explored. There is a slim science base to support the resource-intensive monitoring of nonspecific, potentially false-positive clusters of disease complaints. Over the next few years intensive research should be undertaken to examine the utility of these real-time surveillance systems before large amounts of scarce resources are allocated to their universal adoption.

In the aftermath of the Fall 2001 terrorist attacks, Congress and the Bush administration have allocated $1.1 billion to rebuild the public health infrastructure. A large portion of this investment is directed toward developing and improving the information infrastructure. At the same time, there has been an acceleration in the adoption and implementation of a clinical data standards system as directed by HIPAA. The convergence of the mechanism for change and the infusion of new resources presents a unique opportunity to dramatically improve the PHII and public health system performance. A strong commitment to expanding the base of public health information standards represented by the NEDSS Logical Data Model is essential to realizing this potential. Strong federal leadership in standards development, standards adoption, and implementation of the NHII is key to building a public health system that is fully capable of responding to the realities of today’s world.

Editor's Notes

 
John Lumpkin is director of the Illinois Department of Public Health and chairman of the National Committee on Vital and Health Statistics. Margaret Richards is deputy director, Office of Epidemiology and Health Systems Development, in the Illinois Department of Public Health.

NOTES

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1. Institute of Medicine, The Future of Public Health (Washington: National Academy Press, 1988).
2. L.J. Altman, Plague and Pestilence: A History of Infectious Disease (Berkeley Heights, N.J.: Enslow Publishers, 1998).
3. J. Burke, Connections (Boston: Little Brown and Company, 1995).
4. B.K. Richardson, A History of the Illinois Department of Public Health, 1927–1962 (Springfield: Illinois Department of Public Health, 1963).
5. E.L. Wittenborn, A History of the Illinois Department of Public Health, 1962–1977 (Springfield: Illinois Department of Public Health, 1983).
6. Centers for Disease Control and Prevention, "National Notifiable Diseases Surveillance System," 17 July 2002, www.cdc.gov/epo/dphsi/nndsshis.htm (20 August 2002).
7. Department of Health and Human Services, "HIPAA Administrative Simplification Compliance Act, Frequently Asked Questions," 31 January 2002, aspe.hhs.gov/admnsimp/ASCA percent20FAQs-1-31.htm (20 August 2002).
8. National Committee on Vital and Health Statistics, Report to the Secretary on Uniform Data Standards for Patient Medical Record Information, 6 July 2000, www.ncvhs.hhs.gov/hipaa000706.pdf (20 August 2002).
9. Letter from John Lumpkin, NCVHS chair, to Tommy Thompson, HHS secretary, containing NCVHS recommendations for the first set of PMRI standards, 27 February 2002, www.ncvhs.hhs.gov/020227lt.htm (20 August 2002).
10. NCVHS, "Assuring a Health Dimension for the National Information Infrastructure," 14 October 1998, www.ncvhs.hhs.gov/hii-nii.htm (20 August 2002).
11. NCVHS, Information for Health—A Strategy for Building the National Health Information Infrastructure, 15 November 2002, ncvhs.hhs.gov/nhiilayo.pdf (20 August 2002).
12. Letter to President George W. Bush from President’s Information Technology Advisory Committee, 9 February 2001, www.hpcc.gov/ac/letters/pitac_ltr_hc_9feb01.html (20 August 2002).
13. CDC, Public Health Conceptual Data Model, Premiere edition, July 2000, www.cdc.gov/nedss/DataModels/phcdm.pdf (20 August 2002).
14. CDC, "National Electronic Disease Surveillance System," www.cdc.gov/nedss (20 August 2002).
15. CDC, NEDSS Logical Data Model and Users’ Guide, Version 1.0, www.cdc.gov/nedss/DataModels/NLDM_Overview_Users_Guide_v1.pdf (20 August 2002).
16. CDC, "Description of the NEDSS Base System," 28 March 2001, www.cdc.gov/nedss/BaseSystem/NEDSSBaseSysDescription.pdf (20 August 2002).
17. National Uniform Billing Committee, "The History of the NUBC," 1999, www.nubc.org/history.html (20 August 2002).
18. Wisconsin Outbreak Investigation Team et al., "Outbreak of Acute Febrile Illness among Athletes Participating in Triathlons—Wisconsin and Illinois 1998," Morbidity and Mortality Weekly Report (24 July 1998): 585–588.
19. eHealth Initiative, "Current Issues," 2001, www.ehealthinitiative.org/policy/current.html (20 August 2002); and National Center for Health Statistics, "Public Health Data Standards Consortium," 1 August 2002, www.cdc.gov/nchs/otheract/phdsc/phdsc.htm (20 August 2002).
20. Phil Lee, former assistant secretary for health, Department of Health and Human Services, personal communication, circa 1993.
21. K.A. Chapman and A.D. Moulton, "The Georgia Information Network for Public Health Officials (INPHO): A Demonstration of the CDC INPHO Concept," Journal of Public Health Management and Practice 1, no. 2 (1995): 39–43.[Medline]
22. T. Inglesby et al., "Anthrax as a Biological Weapon—Medical and Public Health Management," Journal of the American Medical Association (12 May 1999): 1735–1745; and CDC, "Facts about Pneumonic Plague," 14 October 2001, www.bt.cdc.gov/DocumentsApp/FactSheet/Plague/About.asp (20 August 2002).

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