Using Real-world Data for Decision Support: Recommendations from a Primary Care Provider Survey.


Journal

The Permanente journal
ISSN: 1552-5775
Titre abrégé: Perm J
Pays: United States
ID NLM: 9800474

Informations de publication

Date de publication:
05 2021
Historique:
entrez: 10 5 2021
pubmed: 11 5 2021
medline: 16 10 2021
Statut: ppublish

Résumé

The use of data from wearable sensors, smartphones, and apps holds promise as a clinical decision-making tool in health and mental health in primary care medicine. The aim of this study was to determine provider perspectives about the utility of these data for building digitally based decision-making tools. This mixed quantitative and qualitative cross-sectional survey of a convenience sample of primary-care clinicians at Kaiser Permanente Northwest was conducted between April and July 2019 online via Institute for Translational Health Sciences' Research Electronic Data Capture. Study outcomes were 1) attitudes toward digital data, 2) willingness to use digital data to support clinical decision making, and 3) concerns and recommendations about implementing a digital tool for clinical decision making. This sample of 131 clinicians was largely white (n = 98) female (n = 91) physicians (n = 86). Although respondents (75.7%, n = 87) had a positive attitude toward using digital tools in their practice, 88 respondents (67.3%) voiced concerns about the possible lack of clinical utility, suspected difficulty in integration with clinical workflows, and worried about the potential burden placed on patients. Participants indicated that the accuracy of the data in detecting the need for treatment adjustments would need to be high and the tool should be clinically tested. Primary care providers find value in collecting real-world patient data to assist in clinical decision making, provided such information does not interfere with provider workflow or impose undue burden on patients. In addition, digital tools will need to demonstrate high accuracy, be able to integrate into current clinical workflows, and maintain the privacy and security of patients' data.

Identifiants

pubmed: 33970071
doi: 10.7812/TPP/20.213
pmc: PMC8817910
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NCATS NIH HHS
ID : KL2 TR002317
Pays : United States
Organisme : NCATS NIH HHS
ID : TL1 TR002318
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR002319
Pays : United States

Informations de copyright

Copyright © 2021 The Permanente Press. All rights reserved.

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Auteurs

Patricia A Areán (PA)

Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA.
ALACRITY Center, University of Washington, Seattle, WA.

Emily C Friedman (EC)

ALACRITY Center, University of Washington, Seattle, WA.

Abhishek Pratap (A)

Sage Bionetworks, Seattle, WA.

Ryan Allred (R)

Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA.

Jaden Duffy (J)

Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA.

Sara Gille (S)

Kaiser Permanente Center for Health Research, Portland, OR.

Shelley Reetz (S)

Kaiser Permanente Center for Health Research, Portland, OR.

Erin Keast (E)

Kaiser Permanente Center for Health Research, Portland, OR.

Gregory Clarke (G)

Kaiser Permanente Center for Health Research, Portland, OR.

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