178487 Detecting errors in electronic laboratory disease data reporting

Monday, October 27, 2008

Deborah Kapell, MPH , Bureau of Communicable Disease, New York City Department of Health and Mental Hygiene, New York, NY
Emily Lumeng, MPH , Bureau of Communicable Disease, New York City Department of Health and Mental Hygiene, New York, NY
Jennifer Baumgartner, MSPH , Bureau of Informatics and Information Technology, New York City Department of Health and Mental Hygiene, New York, NY
Trang Nguyen, MD, DrPH, MPH , Private Consultant, Albany, NY
Beginning July 2006, all laboratories testing for notifiable diseases in New York City (NYC) residents were mandated to transmit data using electronic laboratory reporting. By October 1, 2007, the majority (74%) of reports sent to the NYC Department of Health and Mental Hygiene's Bureau of Communicable Disease (BCD) were received from the Electronic Clinical Laboratory Reporting System (ECLRS). In 2007, 99.6% (n=89,990) of ECLRS reports were directly uploaded into BCD's Communicable Disease Surveillance System (CDSS). Reporting errors can occur anywhere en route from laboratories to CDSS and must be identified and rectified immediately because some reportable diseases require timely attention (e.g., prophylaxis). We developed SAS programs to evaluate systematic data problems by assessing the completeness and timeliness of electronic surveillance reports, and have identified four common types of laboratory errors:

1. Absence of reporting, identified by comparing the number of reports received daily to the expected number as reported previously.

2. Late reporting, defined as reports consistently received >10 days after specimen collection. The New York City Health Code states that reports must be submitted within 24 hours of receiving results.

3. Missing data in reports, including test details or contact information.

4. Missing individual reports from laboratories, identified by comparing any positive test results reported by a medical provider which were not sent by the testing laboratory.

Laboratory reporting and quality assurance are labor intensive and time-consuming for both staff at NYC DOHMH and the laboratories. Laboratories might respond to financial inducements, especially to enable complete reporting of required data. Other forms of quality assurance, including direct laboratory audits, are also necessary. Ultimately, ELR relies on the laboratories understanding their reporting responsibilities, and the willingness of health agencies to provide training and technical support.

Learning Objectives:
1. Recognize common errors in electronic laboratory reporting. 2. Devise methods to detect errors systematically 3. Develop strategies for working with laboratories to minimize errors

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: Developed the SAS programs to evaluate data quality, wrote the abstract
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.