Creating more comparable cohorts in observational palliative care studies: A proposed framework to improve applicability and replicability of research.

Palliative care applicability heterogeneity of populations non-randomised studies observational studies reproducibility

Journal

Palliative medicine
ISSN: 1477-030X
Titre abrégé: Palliat Med
Pays: England
ID NLM: 8704926

Informations de publication

Date de publication:
07 Mar 2024
Historique:
medline: 8 3 2024
pubmed: 8 3 2024
entrez: 8 3 2024
Statut: aheadofprint

Résumé

Palliative care is characterised by heterogeneous patient and caregiver populations who are provided care in different health systems and a research base including a large proportion of observational, mostly retrospective studies. The inherent diversity of palliative care populations and the often inadequate study descriptions challenge the application of new knowledge into practice and reproducibility for confirmatory studies. Being able to define systematically study populations would significantly increase their generalisability and effective translation into practice. Based on an informal consensus process by active palliative care researchers challenged by this problem and a review of the current evidence, we propose an approach to creating more comparable cohorts in observational (non-randomised) palliative care studies that relies on defining the study population in relation to a fixed, well-defined event from which analyses are built ('anchoring'). In addition to providing a detailed and complete description of the study population, anchoring is Anchoring the cohort to reproducible data points will help create more comparable cohorts in palliative care whilst mitigating its inherent heterogeneity. This, in turn, will help optimise the generalisability, applicability and reproducibility of observational palliative care studies to strengthen the evidence base and improve practice.

Sections du résumé

BACKGROUND UNASSIGNED
Palliative care is characterised by heterogeneous patient and caregiver populations who are provided care in different health systems and a research base including a large proportion of observational, mostly retrospective studies. The inherent diversity of palliative care populations and the often inadequate study descriptions challenge the application of new knowledge into practice and reproducibility for confirmatory studies. Being able to define systematically study populations would significantly increase their generalisability and effective translation into practice.
PROPOSAL UNASSIGNED
Based on an informal consensus process by active palliative care researchers challenged by this problem and a review of the current evidence, we propose an approach to creating more comparable cohorts in observational (non-randomised) palliative care studies that relies on defining the study population in relation to a fixed, well-defined event from which analyses are built ('anchoring'). In addition to providing a detailed and complete description of the study population, anchoring is
DISCUSSION UNASSIGNED
Anchoring the cohort to reproducible data points will help create more comparable cohorts in palliative care whilst mitigating its inherent heterogeneity. This, in turn, will help optimise the generalisability, applicability and reproducibility of observational palliative care studies to strengthen the evidence base and improve practice.

Identifiants

pubmed: 38454317
doi: 10.1177/02692163241234227
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2692163241234227

Déclaration de conflit d'intérêts

Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Auteurs

Slavica Kochovska (S)

Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, NSW, Australia.

Fliss Em Murtagh (FE)

Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, UK.

Meera Agar (M)

IMPACCT, Faculty of Health, University of Technology Sydney, Ultimo, NSW, Australia.

Jane L Phillips (JL)

School of Nursing, Faculty of Health, University of Technology Queensland, Brisbane, QLD, Australia.

Deborah Dudgeon (D)

Department of Medicine, Queen's University, Kingston, ON, Canada.

Sanja Lujic (S)

Centre for Big Data Research in Health, University of New South Wales, Sydney, NSW, Australia.

Miriam J Johnson (MJ)

Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, UK.

David C Currow (DC)

Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, NSW, Australia.

Classifications MeSH