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Disease Reporting from an Automated Laboratory-Based Reporting System to a State Health Department via Local County Health Departments
Howard D. Backer, Stanley R. Bissell and Duc J. Vugia
Public Health Reports (1974-)
Vol. 116, No. 3 (May - Jun., 2001), pp. 257-265
Published by: Association of Schools of Public Health
Stable URL: http://www.jstor.org/stable/4598643
Page Count: 9
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Objective: The authors assessed the completeness of disease reporting from a managed care organization's automated laboratory-based reporting system to the California Department of Health Services (CDHS) via local public health departments. Methods: The authors identified all positive laboratory tests for 1997 from the computerized database of Kaiser Permanente Northern California for seven infections for which there are statutory reporting requirements: Campylobacter jejuni, Chlamydia trachomatis, Cryptosporidium parvum, hepatitis A, Neisseria meningitidis, Neisseria gonorrhoeae, and Salmonella (N = 7,331 reports). Cases were then matched by computer query to records of cases reported to CDHS. To determine why cases were not found in CDHS records, a sample of unmatched cases was searched at two county health departments. Results: Overall, 84.5% (95% Cl 83.4, 85.6) of the laboratory reports submitted with accompanying demographic information were successfully matched with cases in the CDHS disease surveillance database. Frequency of matching for specific diseases ranged from 79.4% (95% Cl 75.6, 83.3) for N. gonorrhoeae to 88.4% (95% Cl 85.3, 91.6) for C. jejuni. Reports were more likely to be matched when the county of residence was the same as the county of the health care facility. At the county level, reasons for failure of cases to be forwarded to CDHS included: errors due to manual data entry, failure to forward information from the county of diagnosis to the county of residence, and incorrect disease coding. Conclusion: Automated laboratory-based reporting is highly effective, but some data are lost with off-line transfer of information. To optimize surveillance accuracy and completeness, reporting at all levels should be done via direct electronic data transfer.
Public Health Reports (1974-) © 2001 Association of Schools of Public Health