@article {Bellbmjqs-2021-013672, author = {Sigall K Bell and Fabienne Bourgeois and Catherine M DesRoches and Joe Dong and Kendall Harcourt and Stephen K Liu and Elizabeth Lowe and Patricia McGaffigan and Long H Ngo and Sandy A Novack and James D Ralston and Liz Salmi and Suz Schrandt and Sue Sheridan and Lauge Sokol-Hessner and Glenda Thomas and Eric J Thomas}, title = {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}, elocation-id = {bmjqs-2021-013672}, year = {2021}, doi = {10.1136/bmjqs-2021-013672}, publisher = {BMJ Publishing Group Ltd}, abstract = {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{\textquoteright}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{\textquoteright}s AC1 and Cohen{\textquoteright}s kappa statistic. We considered agreement coefficients 0.61{\textendash}0.8=good agreement and 0.81{\textendash}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breakdowns in each step of the diagnostic process, including missing or inaccurate main concerns and symptoms; missing/outdated test results; and communication breakdowns such as not feeling heard or misalignment between patient and provider about symptoms, events, or their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.}, issn = {2044-5415}, URL = {https://qualitysafety.bmj.com/content/early/2021/10/16/bmjqs-2021-013672}, eprint = {https://qualitysafety.bmj.com/content/early/2021/10/16/bmjqs-2021-013672.full.pdf}, journal = {BMJ Quality \& Safety} }