Inviting patients to identify diagnostic concerns through structured evaluation of their online visit notes.
OpenNotes
communication
diagnostic errors
patient experience
patient safety
Journal
Journal of the American Medical Informatics Association : JAMIA
ISSN: 1527-974X
Titre abrégé: J Am Med Inform Assoc
Pays: England
ID NLM: 9430800
Informations de publication
Date de publication:
11 05 2022
11 05 2022
Historique:
received:
12
07
2021
revised:
03
02
2022
accepted:
08
03
2022
pubmed:
30
3
2022
medline:
18
5
2022
entrez:
29
3
2022
Statut:
ppublish
Résumé
The 21st Century Cures Act mandates patients' access to their electronic health record (EHR) notes. To our knowledge, no previous work has systematically invited patients to proactively report diagnostic concerns while documenting and tracking their diagnostic experiences through EHR-based clinician note review. To test if patients can identify concerns about their diagnosis through structured evaluation of their online visit notes. In a large integrated health system, patients aged 18-85 years actively using the patient portal and seen between October 2019 and February 2020 were invited to respond to an online questionnaire if an EHR algorithm detected any recent unexpected return visit following an initial primary care consultation ("at-risk" visit). We developed and tested an instrument (Safer Dx Patient Instrument) to help patients identify concerns related to several dimensions of the diagnostic process based on notes review and recall of recent "at-risk" visits. Additional questions assessed patients' trust in their providers and their general feelings about the visit. The primary outcome was a self-reported diagnostic concern. Multivariate logistic regression tested whether the primary outcome was predicted by instrument variables. Of 293 566 visits, the algorithm identified 1282 eligible patients, of whom 486 responded. After applying exclusion criteria, 418 patients were included in the analysis. Fifty-one patients (12.2%) identified a diagnostic concern. Patients were more likely to report a concern if they disagreed with statements "the care plan the provider developed for me addressed all my medical concerns" [odds ratio (OR), 2.65; 95% confidence interval [CI], 1.45-4.87) and "I trust the provider that I saw during my visit" (OR, 2.10; 95% CI, 1.19-3.71) and agreed with the statement "I did not have a good feeling about my visit" (OR, 1.48; 95% CI, 1.09-2.01). Patients can identify diagnostic concerns based on a proactive online structured evaluation of visit notes. This surveillance strategy could potentially improve transparency in the diagnostic process.
Sections du résumé
BACKGROUND
The 21st Century Cures Act mandates patients' access to their electronic health record (EHR) notes. To our knowledge, no previous work has systematically invited patients to proactively report diagnostic concerns while documenting and tracking their diagnostic experiences through EHR-based clinician note review.
OBJECTIVE
To test if patients can identify concerns about their diagnosis through structured evaluation of their online visit notes.
METHODS
In a large integrated health system, patients aged 18-85 years actively using the patient portal and seen between October 2019 and February 2020 were invited to respond to an online questionnaire if an EHR algorithm detected any recent unexpected return visit following an initial primary care consultation ("at-risk" visit). We developed and tested an instrument (Safer Dx Patient Instrument) to help patients identify concerns related to several dimensions of the diagnostic process based on notes review and recall of recent "at-risk" visits. Additional questions assessed patients' trust in their providers and their general feelings about the visit. The primary outcome was a self-reported diagnostic concern. Multivariate logistic regression tested whether the primary outcome was predicted by instrument variables.
RESULTS
Of 293 566 visits, the algorithm identified 1282 eligible patients, of whom 486 responded. After applying exclusion criteria, 418 patients were included in the analysis. Fifty-one patients (12.2%) identified a diagnostic concern. Patients were more likely to report a concern if they disagreed with statements "the care plan the provider developed for me addressed all my medical concerns" [odds ratio (OR), 2.65; 95% confidence interval [CI], 1.45-4.87) and "I trust the provider that I saw during my visit" (OR, 2.10; 95% CI, 1.19-3.71) and agreed with the statement "I did not have a good feeling about my visit" (OR, 1.48; 95% CI, 1.09-2.01).
CONCLUSION
Patients can identify diagnostic concerns based on a proactive online structured evaluation of visit notes. This surveillance strategy could potentially improve transparency in the diagnostic process.
Identifiants
pubmed: 35348688
pii: 6555291
doi: 10.1093/jamia/ocac036
pmc: PMC9093029
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, P.H.S.
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1091-1100Subventions
Organisme : Office of Academic Affiliations VA Advanced Fellowship Program in HSR&D
Organisme : VA HSR&D Service
ID : IIR 17-127
Organisme : Houston Veterans Administration (VA) Health Services Research and Development
Organisme : Agency for Healthcare Research and Quality Mentored Career Development Award
ID : K01-HS025474
Organisme : Houston Veterans Administration (VA) Health Services Research and Development (HSR&D) Center for Innovations in Quality
Organisme : AHRQ HHS
ID : K01 HS025474
Pays : United States
Organisme : Agency for Healthcare Research and Quality (R01HS27363), the Gordon and Betty Moore Foundation
ID : GBMF 8838
Organisme : Effectiveness and Safety
ID : CIN 13-413
Organisme : Presidential Early Career Award for Scientists and Engineers USA
ID : 14-274
Organisme : Gordon and Betty Moore Foundation
ID : GBMF 5498
Organisme : CanTest Research Collaborative funded by a Cancer Research UK Population Research Catalyst award
ID : C8640/A23385
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association.
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