title: Participation in an ambulatory e-pharmacovigilance system.
abstract: OBJECTIVE
  There is growing concern about whether passive surveillance can detect adverse drug events (ADEs). Our objective was to demonstrate the reach of an interactive voice response system (IVRS) to systematically monitor symptoms experienced by ambulatory patients prescribed one of 31 medications, and to document whether there were differences in our ability to contact certain populations.
  
  
  METHODS
  Patients receiving a prescription for a target medication at one of 11 clinics were eligible for a cross-sectional IVRS survey, "e-pharmacovigilance," with a follow-up survey done 3 months later if the target medication was still listed on the patient's active medication list.
  
  
  RESULTS
  902 patients participated, representing 43.3% of contacted and 25.7% of potentially eligible patients with a working phone. After adjustment for demographics and drug class, patients >66 years were more likely to participate than those 56-65 years (odds ratio 1.47; 95% confidence interval 1.19-1.81). Hispanics were less likely than whites (0.56; 0.42-0.76), and those in low-income communities less likely to participate than those in high-income communities (0.69; 0.58-0.82). Patients prescribed asthma, or seizure medications were more likely to participate than those prescribed medications for insomnia. Of patients reached by the system, those prescribed medications were erectile dysfunction and smoking cessation were less likely, and those prescribed seizure medication were more likely to participate.
  
  
  CONCLUSIONS
  IVRS technology can be used to perform ambulatory e-pharmacovigilance for a broad spectrum of patients, particularly older individuals who may at particular risk for ADEs.
authors.affiliation: Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA 02120, USA. jhaas@partners.org
authors.forename: Jennifer S
authors.initials: JS
authors.lastname: Haas
authors.forename: Aarthi
authors.initials: A
authors.lastname: Iyer
authors.forename: E John
authors.initials: EJ
authors.lastname: Orav
authors.forename: Gordon D
authors.initials: GD
authors.lastname: Schiff
authors.forename: David W
authors.initials: DW
authors.lastname: Bates
mesh_terms: D000293:Adolescent; D000328:Adult; D016907:Adverse Drug Reaction Reporting Systems; D000367:Age Factors; D000368:Aged; D000553:Ambulatory Care / Q000379:methods; D003430:Cross-Sectional Studies; D003625:Data Collection; D005260:Female; D005500:Follow-Up Studies; D006630:Hispanic or Latino; D006801:Humans; D008297:Male; D008875:Middle Aged; D010342:Patient Acceptance of Health Care; D055553:Prescription Drugs / Q000009:adverse effects*; D012959:Socioeconomic Factors; D049250:Speech Recognition Software; D013689:Telephone; D055815:Young Adult
chemical_list: D055553:Prescription Drugs