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US and Dutch Perspectives on the Use of COVID-19 Clinical Prediction Models: Findings from a Qualitative Analysis.
Basile, Melissa J; Helmrich, I R A Retel; Park, Jinny G; Polo, Jennifer; Rietjens, Judith A C; van Klaveren, David; Zanos, Theodoros P; Nelson, Jason; Lingsma, Hester F; Kent, David M; Alsma, Jelmer; Verdonschot, R J C G; Hajizadeh, Negin.
  • Basile MJ; Institute of Health System Science, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
  • Helmrich IRAR; Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands.
  • Park JG; Institute of Health System Science, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
  • Polo J; Predictive Analytics and Comparative Effectiveness (PACE) Center at the Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA.
  • van Klaveren D; Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands.
  • Zanos TP; Predictive Analytics and Comparative Effectiveness (PACE) Center at the Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA.
  • Nelson J; Predictive Analytics and Comparative Effectiveness (PACE) Center at the Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA.
  • Lingsma HF; Institute of Health System Science, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
  • Kent DM; Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
  • Alsma J; Predictive Analytics and Comparative Effectiveness (PACE) Center at the Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA.
  • Verdonschot RJCG; Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands.
  • Hajizadeh N; Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands.
Med Decis Making ; 43(4): 445-460, 2023 05.
Статья в английский | MEDLINE | ID: covidwho-2239028
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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Полный текст: Имеется в наличии Коллекция: Международные базы данных база данных: MEDLINE Основная тема: Decision Making / COVID-19 Тип исследования: Экспериментальные исследования / Прогностическое исследование / Качественное исследование / Рандомизированные контролируемые испытания Пределы темы: Люди Язык: английский Журнал: Med Decis Making Год: 2023 Тип: Статья Аффилированная страна: 0272989x231152852

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Полный текст: Имеется в наличии Коллекция: Международные базы данных база данных: MEDLINE Основная тема: Decision Making / COVID-19 Тип исследования: Экспериментальные исследования / Прогностическое исследование / Качественное исследование / Рандомизированные контролируемые испытания Пределы темы: Люди Язык: английский Журнал: Med Decis Making Год: 2023 Тип: Статья Аффилированная страна: 0272989x231152852