Literature DB >> 31535832

Serious misdiagnosis-related harms in malpractice claims: The "Big Three" - vascular events, infections, and cancers.

David E Newman-Toker1,2,3, Adam C Schaffer4,5, C Winnie Yu-Moe6, Najlla Nassery7, Ali S Saber Tehrani1, Gwendolyn D Clemens8, Zheyu Wang8,9, Yuxin Zhu8,9, Mehdi Fanai1, Dana Siegal10.   

Abstract

Background Diagnostic errors cause substantial preventable harm, but national estimates vary widely from 40,000 to 4 million annually. This cross-sectional analysis of a large medical malpractice claims database was the first phase of a three-phase project to estimate the US burden of serious misdiagnosis-related harms. Methods We sought to identify diseases accounting for the majority of serious misdiagnosis-related harms (morbidity/mortality). Diagnostic error cases were identified from Controlled Risk Insurance Company (CRICO)'s Comparative Benchmarking System (CBS) database (2006-2015), representing 28.7% of all US malpractice claims. Diseases were grouped according to the Agency for Healthcare Research and Quality (AHRQ) Clinical Classifications Software (CCS) that aggregates the International Classification of Diseases diagnostic codes into clinically sensible groupings. We analyzed vascular events, infections, and cancers (the "Big Three"), including frequency, severity, and settings. High-severity (serious) harms were defined by scores of 6-9 (serious, permanent disability, or death) on the National Association of Insurance Commissioners (NAIC) Severity of Injury Scale. Results From 55,377 closed claims, we analyzed 11,592 diagnostic error cases [median age 49, interquartile range (IQR) 36-60; 51.7% female]. These included 7379 with high-severity harms (53.0% death). The Big Three diseases accounted for 74.1% of high-severity cases (vascular events 22.8%, infections 13.5%, and cancers 37.8%). In aggregate, the top five from each category (n = 15 diseases) accounted for 47.1% of high-severity cases. The most frequent disease in each category, respectively, was stroke, sepsis, and lung cancer. Causes were disproportionately clinical judgment factors (85.7%) across categories (range 82.0-88.8%). Conclusions The Big Three diseases account for about three-fourths of serious misdiagnosis-related harms. Initial efforts to improve diagnosis should focus on vascular events, infections, and cancers.

Entities:  

Keywords:  diagnosis; diagnostic errors; health services research; malpractice; medical errors

Mesh:

Year:  2019        PMID: 31535832     DOI: 10.1515/dx-2019-0019

Source DB:  PubMed          Journal:  Diagnosis (Berl)        ISSN: 2194-802X


  12 in total

1.  Communication of Diagnostic Uncertainty in Primary Care and Its Impact on Patient Experience: an Integrative Systematic Review.

Authors:  Maria R Dahm; William Cattanach; Maureen Williams; Jocelyne M Basseal; Kelly Gleason; Carmel Crock
Journal:  J Gen Intern Med       Date:  2022-09-20       Impact factor: 6.473

2.  Analysis of Variation Between Diagnosis at Admission vs Discharge and Clinical Outcomes Among Adults With Possible Bacteremia.

Authors:  Emma Dregmans; Anna G Kaal; Soufian Meziyerh; Nikki E Kolfschoten; Maarten O van Aken; Emile F Schippers; Ewout W Steyerberg; Cees van Nieuwkoop
Journal:  JAMA Netw Open       Date:  2022-06-01

3.  Diagnostic delays in infectious diseases.

Authors:  Manish Suneja; Susan E Beekmann; Gurpreet Dhaliwal; Aaron C Miller; Philip M Polgreen
Journal:  Diagnosis (Berl)       Date:  2022-01-20

4.  Preventing Diagnostic Errors in Ambulatory Care: An Electronic Notification Tool for Incomplete Radiology Tests.

Authors:  Saul N Weingart; Omar Yaghi; Liz Barnhart; Sucharita Kher; John Mazzullo; Kari Roberts; Eric Lominac; Nancy Gittelson; Philip Argyris; William Harvey
Journal:  Appl Clin Inform       Date:  2020-04-15       Impact factor: 2.342

5.  Factors associated with potentially missed acute deterioration in primary care: cohort study of UK general practices.

Authors:  Elizabeth Cecil; Alex Bottle; Azeem Majeed; Paul Aylin
Journal:  Br J Gen Pract       Date:  2021-06-24       Impact factor: 6.302

Review 6.  Bringing the clinical laboratory into the strategy to advance diagnostic excellence.

Authors:  Ira M Lubin; J Rex Astles; Shahram Shahangian; Bereneice Madison; Ritchard Parry; Robert L Schmidt; Matthew L Rubinstein
Journal:  Diagnosis (Berl)       Date:  2021-01-06

7.  Extracting COVID-19 diagnoses and symptoms from clinical text: A new annotated corpus and neural event extraction framework.

Authors:  Kevin Lybarger; Mari Ostendorf; Matthew Thompson; Meliha Yetisgen
Journal:  J Biomed Inform       Date:  2021-03-26       Impact factor: 8.000

8.  Proof of Concept for an "eyePhone" App to Measure Video Head Impulses.

Authors:  T Maxwell Parker; Nathan Farrell; Jorge Otero-Millan; Amir Kheradmand; Ayodele McClenney; David E Newman-Toker
Journal:  Digit Biomark       Date:  2020-12-30

9.  Real-world virtual patient simulation to improve diagnostic performance through deliberate practice: a prospective quasi-experimental study.

Authors:  Susrutha Kotwal; Mehdi Fanai; Wei Fu; Zheyu Wang; Anand K Bery; Rodney Omron; Nana Tevzadze; Daniel Gold; Brian T Garibaldi; Scott M Wright; David E Newman-Toker
Journal:  Diagnosis (Berl)       Date:  2021-03-08

10.  Evidence That Nurses Need to Participate in Diagnosis: Lessons From Malpractice Claims.

Authors:  Kelly Therese Gleason; Rebecca Jones; Christopher Rhodes; Penny Greenberg; Gene Harkless; Chris Goeschel; Maureen Cahill; Mark Graber
Journal:  J Patient Saf       Date:  2021-12-01       Impact factor: 2.844

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