Drug safety surveillance using de-identified EMR and claims data: issues and challenges.
The author discusses the challenges of pharmacovigilance using electronic medical record and claims data. Use of ICD-9 encoded data has low sensitivity for detection of adverse drug events (ADEs), because it requires that an ADE escalate to major-complaint level before it can be identified, and because clinical symptomatology is relatively under-represented in ICD-9. A more appropriate vocabulary for ADE identification, SNOMED CT, awaits wider deployment. The narrative-text record of progress notes can potentially be used for more sensitive ADE detection. More effective surveillance will require the ability to grade ADEs by severity. Finally, access to online drug information that includes both a reliable hierarchy of drug families as well as structured information on existing ADEs can improve the focus and predictive ability of surveillance efforts.
Center for Medical Informatics, Yale University School of Medicine, New Haven, CT 06511, USA. prakash.nadkarni@yale.edu
Prakash M
PM
Nadkarni
D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D004305:Dose-Response Relationship, Drug; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D011358:Product Surveillance, Postmarketing / Q000379:methods*; D012680:Sensitivity and Specificity; D014481:United States; D018875:Vocabulary, Controlled