Clinical implementation of suicide risk prediction models in healthcare: a qualitative study.
Clinical implementation of suicide risk prediction models in healthcare: a qualitative study.
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DOI：
10.1186/s12888-022-04400-5
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发表时间：
2022-12-14
期刊：
影响因子：
4.4
通讯作者：
中科院分区：
文献类型：
--
作者：
从电子健康记录(EHR)衍生的自杀风险预测模型是自杀预防方面的一项新创新，但几乎没有证据来指导其实施。在这项定性研究中，采访了来自一个卫生系统的30名临床医生和10名卫生保健管理人员，他们预计将实施自动化的EHR衍生自杀风险预测模型，而两个卫生系统将试验不同的实施方法。现场量身定做的访谈指南侧重于受访者对自杀风险预测模型在临床实践中的期望和经验，以及改进实施的建议。访谈提示和内容分析由实施研究综合框架(CFIR)结构指导。管理人员和临床医生发现使用自杀风险预测模型和两种实施方法是可以接受的。临床医生希望有机会及早接受、实施决策和反馈。他们想更好地了解这种风险识别方式如何增强现有的自杀预防努力。他们还希望进行额外的培训，以了解该模型是如何确定风险的，特别是在他们希望看到的被该模型识别的患者没有被标记为风险以及他们没有期望看到的患者被识别之后。临床医生担心有足够的自杀预防资源来应对潜在增加的需求，并担心他们的个人责任；他们希望在无法接触到患者或患者在持续一段时间内仍处于危险之中的情况下采取明确的程序。使风险模型工作流程更有效率和更少负担的建议包括将自杀风险信息整合到EHR的专用模块中，并在临床笔记中填充风险评估分数和文本。考虑实施自杀风险模型的卫生系统应在流程的早期让临床医生参与，以确保他们了解风险模型如何评估风险并为现有工作流程增加价值，明确临床医生的角色期望，并在电子病历中方便的位置汇总风险信息，以支持高质量的患者护理。网上版载有补充材料，可在10.1186/s12888-022-04400-5查阅。
Suicide risk prediction models derived from electronic health records (EHR) are a novel innovation in suicide prevention but there is little evidence to guide their implementation. In this qualitative study, 30 clinicians and 10 health care administrators were interviewed from one health system anticipating implementation of an automated EHR-derived suicide risk prediction model and two health systems piloting different implementation approaches. Site-tailored interview guides focused on respondents’ expectations for and experiences with suicide risk prediction models in clinical practice, and suggestions for improving implementation. Interview prompts and content analysis were guided by Consolidated Framework for Implementation Research (CFIR) constructs. Administrators and clinicians found use of the suicide risk prediction model and the two implementation approaches acceptable. Clinicians desired opportunities for early buy-in, implementation decision-making, and feedback. They wanted to better understand how this manner of risk identification enhanced existing suicide prevention efforts. They also wanted additional training to understand how the model determined risk, particularly after patients they expected to see identified by the model were not flagged at-risk and patients they did not expect to see identified were. Clinicians were concerned about having enough suicide prevention resources for potentially increased demand and about their personal liability; they wanted clear procedures for situations when they could not reach patients or when patients remained at-risk over a sustained period. Suggestions for making risk model workflows more efficient and less burdensome included consolidating suicide risk information in a dedicated module in the EHR and populating risk assessment scores and text in clinical notes. Health systems considering suicide risk model implementation should engage clinicians early in the process to ensure they understand how risk models estimate risk and add value to existing workflows, clarify clinician role expectations, and summarize risk information in a convenient place in the EHR to support high-quality patient care. The online version contains supplementary material available at 10.1186/s12888-022-04400-5.
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DOI：
10.1186/1748-5908-4-50
发表时间：
2009-08-07
期刊：
Implementation science : IS
影响因子：
--
作者：
Damschroder LJ;Aron DC;Keith RE;Kirsh SR;Alexander JA;Lowery JC
通讯作者：
Lowery JC
影响因子：
3.8
作者：
Reger, Greg M.;McClure, Mary Lou;Reger, Mark A.
通讯作者：
Reger, Mark A.
影响因子：
17.7
作者：
Simon, Gregory E.;Stewart, Christine;Carrell, David S.
通讯作者：
Carrell, David S.
影响因子：
15.1
作者：
Sanderson, Michael;Bulloch, Andrew G. M.;Patten, Scott B.
通讯作者：
Patten, Scott B.
影响因子：
22.4
作者：
Franklin, Joseph C.;Ribeiro, Jessica D.;Nock, Matthew K.
通讯作者：
Nock, Matthew K.