Diagnostic Error

2022 ◽  
Vol 38 (1) ◽  
pp. 1-10
Author(s):  
Grant Shafer ◽  
Kanekal Suresh Gautham
Keyword(s):  
1973 ◽  
Vol 12 (02) ◽  
pp. 108-113 ◽  
Author(s):  
P. W. Gill ◽  
D. J. Leaper ◽  
P. J. Guillou ◽  
J. R. Staniland ◽  
J. C. Horhocks ◽  
...  

This report describes an evaluation of »observer variation« in history taking and examination of patients with abdominal pain. After an initial survey in which the degree of observer variation amongst the present authors fully confirmed previous rather gloomy forecasts, a system of »agreed definitions« was produced, and further studies showed a rapid and considerable fall in the degree of observer variation between the data recorded by the same authors. Finally, experience with a computer-based diagnostic system using the same system of agreed definitions showed the maximum diagnostic error rate due to faulty acquisition of data to be low (4.7°/o in a series of 552 cases). It is suggested as a result of these studies that — at least in respect of abdominal pain — errors in data acquisition by the clinician need not be the prime cause of faulty diagnoses.


Diagnosis ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Justin B. Searns ◽  
Manon C. Williams ◽  
Christine E. MacBrayne ◽  
Ann L. Wirtz ◽  
Jan E. Leonard ◽  
...  

AbstractObjectivesFew studies describe the impact of antimicrobial stewardship programs (ASPs) on recognizing and preventing diagnostic errors. Handshake stewardship (HS-ASP) is a novel ASP model that prospectively reviews hospital-wide antimicrobial usage with recommendations made in person to treatment teams. The purpose of this study was to determine if HS-ASP could identify and intervene on potential diagnostic errors for children hospitalized at a quaternary care children’s hospital.MethodsPreviously self-identified “Great Catch” (GC) interventions by the Children’s Hospital Colorado HS-ASP team from 10/2014 through 5/2018 were retrospectively reviewed. Each GC was categorized based on the types of recommendations from HS-ASP, including if any diagnostic recommendations were made to the treatment team. Each GC was independently scored using the “Safer Dx Instrument” to determine presence of diagnostic error based on a previously determined cut-off score of ≤1.50. Interrater reliability for the instrument was measured using a randomized subset of one third of GCs.ResultsDuring the study period, there were 162 GC interventions. Of these, 65 (40%) included diagnostic recommendations by HS-ASP and 19 (12%) had a Safer Dx Score of ≤1.50, (Κ=0.44; moderate agreement). Of those GCs associated with diagnostic errors, the HS-ASP team made a diagnostic recommendation to the primary treatment team 95% of the time.ConclusionsHandshake stewardship has the potential to identify and intervene on diagnostic errors for hospitalized children.


Diagnosis ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 265-272
Author(s):  
Sandra Monteiro ◽  
Jonathan Sherbino ◽  
Jonathan S. Ilgen ◽  
Emily M. Hayden ◽  
Elizabeth Howey ◽  
...  

AbstractObjectivesDiagnostic reasoning has been shown to be influenced by a prior similar patient case. However, it is unclear whether this process influences diagnostic error rates or whether clinicians at all experience levels are equally susceptible. The present study measured the influence of specific prior exposure and experience level on diagnostic accuracy.MethodsTo create the experience of prior exposure, participants (pre-clerkship medical students, emergency medicine residents, and faculty) first verified diagnoses of clinical vignettes. The influence of prior exposures was measured using equiprobable clinical vignettes; indicating two diagnoses. Participants diagnosed equiprobable cases that were: 1) matched to exposure cases (in one of three conditions: a) similar patient features, similar clinical features; b) dissimilar patient features, similar clinical features; c) similar patient features, dissimilar clinical features), or 2) not matched to any prior case (d) no exposure). A diagnosis consistent with a matched exposure case was scored correct. Cases with no prior exposure had no matched cases, hence validated the equiprobable design.ResultsDiagnosis A represented 47% of responses in condition d, but there was no influence of specific similarity of patient characteristics for Diagnosis A, F(3,712)=7.28, p=0.28 or Diagnosis B, F(3,712)=4.87, p=0.19. When re-scored based on matching both equiprobable diagnoses, accuracy was high, but favored faculty (n=40) 98%, and residents (n=39) 98% over medical students (n=32) 85%, F(2,712)=35.6, p<0.0001. Accuracy for medical students was 84, 87, 94, and 73% for conditions a–d, respectively, interaction F(2,712)=3.55, p<0.002.ConclusionsThe differential diagnosis of pre-clerkship medical students improved with prior exposure, but this was unrelated to specific case or patient features. The accuracy of medical residents and staff was not influenced by prior exposure.


