Information Systems

Health departments receive vast quantities of data from laboratories, healthcare systems, and private citizens, as well as from their own investigations. Health departments and commercial information technology companies have been developing specialized information systems to manage these data since the 1970s. Many of the systems developed before 2000 were developed for specific organizational units within health departments, such as the Sexually Transmitted Disease Management Information System (STD-MIS) (Koo and Gibson Parrish II, 2000). As a result of differences in system design, terminologies used, and other formatting details, these systems could not automatically exchange data, even with systems within the same health department. In the late 1990s, these limitations led to a rethinking of how to develop and organize information systems used by health departments.

7.1. Systems Developed before 2000

As a result of the siloing of information-system functionality before 2000, health department staff often had to type the name, address, birth date, and other data about the same person into each system that needed the data. To file a weekly report of disease activity to the CDC, for example, a staff member of a state health department might have to print out (or read from a screen) data from a local system and type it into another system.

In 2003, the CDC conducted an internal inventory of its own information systems, identifying 120 surveillance systems in use at CDC (Figure 5.5).These systems collected data from various sources, including health departments, healthcare providers, laboratories, individuals, or medical records and birth and death certificates (Koo et al., 2003). We describe a representative sample of those systems to illustrate the lack of integration and consistency of biosurveillance systems in use before 2000.

7.1.1. National Electronic Telecommunications System for Surveillance

The National Electronic Telecommunications System for Surveillance (NETSS) was developed by CDC and the CSTE. NETSS supports the collection, transmission, analysis, and publication of weekly summaries of notifiable disease and injury activity in the 50 states, New York City, the District of Columbia, Puerto Rico, the Virgin Islands, Guam, American Samoa, and the Commonwealth of the Northern Mariana Islands.

NETSS depends on agreements and cooperation among a large number of organizations. CDC/CSTE agreements on notifiable conditions, protocols for formatting and transmitting data, and standard case definitions enable the required data to be collected in a standardized format. Designated staff members in each participating agency prepare and submit the data. Up until 1984, the staff transmitted only the total number of cases in its jurisdiction for each of 37 notifiable diseases (23 common diseases and 14 less frequent conditions). They reported this

FIGURE 5.5 Existing surveillance information systems, data sources, and information flows. (From Koo et al., 383: figure 19.2. Copyright Springer-Verlag New York, 2003. Reprinted with kind permission of Springer Science and Business Media.)

information by telephone. In 1984, six state health departments began transmitting individual case records to CDC electronically via commercial telecommunications systems. Since 1989, all 50 states and some territories and cities have transmitted individual case records in this manner (CDC, 1991).

In January 1991, the CDC developed a new format for NETSS records. The new format provides for transmission of both individual and summary (aggregate) records. All states completed implementation of the new format in 1993 (CDC, 1991). NETSS is still operational.

7.1.2. Public Health Laboratory Information System

The Public Health Laboratory Information System (PHLIS) is a surveillance system that collects results of microbiology cultures. The National Center for Infectious Diseases and the Association of State and Territorial Public Health Laboratory Directors began developing PHLIS in 1988. By the summer of 1989, nine states were reporting Salmonella sp. isolates electronically to CDC and to state epidemiologists. States also report Campylobacter sp., Mycobacteria sp., and Shigella sp. isolates. As of December 1992, PHLIS was in use in more than 40 states (CDC, 2003a).

PHLIS reporting is limited to illnesses that are confirmed by culture and verified at a public health laboratory. After verification by the laboratory, the health department reports the information about the infection to the CDC (National Technical Information Service, 2005).

7.1.3. PulseNet

PulseNet is a nationwide surveillance system, operated by the CDC, that monitors food-borne diseases. PulseNet was developed after a large outbreak of foodborne illness caused by the bacterium Escherichia coli O157:H7 occurred in the western United States in 1993. In this outbreak, scientists at CDC performed DNA "fingerprinting" by pulsed-field gel electrophoresis (PFGE) and determined that the strain of E. coli O157:H7 found in patients had the same PFGE pattern as that of the strain found in hamburger patties served at a large chain of regional fast food restaurants. However, it took three weeks to trace the source of the E. coli contamination of hamburger meat to a single producer (CDC, 2003b).

