Using primary care prescribing data to improve GP awareness of antidepressant adherence issues

• Published in: Informatics in primary care 2011, Vol.19 (1), p.7-15
• Main Authors: Mabotuwana, Thusitha, Warren, Jim, Orr, Martin, Kenealy, Timothy, Harrison, Jeff
• Format: Article
• Language: English
• Subjects: Adult; Age Factors; Aged; ambulatory care information systems; Antidepressive Agents - administration & dosage; clinical audit; Data Collection - methods; Electronic Prescribing - statistics & numerical data; Female; General Practitioners - statistics & numerical data; Humans; Insurance Claim Review; Male; Medication Adherence - statistics & numerical data; Middle Aged; patient non-adherence; Primary Health Care - statistics & numerical data; quality indicators; Sex Factors; Socioeconomic Factors
• ISSN: 1476-0320; 2058-4555; 2058-4563
• DOI: 10.14236/jhi.v19i1.788

Adherence to antidepressant therapy remains a major issue worldwide. Most people with depression are treated in a general practice setting, but many stop taking antidepressants before completing a six-month course as recommended by guidelines. To determine antidepressant adherence rates as indicated in primary care prescribing data and pharmacy dispensing data; to demonstrate commonly occurring patterns related to non-adherence, using a prescription visualisation tool we have developed; and to determine whether prescribing data is a good predictor of dispensing based adherence. We analysed general practice electronic prescribing data for the year ending 31 December 2006 and linked pharmacy dispensing records by National Health Index. We calculated medication adherence for patients starting antidepressants using a six-month evaluation period and a gap-based adherence measure. Patients with a gap of more than 15 days in antidepressant therapy were considered non-adherent. Using a prescription visualisation tool, we described common modes of non-adherence. Out of 2713 patients, 153 satisfied our inclusion criteria. Thirty-nine percent of patients showed poor adherence based on prescribing and 68% showed poor adherence on dispensing. Prescribing based non-adherence had a positive predictive value of 98% (95% CI 92%-99%) and negative predictive value of 51% (CI 47%-52%) for dispensing based non-adherence. Three broad categories of non-adherence were identified: 1) failure to return for re-prescription, 2) failure to maintain adherence despite initial attempts and 3) failure to return for re-prescription in a timely manner. Prescribing data identifies substantial adherence issues in antidepressant therapy. Clinicians should consider adherence issues as part of the overall treatment regime and discuss such issues during consultations.