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运用多标准决策分析来描述利益相关者对新的质量改进举措的偏好,这些举措可优化英格兰的处方开具。

Using multi-criteria decision analysis to describe stakeholder preferences for new quality improvement initiatives that could optimise prescribing in England.

作者信息

Khanal Saval, Schmidtke Kelly Ann, Talat Usman, Turner Alice M, Vlaev Ivo

机构信息

Behavioural Science Group, Warwick Business School, University of Warwick, Coventry, United Kingdom.

Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, United Kingdom.

出版信息

Front Health Serv. 2023 Jun 20;3:1155523. doi: 10.3389/frhs.2023.1155523. eCollection 2023.

Abstract

BACKGROUND

Hospital decision-makers have limited resources to implement quality improvement projects. To decide which interventions to take forward, trade-offs must be considered that inevitably turn on stakeholder preferences. The multi-criteria decision analysis (MCDA) approach could make this decision process more transparent.

METHOD

An MCDA was conducted to rank-order four types of interventions that could optimise medication use in England's National Healthcare System (NHS) hospitals, including Computerised Interface, Built Environment, Written Communication, and Face-to-Face Interactions. Initially, a core group of quality improvers ( = 10) was convened to determine criteria that could influence which interventions are taken forward according to the Consolidated Framework for Implementation Research. Next, to determine preference weightings, a preference survey was conducted with a diverse group of quality improvers ( = 356) according to the Potentially All Pairwise Ranking of All Possible Alternatives method. Then, rank orders of four intervention types were calculated according to models with criteria unweighted and weighted according to participant preferences using an additive function. Uncertainty was estimated by probabilistic sensitivity analysis using 1,000 Monte Carlo Simulation iterations.

RESULTS

The most important criteria influencing what interventions were preferred was whether they addressed "patient needs" (17.6%)' and their financial "cost (11.5%)". The interventions' total scores (unweighted score out of 30 | weighted out of 100%) were: Computerised Interface (25 | 83.8%), Built Environment (24 | 79.6%), Written Communication (22 | 71.6%), and Face-to-Face (22 | 67.8%). The probabilistic sensitivity analysis revealed that the Computerised Interface would be the most preferred intervention over various degrees of uncertainty.

CONCLUSIONS

An MCDA was conducted to rank order intervention types that stand to increase medication optimisation across hospitals in England. The top-ranked intervention type was the Computerised Interface. This finding does not imply Computerised Interface interventions are the most effective interventions but suggests that successfully implementing lower-ranked interventions may require more conversations that acknowledge stakeholder concerns.

摘要

背景

医院决策者用于实施质量改进项目的资源有限。为了决定推进哪些干预措施,必须考虑权衡取舍,而这不可避免地取决于利益相关者的偏好。多标准决策分析(MCDA)方法可以使这一决策过程更加透明。

方法

进行了一项MCDA,以对四种可优化英格兰国家医疗服务体系(NHS)医院用药的干预措施进行排序,包括计算机化接口、建筑环境、书面沟通和面对面互动。最初,召集了一个由质量改进人员组成的核心小组(n = 10),根据实施研究综合框架确定可能影响推进哪些干预措施的标准。接下来,为了确定偏好权重,根据所有可能替代方案的潜在全对全排序方法,对不同的质量改进人员群体(n = 356)进行了偏好调查。然后,根据使用加法函数的未加权标准模型和根据参与者偏好加权的模型,计算四种干预类型的排序。通过1000次蒙特卡洛模拟迭代的概率敏感性分析估计不确定性。

结果

影响首选干预措施的最重要标准是它们是否满足“患者需求”(17.6%)以及其财务“成本”(11.5%)。干预措施的总分(满分30分的未加权分数|满分100%的加权分数)为:计算机化接口(25 | 83.8%)、建筑环境(24 | 79.6%)、书面沟通(22 | 71.6%)和面对面(22 | 67.8%)。概率敏感性分析表明,在不同程度的不确定性下,计算机化接口将是最受欢迎的干预措施。

结论

进行了一项MCDA,以对有望提高英格兰各医院用药优化水平的干预类型进行排序。排名最高的干预类型是计算机化接口。这一发现并不意味着计算机化接口干预措施是最有效的干预措施,但表明成功实施排名较低的干预措施可能需要更多承认利益相关者关切的对话。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/298b/10318338/a483a871c83e/frhs-03-1155523-g001.jpg

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