利用初级保健处方数据提高全科医生对抗抑郁药物依从性问题的认识。

Thusitha Mabotuwana, Jim Warren, Martin Orr, Timothy Kenealy, Jeff Harrison
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引用次数: 13

摘要

背景:抗抑郁治疗的依从性仍然是世界范围内的一个主要问题。大多数抑郁症患者在一般的实践环境中接受治疗,但许多人在完成指南建议的六个月疗程之前就停止服用抗抑郁药。目的:确定初级保健处方数据和药房配药数据中显示的抗抑郁药物依从率;使用我们开发的处方可视化工具,展示与不依从性相关的常见模式;并确定处方数据是否能很好地预测基于配药的依从性。方法:对截至2006年12月31日的全科电子处方数据和全国健康指数关联的药房配药记录进行分析。我们使用六个月的评估期和基于间隙的依从性测量来计算开始服用抗抑郁药的患者的药物依从性。抗抑郁治疗间隔超过15天的患者被认为是非依从性的。使用处方可视化工具,我们描述了常见的不依从模式。结果:2713例患者中,153例符合纳入标准。39%的患者表现出处方依从性差,68%的患者表现出配药依从性差。基于处方的不依从性阳性预测值为98% (95% CI 92%-99%),基于配药的不依从性阴性预测值为51% (CI 47%-52%)。确定了三大类不依从性:1)未能返回重新处方,2)尽管最初尝试仍未能保持依从性,3)未能及时返回重新处方。结论:处方数据确定了抗抑郁药物治疗中实质性的依从性问题。临床医生应将依从性问题视为整体治疗方案的一部分,并在会诊时讨论这些问题。
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Using primary care prescribing data to improve GP awareness of antidepressant adherence issues.

Background: 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.

Objectives: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

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