Detecting Drop-offs in Electronic Laboratory Reporting for Communicable Diseases in New York City.

CONTEXT: The Bureau of Communicable Disease at the New York City Department of Health and Mental Hygiene receives an average of more than 1000 reports daily via electronic laboratory reporting. Rapid recognition of any laboratory reporting drop-off of test results for 1 or more diseases is necessary to avoid delays in case investigation and outbreak detection. PROGRAM: We modified our outbreak detection approach using the prospective space-time permutation scan statistic in SaTScan. Instead of searching for spatiotemporal clusters of high case counts, we reconceptualized "space" as "laboratory" and instead searched for clusters of recent low reporting, overall and for each of 52 diseases and 10 hepatitis test types, within individual laboratories. Each analysis controlled for purely temporal trends affecting all laboratories and accounted for multiple testing. IMPLEMENTATION: A SAS program automatically created input files, invoked SaTScan, and further processed SaTScan analysis results and output summaries to a secure folder. Analysts reviewed output weekly and reported concerning drop-offs to coordinators, who liaised with reporting laboratory staff to investigate and resolve issues. EVALUATION: During a 42-week evaluation period, October 2017 to July 2018, we detected 62 unique signals of reporting drop-offs. Of these, 39 (63%) were verified as true drop-offs, including failures to generate or transmit files and programming errors. For example, a hospital laboratory stopped reporting influenza after changing a multiplex panel result from "positive" to "detected." Six drop-offs were detected despite low numbers of expected reports missing (<10 per drop-off). DISCUSSION: Our novel application of SaTScan identified a manageable number of possible electronic laboratory reporting drop-offs for investigation. Ongoing maintenance requirements are minimal but include accounting for laboratory mergers and referrals. Automated analyses facilitated rapid identification and correction of electronic laboratory reporting errors, even with small numbers of expected reports missing, suggesting that our approach might be generalizable to smaller jurisdictions.

Effect of Policy Change to Require Laboratory Reporting With Pregnancy Indicated for Syphilis and Hepatitis B Virus Infection, New York City, January 2013-June 2018.

OBJECTIVES: We evaluated the impact of a 2014 New York City health code change requiring laboratories to indicate if a patient is pregnant or probably pregnant in the electronic laboratory report (ELR) when reporting syphilis and hepatitis B virus (HBV) cases to the New York City Department of Health and Mental Hygiene (DOHMH). METHODS: We calculated the number of pregnant persons with syphilis or HBV infection reported to DOHMH from January 1, 2013, through June 30, 2018. We compared the proportion in which the first report to DOHMH was an ELR with pregnancy indicated before and after the policy change. We calculated time between first ELR with pregnancy indicated and subsequent reporting by a method other than ELR and the proportion of cases in which ELR with pregnancy indicated was the only report source. RESULTS: A total of 552 new syphilis and 8414 HBV-infected cases were reported to DOHMH. From January 2013-June 2014 (pre-change) to January 2017-June 2018 (post-change), the proportion of cases in which ELR with pregnancy indicated was the first report to DOHMH increased significantly (14.7% [23/156] to 46.2% [80/173] for syphilis; 8.0% [200/2498] to 45.3% [851/1879] for HBV infection [P < .001]). Median time between first ELR with pregnancy indicated and subsequent reporting by a method other than ELR was 9.0 days for syphilis and 51.0 days for HBV infection. ELR with pregnancy indicated was the only report for 43.1% (238/552) of syphilis cases and 23.4% (1452/6200) of HBV cases during the study period. CONCLUSION: Including pregnancy status with ELR can increase the ability of public health departments to conduct timely interventions to prevent mother-to-child transmission.