US and Dutch Perspectives on the Use of COVID-19 Clinical Prediction Models: Findings from a Qualitative Analysis.

IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Medical Decision Making Pub Date : 2023-05-01 DOI:10.1177/0272989X231152852
Melissa J Basile, I R A Retel Helmrich, Jinny G Park, Jennifer Polo, Judith A C Rietjens, David van Klaveren, Theodoros P Zanos, Jason Nelson, Hester F Lingsma, David M Kent, Jelmer Alsma, R J C G Verdonschot, Negin Hajizadeh
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Abstract

Introduction: Clinical prediction models (CPMs) for coronavirus disease 2019 (COVID-19) may support clinical decision making, treatment, and communication. However, attitudes about using CPMs for COVID-19 decision making are unknown.

Methods: Online focus groups and interviews were conducted among health care providers, survivors of COVID-19, and surrogates (i.e., loved ones/surrogate decision makers) in the United States and the Netherlands. Semistructured questions explored experiences about clinical decision making in COVID-19 care and facilitators and barriers for implementing CPMs.

Results: In the United States, we conducted 4 online focus groups with 1) providers and 2) surrogates and survivors of COVID-19 between January 2021 and July 2021. In the Netherlands, we conducted 3 focus groups and 4 individual interviews with 1) providers and 2) surrogates and survivors of COVID-19 between May 2021 and July 2021. Providers expressed concern about CPM validity and the belief that patients may interpret CPM predictions as absolute. They described CPMs as potentially useful for resource allocation, triaging, education, and research. Several surrogates and people who had COVID-19 were not given prognostic estimates but believed this information would have supported and influenced their decision making. A limited number of participants felt the data would not have applied to them and that they or their loved ones may not have survived, as poor prognosis may have suggested withdrawal of treatment.

Conclusions: Many providers had reservations about using CPMs for people with COVID-19 due to concerns about CPM validity and patient-level interpretation of the outcome predictions. However, several people who survived COVID-19 and their surrogates indicated that they would have found this information useful for decision making. Therefore, information provision may be needed to improve provider-level comfort and patient and surrogate understanding of CPMs.

Highlights: While clinical prediction models (CPMs) may provide an objective means of assessing COVID-19 prognosis, provider concerns about CPM validity and the interpretation of CPM predictions may limit their clinical use.Providers felt that CPMs may be most useful for resource allocation, triage, research, or educational purposes for COVID-19.Several survivors of COVID-19 and their surrogates felt that CPMs would have been informative and may have aided them in making COVID-19 treatment decisions, while others felt the data would not have applied to them.

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美国和荷兰对COVID-19临床预测模型使用的看法:来自定性分析的结果。
2019冠状病毒病(COVID-19)的临床预测模型(cpm)可以支持临床决策、治疗和交流。然而,人们对在COVID-19决策中使用cpm的态度尚不清楚。方法:对美国和荷兰的医疗服务提供者、COVID-19幸存者和代孕者(即亲人/代孕决策者)进行在线焦点小组和访谈。半结构化问题探讨了COVID-19护理的临床决策经验以及实施cpm的促进因素和障碍。结果:在美国,我们在2021年1月至2021年7月期间进行了4个在线焦点小组,包括1)提供者和2)代理和COVID-19幸存者。在荷兰,我们在2021年5月至2021年7月期间对1)提供者和2)COVID-19的代理人和幸存者进行了3个焦点小组和4次个人访谈。提供者表达了对CPM有效性的担忧,并相信患者可能会将CPM预测解释为绝对的。他们认为cpm在资源分配、分类、教育和研究方面具有潜在的用处。几名代孕母亲和感染COVID-19的人没有得到预后估计,但他们认为这些信息会支持和影响他们的决策。有限数量的参与者认为这些数据不适用于他们,他们或他们的亲人可能无法幸存,因为预后不佳可能意味着放弃治疗。结论:由于担心CPM的有效性和患者对结果预测的解释,许多提供者对对COVID-19患者使用CPM持保留态度。然而,一些在COVID-19中幸存下来的人和他们的代理人表示,他们会发现这些信息对决策有用。因此,可能需要提供信息来提高提供者水平的舒适度以及患者和代理对cpm的理解。虽然临床预测模型(CPM)可以提供评估COVID-19预后的客观手段,但提供者对CPM有效性和CPM预测解释的担忧可能会限制其临床应用。供应商认为cpm可能对COVID-19的资源分配、分类、研究或教育目的最有用。一些COVID-19的幸存者和他们的代理人认为cpm本可以提供信息,并可能帮助他们做出COVID-19治疗决策,而其他人则认为这些数据不适用于他们。
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来源期刊
Medical Decision Making
Medical Decision Making 医学-卫生保健
CiteScore
6.50
自引率
5.60%
发文量
146
审稿时长
6-12 weeks
期刊介绍: Medical Decision Making offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health care policy development. Using the fundamentals of decision analysis and theory, economic evaluation, and evidence based quality assessment, Medical Decision Making presents both theoretical and practical statistical and modeling techniques and methods from a variety of disciplines.
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