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

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

Research output: Contribution to journalArticleAcademicpeer-review

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. 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.

Original languageEnglish
Article number272989X231152852
Pages (from-to)445-460
Number of pages16
JournalMedical Decision Making
Volume43
Issue number4
Early online date9 Feb 2023
DOIs
Publication statusPublished - May 2023

Bibliographical note

Funding Information:
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support for this study was provided in part by a grant from Tufts Medical Center, whereby research reported in this work was funded through a COVID-19 Enhancement to a Patient-Centered Outcomes Research Institute (PCORI) award (ME-1606-35555; the statements in this work are solely the responsibility of the authors and do not necessarily represent the views of the PCORI, its Board of Governors, or the Methodology Committee), and Erasmus Medical Center, the Netherlands. This work was supported by ZonMw (project No. 10430 01 201 0019: Clinical Prediction Models for COVID-19: Development, International Validation, and Use) and the PCORI (grant No. ME-1606–35555: How Well Do Clinical Prediction Models [CPMs] Validate? A Large-Scale Evaluation of Cardiovascular Clinical Prediction Models). This work was supported by the National Institute on Aging of the National Institutes of Health (grant No. R24AG064191). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. All authors are independent from funders and had full access to all of the data (including statistical reports and tables) in the study and can take responsibility for the integrity of the data and the accuracy of the data analysis. The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. None of the authors are employed by the sponsor.

Publisher Copyright:
© The Author(s) 2023.

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