Procurement of patient medical records from multiple health care facilities for public health research: feasibility, challenges, and lessons learned.

health care facilities medical record procurement medical research

Journal

JAMIA open
ISSN: 2574-2531
Titre abrégé: JAMIA Open
Pays: United States
ID NLM: 101730643

Informations de publication

Date de publication:
Jul 2023
Historique:
received: 30 11 2022
revised: 03 05 2023
accepted: 05 06 2023
medline: 16 6 2023
pubmed: 16 6 2023
entrez: 16 6 2023
Statut: epublish

Résumé

Studies that combine medical record and primary data are typically conducted in a small number of health care facilities (HCFs) covering a limited catchment area; however, depending on the study objectives, validity may be improved by recruiting a more expansive sample of patients receiving care across multiple HCFs. We evaluate the feasibility of a novel protocol to obtain patient medical records from multiple HCFs using a broad representative sampling frame. In a prospective cohort study on HIV pre-exposure prophylaxis utilization, primary data were collected from a representative sample of community-dwelling participants; voluntary authorization was obtained to access participants' medical records from the HCF at which they were receiving care. Medical record procurement procedures were documented for later analysis. The cohort consisted of 460 participants receiving care from 122 HCFs; 81 participants were lost to follow-up resulting in 379 requests for medical records submitted to HCFs, and a total of 343 medical records were obtained (91% response rate). Less than 20% of the medical records received were in electronic form. On average, the cost of medical record acquisition was $120 USD per medical record. Obtaining medical record data on research participants receiving care across multiple HCFs was feasible, but time-consuming and resulted in appreciable missing data. Researchers combining primary data with medical record data should select a sampling and data collection approach that optimizes study validity while weighing the potential benefits (more representative sample; inclusion of HCF-level predictors) and drawbacks (cost, missing data) of obtaining medical records from multiple HCFs.

Identifiants

pubmed: 37323540
doi: 10.1093/jamiaopen/ooad040
pii: ooad040
pmc: PMC10264223
doi:

Types de publication

Journal Article

Langues

eng

Pagination

ooad040

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Déclaration de conflit d'intérêts

None declared.

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Auteurs

James M McMahon (JM)

School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.

Judith Brasch (J)

School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.

Eric Podsiadly (E)

School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.

Leilani Torres (L)

School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.

Robert Quiles (R)

School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.

Evette Ramos (E)

School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.

Hugh F Crean (HF)

School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.

Jessica E Haberer (JE)

Center for Global Health, Massachusetts General Hospital, Boston, Massachusetts, USA.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.

Classifications MeSH