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.
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.
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.
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).
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.
Bureau of Communicable Disease (Drs Greene and Andrews, Ms Baumgartner, and Mr Peterson) and Bureau of Information Technology and Informatics (Ms Evans Lloyd), New York City Department of Health and Mental Hygiene, Queens, New York. Dr Andrews is now with the City University of New York School of Medicine, New York, New York.
Correspondence: Sharon K. Greene, PhD, MPH, Bureau of Communicable Disease, New York City Department of Health and Mental Hygiene, 42-09 28th St, CN 22A, WS 06-154, Queens, NY 11101 (email@example.com).
The authors thank Annie Fine and Martin Kulldorff for guidance and all who conducted quality assurance for electronic laboratory reporting, including staff at all reporting laboratories, New York City (NYC) Department of Health and Mental Hygiene (DOHMH) electronic laboratory reporting coordinators (Youseline Cherfilus, Veronica Culhane, Paula Durongwong, Eileen Jacobs, and Nicketa Nusum), and DOHMH Bureau of Communicable Disease analysts (Ana Maria Fireteanu, Kristen Lee, Maryam Iqbal, and Alaina Stoute).
A preliminary version of this work was presented in a breakout session (abstract #9525) at the annual conference of the Council of State and Territorial Epidemiologists (CSTE), West Palm Beach, Florida, June 10 to 14, 2018, where it received the CSTE Presidential Priorities award in recognition of exceptional work to advance the use of informatics to improve health outcomes.
SaTScan™ is a trademark of Martin Kulldorff. The SaTScan™ software was developed under the joint auspices of Martin Kulldorff, the National Cancer Institute, and Farzad Mostashari of NYC DOHMH.
This work was reviewed and deemed public health surveillance that is nonresearch by the DOHMH Institutional Review Board.
Drs Greene and Andrews and Mr Peterson were supported by the Public Health Emergency Preparedness Cooperative Agreement (grant NU90TP921922) funded by the Centers for Disease Control and Prevention (CDC). Ms Evans Lloyd was supported by the Homeland Security Grant Program (Urban Areas Security Initiative). Ms Baumgartner was supported by the Epidemiology and Laboratory Capacity for Infectious Diseases Cooperative Agreement (grant NU50CK000407) funded by the CDC. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Department of Health & Human Services.
The authors declare no conflicts of interest.
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