Harnessing a health information exchange to identify surgical device adverse events for urogynecologic mesh.

Jeanne Ballard, Marc Rosenman, Michael Weiner

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

We sought to create an automated means to conduct surveillance of complications related to urogynecologic mesh because current postmarket surveillance fails to detect the true incidence of device-related adverse events. Using health information exchange data, we developed a search algorithm to identify urogynecologic surgeries with mesh implantation and associated inpatient adverse events. We validated the algorithm search results against those obtained from a manual case review of mesh surgical records. Our refined automated search strategy matched 93% of the 2874 mesh cases manually identified, and further identified 97% of 2103 vaginal mesh cases. Complications were identified in 380 of the 2874 mesh cases. This is the first known report of an automated process for identifying urogynecologic surgical mesh implantation cases from a health information exchange. Automated surveillance of health information exchange data may contribute to tracking of device-related adverse events.

Original languageEnglish (US)
Pages (from-to)1109-1118
Number of pages10
JournalUnknown Journal
Volume2012
StatePublished - 2012
Externally publishedYes

ASJC Scopus subject areas

  • Medicine(all)

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