title: Near real-time adverse drug reaction surveillance within population-based health networks: methodology considerations for data accrual.
abstract: OBJECTIVE
  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 1.5 month 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 43,960 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 1.5 month 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.
authors: Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA. Taliser_Avery@hphc.org
authors: Taliser R
authors: TR
authors: Avery
authors: Martin
authors: M
authors: Kulldorff
authors: Yury
authors: Y
authors: Vilk
authors: Lingling
authors: L
authors: Li
authors: T Craig
authors: TC
authors: Cheetham
authors: Sascha
authors: S
authors: Dublin
authors: Robert L
authors: RL
authors: Davis
authors: Liyan
authors: L
authors: Liu
authors: Lisa
authors: L
authors: Herrinton
authors: Jeffrey S
authors: JS
authors: Brown
mesh_terms: D000293:Adolescent; D000328:Adult; D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D000927:Anticonvulsants / Q000009:adverse effects*; D002648:Child; D016568:Drugs, Generic / Q000009:adverse effects*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005240:Feasibility Studies; D005260:Female; D050723:Fractures, Bone / Q000453:epidemiology; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D010865:Pilot Projects; D011358:Product Surveillance, Postmarketing / Q000379:methods; D011446:Prospective Studies; D012189:Retrospective Studies; D012306:Risk; D013997:Time Factors; D014635:Valproic Acid / Q000009:adverse effects*; D055815:Young Adult
chemical_list: D000927:Anticonvulsants; D016568:Drugs, Generic; D014635:Valproic Acid
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