Figure 3. Example of a pathogen-trending report showing the trends for a user-selected set of pathogens. Other reports include facility summaries, detailed-line listings, and age trends. Jurisdictional filters were applied to deliver appropriate data to the Kansas Department of Health and Environment (these data will be analyzed separately). We evaluated reports received through both conven- tional and electronic reporting between March 29, 2002, and September 2, 2002, for data completeness and timeli- ness. Disease reporting in Kansas City requires that public health officials know the name of the testing facility and the patient’s age, date of birth, race, sex, address, and tele- phone number. As each conventional or electronic report was received, KCHD documented whether each required data element was provided and documented the date on which conventional reports were received. Timeliness was determined by comparing this date with the date that a reportable pathogen was first posted to data clearinghouse. Reports received only through electronic means were evaluated to confirm that they satisfied KCHD reporting criteria. This review included confirmation of appropriate jurisdictional concerns, origin of isolate (appropriate body site), and exclusion of false-positive results. Geographic information system maps, showing the res- idential zip code of patients with reportable isolates, were delivered to KCHD by using ArcIMS (ESRI, Redlands, CA). Users could select a pathogen and observe the zip codes of patients with confirmed cases. Geographic cover- age maps were generated by using the zip codes of all patients whose results were evaluated by the system. Critical isolate alerts were also built into the system. A single instance of Bacillus anthracis, Coxiella burnetii, Yersinia pestis, or any Brucella species would trigger alerts sent to the pagers of on-call public health officers and supervisors. Results The electronic data clearinghouse study was conducted in tandem with conventional reporting at all sites. In 2002, conventional reports to KCHD originated from laborato- RESEARCH ries (52%), infection control practitioners (34%), blood centers (6%), private physicians (4%), and other sources (4%). Personnel involved in conventional reporting were generally unaware of the electronic reporting system; their management was instructed in the dual reporting require- ment. Our review of reports received through both the clearinghouse and conventional reporting identified 144 isolate reports. An additional 213 cases arrived only through electronic reporting (Table 1). We reviewed the addresses of the patient and reporting laboratory to verify that a report was in the KCHD jurisdiction. Table 1 lists the specific pathogens documented through this system and the average improvement in timeliness for each pathogen. Timeliness improved for all pathogens; the improvements for chlamydia, invasive group A streptococcal infections, and salmonellosis cases were statistically significant (Table 1). One chlamydia case arrived 20 days earlier through clearinghouse reports. Many case reports were only received through electron- ic reporting (Table 1). In particular, giardiasis and hepati- tis C were underreported. Sexually transmitted diseases, including chlamydia, gonorrhea, and syphilis, were also underreported. The data clearinghouse received all cases reported by traditional means for diseases that were consistently docu- mented by using microbiology reports. The value pre- cluded the use of the Chandra Sekar-Deming capture- recapture technique used to assess reporting coverage in other electronic reporting systems (8,9). Diagnostic results verifying some diseases, especially viral diseases such as hepatitis and HIV, are sometimes documented using microbiology reports but are often documented using LIS applications from which results were not evaluated by the data clearinghouse. Demographic information about patients was provided more often through clearinghouse reports than through reports received in tandem by traditional means. This improvement was statistically significant for patient address, race, age, date of birth, and sex, as determined by McNemar’s test (Table 2). Geographic coverage was examined by using ArcIMS (ESRI) to plot the zip codes of patients whose data were evaluated by the system, independent of the result (Figure 4). The breadth of geographic coverage provided by the system extended well beyond the Kansas City metropoli- tan area. The system evaluated patients from all regions of Missouri and Kansas, as well as out-of-state residents. Discussion We evaluated a data clearinghouse approach to biosur- veillance using clinical microbiologic laboratory data. Electronic reporting of communicable diseases has been tested in other communities, including Hawaii, Pittsburgh, Emerging Infectious Diseases • Vol. 9, No. 10, October 2003 1283