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Wonderings to research questions: Engaging patients in long COVID research prioritization within a learning health system.
Kennedy, Ann Blair; Mitcham, Ariana; Parris, Katherine; Albertson, Faith; Sanchez Ferrer, Luis; O'Boyle, Conor; Patel, Maushmi K; Gartner, Tracey; Broomer, Amy M; Katzman, Evan; Coffin, Jeanette; Grier, Jennifer T; Natafgi, Nabil.
Afiliação
  • Kennedy AB; Biomedical Sciences University of South Carolina School of Medicine Greenville South Carolina USA.
  • Mitcham A; Family Medicine Prisma Health Greenville South Carolina USA.
  • Parris K; Patient Engagement Studio, University of South Carolina Greenville South Carolina USA.
  • Albertson F; Patient Engagement Studio, University of South Carolina Greenville South Carolina USA.
  • Sanchez Ferrer L; Health Services Policy and Management, University of South Carolina Arnold School of Public Health Columbia South Carolina USA.
  • O'Boyle C; Patient Engagement Studio, University of South Carolina Greenville South Carolina USA.
  • Patel MK; Health Services Policy and Management, University of South Carolina Arnold School of Public Health Columbia South Carolina USA.
  • Gartner T; Neurodevelopmental Disorders Lab University of South Carolina College of Art and Sciences Columbia South Carolina USA.
  • Broomer AM; University of South Carolina Honors College Columbia South Carolina USA.
  • Katzman E; Biomedical Sciences University of South Carolina School of Medicine Greenville South Carolina USA.
  • Coffin J; Patient Engagement Studio, University of South Carolina Greenville South Carolina USA.
  • Grier JT; Biomedical Sciences University of South Carolina School of Medicine Greenville South Carolina USA.
  • Natafgi N; Patient Engagement Studio, University of South Carolina Greenville South Carolina USA.
Learn Health Syst ; 8(Suppl 1): e10410, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38883877
ABSTRACT

Background:

An integral component of research within a learning health system is patient engagement at all stages of the research process. While there are well-defined best practices for engaging with patients on predetermined research questions, there is little specific methodology for engaging patients at the stage of research question formation and prioritization. Further, with an emerging disease such as Long COVID, population-specific strategies for meaningful engagement have not been characterized.

Methods:

The COVID-19 Focused Virtual Patient Engagement Studio (CoVIP studio) was a virtual panel created to facilitate patient-centered studies surrounding the effects of long-term COVID ("Long COVID") also known as post-acute SARS-CoV-2 syndrome (PASC). A diverse group of panelists was recruited and trained in several different areas of knowledge, competencies, and abilities regarding research and Long COVID. A three-step approach was developed that consisted of recording panelists' broad wonderings to generate patient-specific research questions.

Results:

The "wonderings" discussed in panelists' training sessions were analyzed to identify specific populations, interventions, comparators, outcomes, and timeframes (PICOT) elements, which were then used to create a survey to identify the elements of greatest importance to the panel. Based on the findings, 10 research questions were formulated using the PICOT format. The panelists then ranked the questions on perceived order of importance and distributed one million fictional grant dollars between the five chosen questions in the second survey. Through this stepwise prioritization process, the project team successfully translated panelists' research wonderings into investigable research questions.

Conclusion:

This methodology has implications for the advancement of patient-engaged prioritization both within the scope of Long COVID research and in research on other rare or emerging diseases.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Learn Health Syst Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Learn Health Syst Ano de publicação: 2024 Tipo de documento: Article