Prompted by this event, the CDC, in collaboration with the Association of Public Health Laboratories (APHL), introduced PulseNet in 1998. PulseNet obtains samples of bacteria that have been isolated from patients with suspected food-borne illness. Laboratories located either in the healthcare system or in health departments submit samples to PulseNet (CDC, 2003b). After technicians take the DNA PFGE pattern, which determines the genotype (or other specific information on foodborne bacteria) of the bacteria, the result is stored in a centralized database, allowing scientists at public health laboratories throughout the country to compare the PFGE patterns of bacteria isolated from ill persons and determine whether the patterns are similar to those of bacteria isolated from other individuals or samples of food (CDC, 2003b).

7.1.4. Other pre-2000 CDC Systems

There were many other special purpose,"single-disease" systems identified in the 2003 survey. These single-disease systems included the National Malaria Surveillance Systems (Kachur et al., 1997), the 121-cities mortality reporting systems (CDC, n.d.) and the U.S. Influenza Sentinel Physicians Surveillance Network (CDC, 2005a).

7.2. Post-2000 Systems

The large (and proliferating) number of specialized surveillance systems that existed pre-2000 provided an impetus to re-engineer the information infrastructure of health departments. These systems could not interoperate and required health departments to enter the same data multiple times. The designers of newer information systems (which we refer to as post-2000 systems, although a few went into operation earlier than 2000) share the following design objectives: to reduce redundancy in data collection, to connect the divisions within a health department at a functional level, and to connect different health departments, as well as the CDC, for purposes of data sharing and better functional integration for outbreaks that cross jurisdictional boundaries.

The re-engineering of systems has been ongoing for approximately five years. At present, most health departments are focusing on the development of four types of systems that together will replace most of the functions of the existing base of diverse systems: National Electronic Disease Surveillance System (NEDSS), syndromic surveillance, electronic laboratory reporting (ELR), and a laboratory reporting network. As we

FIGURE 5.6 Pennsylvania NEDSS analysis and reporting. a, confirmed cases investigated fourth quarter 2003 by week investigation initiated. The large increase in November 2003 is owing to the hepatitis A outbreak described in Chapter 1.2.

Continued

FIGURE 5.6 Pennsylvania NEDSS analysis and reporting. a, confirmed cases investigated fourth quarter 2003 by week investigation initiated. The large increase in November 2003 is owing to the hepatitis A outbreak described in Chapter 1.2.

Continued will discuss, there is a pan-health department effort to standardize terminology and architecture that was originally referred to as NEDSS but is now called the Public Health Information Network (PHIN). Both of these initiatives involve standardization, system specification, and software development. The inclusion of this range of activities under names that suggest at first only a "system'' or "network" may be somewhat confusing at first to readers.

7.2.1. National Electronic Disease Surveillance System

The recommendations of a 1995 report led the CDC to develop the concept of the NEDSS (Committee on Health Promotion and Disease Prevention, 2003).

NEDSS is a somewhat confusing name because it refers to three things. It is the name of software that the CDC develops (i.e., NEDSS base system), a set of specifications that a health department can follow to construct a system with similar functionality, and a "system of systems'' (i.e., the network of interoperating systems in each state and city that has installed either the CDC-provided NEDSS system or a version that they have developed or acquired from another source) that will replace NETSS and many other pre-2000 systems.

To avoid confusion, we refer collectively to the CDC software and the software developed by states according to the blueprint as NEDSS-component systems. Figure 5.6 is a screen from a NEDSS-component system built by the Commonwealth of Pennsylvania. NEDSS-component systems include Web-based disease reporting, integration of laboratory data from the health department's laboratories, and collection and management of case data from investigations. It is important to note that NEDSS is designed to automate disease reporting first and foremost, so it is a replacement for NETSS and several disease-specific surveillance systems (e.g., the HIV/AIDS reporting system, the vaccine-preventable diseases, and systems for tuberculosis). It is intended to support disease reporting by the

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