Filling a gap in safety metrics: development of a patient-centred framework to identify and categorise patient-reported breakdowns related to the diagnostic process in ambulatory care.


Journal

BMJ quality & safety
ISSN: 2044-5423
Titre abrégé: BMJ Qual Saf
Pays: England
ID NLM: 101546984

Informations de publication

Date de publication:
07 2022
Historique:
received: 11 05 2021
accepted: 29 09 2021
pubmed: 18 10 2021
medline: 23 6 2022
entrez: 17 10 2021
Statut: ppublish

Résumé

Patients and families are important contributors to the diagnostic team, but their perspectives are not reflected in current diagnostic measures. Patients/families can identify some breakdowns in the diagnostic process beyond the clinician's view. We aimed to develop a framework with patients/families to help organisations identify and categorise patient-reported diagnostic process-related breakdowns (PRDBs) to inform organisational learning. A multi-stakeholder advisory group including patients, families, clinicians, and experts in diagnostic error, patient engagement and safety, and user-centred design, co-developed a framework for PRDBs in ambulatory care. We tested the framework using standard qualitative analysis methods with two physicians and one patient coder, analysing 2165 patient-reported ambulatory errors in two large surveys representing 25 425 US respondents. We tested intercoder reliability of breakdown categorisation using the Gwet's AC1 and Cohen's kappa statistic. We considered agreement coefficients 0.61-0.8=good agreement and 0.81-1.00=excellent agreement. The framework describes 7 patient-reported breakdown categories (with 40 subcategories), 19 patient-identified contributing factors and 11 potential patient-reported impacts. Patients identified breakdowns in each step of the diagnostic process, including missing or inaccurate main concerns and symptoms; missing/outdated test results; and communication breakdowns such as not feeling heard or misalignment between patient and provider about symptoms, events, or their significance. The frequency of PRDBs was 6.4% in one dataset and 6.9% in the other. Intercoder reliability showed good-to-excellent reliability in each dataset: AC1 0.89 (95% CI 0.89 to 0.90) to 0.96 (95% CI 0.95 to 0.97); kappa 0.64 (95% CI 0.62, to 0.66) to 0.85 (95% CI 0.83 to 0.88). The PRDB framework, developed in partnership with patients/families, can help organisations identify and reliably categorise PRDBs, including some that are invisible to clinicians; guide interventions to engage patients and families as diagnostic partners; and inform whole organisational learning.

Sections du résumé

BACKGROUND
Patients and families are important contributors to the diagnostic team, but their perspectives are not reflected in current diagnostic measures. Patients/families can identify some breakdowns in the diagnostic process beyond the clinician's view. We aimed to develop a framework with patients/families to help organisations identify and categorise patient-reported diagnostic process-related breakdowns (PRDBs) to inform organisational learning.
METHOD
A multi-stakeholder advisory group including patients, families, clinicians, and experts in diagnostic error, patient engagement and safety, and user-centred design, co-developed a framework for PRDBs in ambulatory care. We tested the framework using standard qualitative analysis methods with two physicians and one patient coder, analysing 2165 patient-reported ambulatory errors in two large surveys representing 25 425 US respondents. We tested intercoder reliability of breakdown categorisation using the Gwet's AC1 and Cohen's kappa statistic. We considered agreement coefficients 0.61-0.8=good agreement and 0.81-1.00=excellent agreement.
RESULTS
The framework describes 7 patient-reported breakdown categories (with 40 subcategories), 19 patient-identified contributing factors and 11 potential patient-reported impacts. Patients identified breakdowns in each step of the diagnostic process, including missing or inaccurate main concerns and symptoms; missing/outdated test results; and communication breakdowns such as not feeling heard or misalignment between patient and provider about symptoms, events, or their significance. The frequency of PRDBs was 6.4% in one dataset and 6.9% in the other. Intercoder reliability showed good-to-excellent reliability in each dataset: AC1 0.89 (95% CI 0.89 to 0.90) to 0.96 (95% CI 0.95 to 0.97); kappa 0.64 (95% CI 0.62, to 0.66) to 0.85 (95% CI 0.83 to 0.88).
CONCLUSIONS
The PRDB framework, developed in partnership with patients/families, can help organisations identify and reliably categorise PRDBs, including some that are invisible to clinicians; guide interventions to engage patients and families as diagnostic partners; and inform whole organisational learning.

Identifiants

pubmed: 34656982
pii: bmjqs-2021-013672
doi: 10.1136/bmjqs-2021-013672
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Pagination

526-540

Subventions

Organisme : AHRQ HHS
ID : R01 HS027367
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

Auteurs

Sigall K Bell (SK)

Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA sbell1@bidmc.harvard.edu.

Fabienne Bourgeois (F)

Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Catherine M DesRoches (CM)

Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

Joe Dong (J)

Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

Kendall Harcourt (K)

Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

Stephen K Liu (SK)

Department of Medicine, Dartmouth College Geisel School of Medicine, Hanover, New Hampshire, USA.

Elizabeth Lowe (E)

Patient and Family Advisory Council, Department of Social Work, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

Patricia McGaffigan (P)

Institute for Healthcare Improvement, Boston, Massachusetts, USA.

Long H Ngo (LH)

Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

Sandy A Novack (SA)

Patient and Family Advisory Council, Department of Social Work, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

James D Ralston (JD)

Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA.

Liz Salmi (L)

Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

Suz Schrandt (S)

Society to Improve Diagnosis in Medicine, Evanston, Illinois, USA.

Sue Sheridan (S)

Society to Improve Diagnosis in Medicine, Evanston, Illinois, USA.

Lauge Sokol-Hessner (L)

Department of Medicine and Department of Health Care Quality, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

Glenda Thomas (G)

Patient and Family Advisory Council, Department of Social Work, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

Eric J Thomas (EJ)

Department of Medicine, University of Texas McGovern Medical School, Houston, Texas, USA.
Healthcare Quality and Safety, Memorial Hermann Texas Medical Center, Houston, Texas, USA.

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