RT Journal Article
SR Electronic
T1 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
JF BMJ Quality & Safety
JO BMJ Qual Saf
FD BMJ Publishing Group Ltd
SP bmjqs-2021-013672
DO 10.1136/bmjqs-2021-013672
A1 Sigall K Bell
A1 Fabienne Bourgeois
A1 Catherine M DesRoches
A1 Joe Dong
A1 Kendall Harcourt
A1 Stephen K Liu
A1 Elizabeth Lowe
A1 Patricia McGaffigan
A1 Long H Ngo
A1 Sandy A Novack
A1 James D Ralston
A1 Liz Salmi
A1 Suz Schrandt
A1 Sue Sheridan
A1 Lauge Sokol-Hessner
A1 Glenda Thomas
A1 Eric J Thomas
YR 2021
UL http://qualitysafety.bmj.com/content/early/2021/10/16/bmjqs-2021-013672.abstract
AB 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breakdowns in each step of the diagnostic process, including missing or inaccurate main concerns and symptoms; missing/outdated test results; and communication breakdowns such as not feeling heard or misalignment between patient and provider about symptoms, events, or their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.Data may be obtained from a third party and are not publicly available.