Grant Aileen, Dreischulte Tobias, Guthrie Bruce
Faculty of Health Sciences and Sport, University of Stirling, Stirling, UK.
Medicines Governance Unit, NHS Tayside, Dundee, UK.
Implement Sci. 2017 Jan 7;12(1):4. doi: 10.1186/s13012-016-0531-2.
Two to 4% of emergency hospital admissions are caused by preventable adverse drug events. The estimated costs of such avoidable admissions in England were £530 million in 2015. The data-driven quality improvement in primary care (DQIP) intervention was designed to prompt review of patients vulnerable from currently prescribed non-steroidal anti-inflammatory drugs (NSAIDs) and anti-platelets and was found to be effective at reducing this prescribing. A process evaluation was conducted parallel to the trial, and this paper reports the analysis which aimed to explore response to the intervention delivered to clusters in relation to participants' perceptions about which intervention elements were active in changing their practice.
Data generation was by in-depth interview with key staff exploring participant's perceptions of the intervention components. Analysis was iterative using the framework technique and drawing on normalisation process theory.
All the primary components of the intervention were perceived as active, but at different stages of implementation: financial incentives primarily supported recruitment; education motivated the GPs to initiate implementation; the informatics tool facilitated sustained implementation. Participants perceived the primary components as interdependent. Intervention subcomponents also varied in whether and when they were active. For example, run charts providing feedback of change in prescribing over time were ignored in the informatics tool, but were motivating in some practices in the regular e-mailed newsletter. The high-risk NSAID and anti-platelet prescribing targeted was accepted as important by all interviewees, and this shared understanding was a key wider context underlying intervention effectiveness.
This was a novel use of process evaluation data which examined whether and how the individual intervention components were effective from the perspective of the professionals delivering changed care to patients. These findings are important for reproducibility and roll-out of the intervention.
ClinicalTrials.gov, NCT01425502 .
2%至4%的急诊入院是由可预防的药物不良事件引起的。2015年，英格兰此类可避免入院的估计费用为5.3亿英镑。数据驱动的初级保健质量改进（DQIP）干预旨在促使对目前正在服用非甾体抗炎药（NSAIDs）和抗血小板药物的易受伤害患者进行复查，并被发现可有效减少此类处方。在试验的同时进行了过程评估，本文报告了该分析，旨在探讨与参与者对哪些干预因素在改变其行为方面起作用的看法相关的对集群实施干预的反应。
通过对关键工作人员进行深入访谈来生成数据，以探讨参与者对干预组成部分的看法。使用框架技术并借鉴规范化过程理论进行迭代分析。
干预的所有主要组成部分都被认为是有效的，但在实施的不同阶段：经济激励主要支持招募；教育促使全科医生开始实施；信息学工具促进了持续实施。参与者认为主要组成部分是相互依存的。干预子组成部分在是否以及何时起作用方面也有所不同。例如，信息学工具中忽略了提供随时间变化的处方反馈的运行图表，但在定期电子邮件通讯中的某些实践中却具有激励作用。所有受访者都认为针对高风险NSAID和抗血小板药物的处方很重要，这种共同的理解是干预有效性背后的一个关键更广泛背景。
这是对过程评估数据的一种新颖运用，从为患者提供改变后护理的专业人员的角度检查了各个干预组成部分是否有效以及如何有效。这些发现对于干预措施的可重复性和推广很重要。
ClinicalTrials.gov，NCT01425502 。
