TY - JOUR
T1 - Adverse diagnostic events in hospitalised patients
T2 - A single-centre, retrospective cohort study
AU - Dalal, Anuj K.
AU - Plombon, Savanna
AU - Konieczny, Kaitlyn
AU - Motta-Calderon, Daniel
AU - Malik, Maria
AU - Garber, Alison
AU - Lam, Alyssa
AU - Piniella, Nicholas
AU - Leeson, Marie
AU - Garabedian, Pamela
AU - Goyal, Abhishek
AU - Roulier, Stephanie
AU - Yoon, Cathy
AU - Fiskio, Julie M.
AU - Schnock, Kumiko O.
AU - Rozenblum, Ronen
AU - Griffin, Jacqueline
AU - Schnipper, Jeffrey L.
AU - Lipsitz, Stuart
AU - Bates, David W.
AU - Lee, David
AU - Palazuelos, Daniel
AU - Serna, Myrna Katalina
AU - Kozak, Anne
AU - O'Brien, Khelsea
AU - Shah, Shela
AU - Wazir, Mohammed
AU - Cortas, Chadi
AU - Yang, Caroline
N1 - Publisher Copyright:
© Author(s) (or their employer(s)) 2025.
PY - 2025/6/1
Y1 - 2025/6/1
N2 - Background Adverse event surveillance approaches underestimate the prevalence of harmful diagnostic errors (DEs) related to hospital care. Methods We conducted a single-centre, retrospective cohort study of a stratified sample of patients hospitalised on general medicine using four criteria: transfer to intensive care unit (ICU), death within 90 days, complex clinical events, and none of the aforementioned high-risk criteria. Cases in higher-risk subgroups were over-sampled in predefined percentages. Each case was reviewed by two adjudicators trained to judge the likelihood of DE using the Safer Dx instrument; characterise harm, preventability and severity; and identify associated process failures using the Diagnostic Error Evaluation and Research Taxonomy modified for acute care. Cases with discrepancies or uncertainty about DE or impact were reviewed by an expert panel. We used descriptive statistics to report population estimates of harmful, preventable and severely harmful DEs by demographic variables based on the weighted sample, and characteristics of harmful DEs. Multivariable models were used to adjust association of process failures with harmful DEs. Results Of 9147 eligible cases, 675 were randomly sampled within each subgroup: 100% of ICU transfers, 38.5% of deaths within 90 days, 7% of cases with complex clinical events and 2.4% of cases without high-risk criteria. Based on the weighted sample, the population estimates of harmful, preventable and severely harmful DEs were 7.2% (95% CI 4.66 to 9.80), 6.1% (95% CI 3.79 to 8.50) and 1.1% (95% CI 0.55 to 1.68), respectively. Harmful DEs were frequently characterised as delays (61.9%). Severely harmful DEs were frequent in high-risk cases (55.1%). In multivariable models, process failures in assessment, diagnostic testing, subspecialty consultation, patient experience, and history were significantly associated with harmful DEs. Conclusions We estimate that a harmful DE occurred in 1 of every 14 patients hospitalised on general medicine, the majority of which were preventable. Our findings underscore the need for novel approaches for adverse DE surveillance.
AB - Background Adverse event surveillance approaches underestimate the prevalence of harmful diagnostic errors (DEs) related to hospital care. Methods We conducted a single-centre, retrospective cohort study of a stratified sample of patients hospitalised on general medicine using four criteria: transfer to intensive care unit (ICU), death within 90 days, complex clinical events, and none of the aforementioned high-risk criteria. Cases in higher-risk subgroups were over-sampled in predefined percentages. Each case was reviewed by two adjudicators trained to judge the likelihood of DE using the Safer Dx instrument; characterise harm, preventability and severity; and identify associated process failures using the Diagnostic Error Evaluation and Research Taxonomy modified for acute care. Cases with discrepancies or uncertainty about DE or impact were reviewed by an expert panel. We used descriptive statistics to report population estimates of harmful, preventable and severely harmful DEs by demographic variables based on the weighted sample, and characteristics of harmful DEs. Multivariable models were used to adjust association of process failures with harmful DEs. Results Of 9147 eligible cases, 675 were randomly sampled within each subgroup: 100% of ICU transfers, 38.5% of deaths within 90 days, 7% of cases with complex clinical events and 2.4% of cases without high-risk criteria. Based on the weighted sample, the population estimates of harmful, preventable and severely harmful DEs were 7.2% (95% CI 4.66 to 9.80), 6.1% (95% CI 3.79 to 8.50) and 1.1% (95% CI 0.55 to 1.68), respectively. Harmful DEs were frequently characterised as delays (61.9%). Severely harmful DEs were frequent in high-risk cases (55.1%). In multivariable models, process failures in assessment, diagnostic testing, subspecialty consultation, patient experience, and history were significantly associated with harmful DEs. Conclusions We estimate that a harmful DE occurred in 1 of every 14 patients hospitalised on general medicine, the majority of which were preventable. Our findings underscore the need for novel approaches for adverse DE surveillance.
KW - Adverse events, epidemiology and detection
KW - Diagnostic errors
KW - Hospital medicine
KW - Information technology
KW - Patient safety
UR - https://www.scopus.com/pages/publications/85206343015
UR - https://www.scopus.com/inward/citedby.url?scp=85206343015&partnerID=8YFLogxK
U2 - 10.1136/bmjqs-2024-017183
DO - 10.1136/bmjqs-2024-017183
M3 - Article
C2 - 39353737
AN - SCOPUS:85206343015
SN - 2044-5415
VL - 34
SP - 377
EP - 388
JO - BMJ Quality and Safety
JF - BMJ Quality and Safety
IS - 6
ER -