Near real-time adverse drug reaction surveillance within population-based health networks

Methodology considerations for data accrual

Taliser R. Avery, Martin Kulldorff, Yury Vilk, Lingling Li, T. Craig Cheetham, Sascha Dublin, Robert Davis, Liyan Liu, Lisa Herrinton, Jeffrey S. Brown

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Purpose: This study describes practical considerations for implementation of near real-time medical product safety surveillance in a distributed health data network. Methods: We conducted pilot active safety surveillance comparing generic divalproex sodium to historical branded product at four health plans from April to October 2009. Outcomes reported are all-cause emergency room visits and fractures. One retrospective data extract was completed (January 2002-June 2008), followed by seven prospective monthly extracts (January 2008-November 2009). To evaluate delays in claims processing, we used three analytic approaches: near real-time sequential analysis, sequential analysis with 1.5month delay, and nonsequential (using final retrospective data). Sequential analyses used the maximized sequential probability ratio test. Procedural and logistical barriers to active surveillance were documented. Results: We identified 6586 new users of generic divalproex sodium and 43960 new users of the branded product. Quality control methods identified 16 extract errors, which were corrected. Near real-time extracts captured 87.5% of emergency room visits and 50.0% of fractures, which improved to 98.3% and 68.7% respectively with 1.5month delay. We did not identify signals for either outcome regardless of extract timeframe, and slight differences in the test statistic and relative risk estimates were found. Conclusions: Near real-time sequential safety surveillance is feasible, but several barriers warrant attention. Data quality review of each data extract was necessary. Although signal detection was not affected by delay in analysis, when using a historical control group differential accrual between exposure and outcomes may theoretically bias near real-time risk estimates towards the null, causing failure to detect a signal.

Original languageEnglish (US)
Pages (from-to)488-495
Number of pages8
JournalPharmacoepidemiology and Drug Safety
Volume22
Issue number5
DOIs
StatePublished - May 1 2013

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Population Surveillance
Drug-Related Side Effects and Adverse Reactions
Health
Valproic Acid
Safety
Hospital Emergency Service
Quality Control
Control Groups

All Science Journal Classification (ASJC) codes

  • Pharmacology (medical)
  • Epidemiology

Cite this

Near real-time adverse drug reaction surveillance within population-based health networks : Methodology considerations for data accrual. / Avery, Taliser R.; Kulldorff, Martin; Vilk, Yury; Li, Lingling; Craig Cheetham, T.; Dublin, Sascha; Davis, Robert; Liu, Liyan; Herrinton, Lisa; Brown, Jeffrey S.

In: Pharmacoepidemiology and Drug Safety, Vol. 22, No. 5, 01.05.2013, p. 488-495.

Research output: Contribution to journalArticle

Avery, TR, Kulldorff, M, Vilk, Y, Li, L, Craig Cheetham, T, Dublin, S, Davis, R, Liu, L, Herrinton, L & Brown, JS 2013, 'Near real-time adverse drug reaction surveillance within population-based health networks: Methodology considerations for data accrual', Pharmacoepidemiology and Drug Safety, vol. 22, no. 5, pp. 488-495. https://doi.org/10.1002/pds.3412
Avery, Taliser R. ; Kulldorff, Martin ; Vilk, Yury ; Li, Lingling ; Craig Cheetham, T. ; Dublin, Sascha ; Davis, Robert ; Liu, Liyan ; Herrinton, Lisa ; Brown, Jeffrey S. / Near real-time adverse drug reaction surveillance within population-based health networks : Methodology considerations for data accrual. In: Pharmacoepidemiology and Drug Safety. 2013 ; Vol. 22, No. 5. pp. 488-495.
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