2021 ◽  
pp. bmjqs-2020-011593
Author(s):  
Traber D Giardina ◽  
Saritha Korukonda ◽  
Umber Shahid ◽  
Viralkumar Vaghani ◽  
Divvy K Upadhyay ◽  
...  

BackgroundPatient complaints are associated with adverse events and malpractice claims but underused in patient safety improvement.ObjectiveTo systematically evaluate the use of patient complaint data to identify safety concerns related to diagnosis as an initial step to using this information to facilitate learning and improvement.MethodsWe reviewed patient complaints submitted to Geisinger, a large healthcare organisation in the USA, from August to December 2017 (cohort 1) and January to June 2018 (cohort 2). We selected complaints more likely to be associated with diagnostic concerns in Geisinger’s existing complaint taxonomy. Investigators reviewed all complaint summaries and identified cases as ‘concerning’ for diagnostic error using the National Academy of Medicine’s definition of diagnostic error. For all ‘concerning’ cases, a clinician-reviewer evaluated the associated investigation report and the patient’s medical record to identify any missed opportunities in making a correct or timely diagnosis. In cohort 2, we selected a 10% sample of ‘concerning’ cases to test this smaller pragmatic sample as a proof of concept for future organisational monitoring.ResultsIn cohort 1, we reviewed 1865 complaint summaries and identified 177 (9.5%) concerning reports. Review and analysis identified 39 diagnostic errors. Most were categorised as ‘Clinical Care issues’ (27, 69.2%), defined as concerns/questions related to the care that is provided by clinicians in any setting. In cohort 2, we reviewed 2423 patient complaint summaries and identified 310 (12.8%) concerning reports. The 10% sample (n=31 cases) contained five diagnostic errors. Qualitative analysis of cohort 1 cases identified concerns about return visits for persistent and/or worsening symptoms, interpersonal issues and diagnostic testing.ConclusionsAnalysis of patient complaint data and corresponding medical record review identifies patterns of failures in the diagnostic process reported by patients and families. Health systems could systematically analyse available data on patient complaints to monitor diagnostic safety concerns and identify opportunities for learning and improvement.


Diagnosis ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 169-176 ◽  
Author(s):  
Jerusalem Merkebu ◽  
Michael Battistone ◽  
Kevin McMains ◽  
Kathrine McOwen ◽  
Catherine Witkop ◽  
...  

AbstractThe diagnostic error crisis suggests a shift in how we view clinical reasoning and may be vital for transforming how we view clinical encounters. Building upon the literature, we propose clinical reasoning and error are context-specific and proceed to advance a family of theories that represent a model outlining the complex interplay of physician, patient, and environmental factors driving clinical reasoning and error. These contemporary social cognitive theories (i.e. embedded cognition, ecological psychology, situated cognition, and distributed cognition) can emphasize the dynamic interactions occurring amongst participants in particular settings. The situational determinants that contribute to diagnostic error are also explored.


2007 ◽  
Vol 36 (12) ◽  
pp. 1147-1153 ◽  
Author(s):  
Kush Singh ◽  
Clyde A. Helms ◽  
David Fiorella ◽  
Nancy A. Major

Biometrics ◽  
1999 ◽  
Vol 55 (4) ◽  
pp. 1232-1235 ◽  
Author(s):  
Joanna H. Shih ◽  
Paul S. Albert

Neurology ◽  
2008 ◽  
Vol 70 (4) ◽  
pp. e14-e15 ◽  
Author(s):  
S. Laureys ◽  
J. J. Fins
Keyword(s):  

2011 ◽  
Vol 23 (1) ◽  
pp. 78-84 ◽  
Author(s):  
Jonathan Sherbino ◽  
Kelly L. Dore ◽  
Eric Siu ◽  
Geoffrey R. Norman

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