Evidence map›Paper›PMID 37460118›Full record

ArticleBMJ quality & safety2024

Burden of serious harms from diagnostic error in the USA.

David E Newman-Toker, Najlla Nassery, Adam C Schaffer, Chihwen Winnie Yu-Moe, Gwendolyn D Clemens, Zheyu Wang, Yuxin Zhu, Ali S Saber Tehrani, Mehdi Fanai, Ahmed Hassoon and 1 more

Abstract read
In one paragraph

Article in BMJ quality & safety, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

86 citing papers in PubMed.

  1. Trial
  2. Effects of Prior Diagnosis on Second Opinions and Pathologist Viewing Behaviors: Results from a Randomized Trial in Breast Pathology.Medical decision making : an international journal of the Society for Medical Decision Making · 2026
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26 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

David E Newman-TokerDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA toker@jhu.edu.ORCID 0000-0003-2789-4115
Najlla NasseryDepartment of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Adam C SchafferDepartment of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Chihwen Winnie Yu-MoeDepartment of Patient Safety, The Risk Management Foundation of the Harvard Medical Institutions Inc, Boston, Massachusetts, USA.
Gwendolyn D ClemensDepartment of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
Zheyu WangDepartment of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
Yuxin ZhuDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Ali S Saber TehraniDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Mehdi FanaiDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Ahmed HassoonDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Dana SiegalCandello, The Risk Management Foundation of the Harvard Medical Institutions Inc, Boston, Massachusetts, USA.

Funding

Towards a National Diagnostic Excellence Dashboard - Partnering with Stakeholders to Construct Evidence-Based Operational Measures of Misdiagnosis-Related HarmsR01HS027614 · AHRQ · JOHNS HOPKINS UNIVERSITY · PI NEWMAN-TOKER, DAVID · 2020 to 2023
$1.5M
AHRQ HHS R01 HS027614
6 · The paper itself

Abstract

backgroundDiagnostic errors cause substantial preventable harms worldwide, but rigorous estimates for total burden are lacking. We previously estimated diagnostic error and serious harm rates for key dangerous diseases in major disease categories and validated plausible ranges using clinical experts.

objectiveWe sought to estimate the annual US burden of serious misdiagnosis-related harms (permanent morbidity, mortality) by combining prior results with rigorous estimates of disease incidence.

methodsCross-sectional analysis of US-based nationally representative observational data. We estimated annual incident vascular events and infections from 21.5 million (M) sampled US hospital discharges (2012-2014). Annual new cancers were taken from US-based registries (2014). Years were selected for coding consistency with prior literature. Disease-specific incidences for 15 major vascular events, infections and cancers ('Big Three' categories) were multiplied by literature-based rates to derive diagnostic errors and serious harms. We calculated uncertainty estimates using Monte Carlo simulations. Validity checks included sensitivity analyses and comparison with prior published estimates.

resultsAnnual US incidence was 6.0 M vascular events, 6.2 M infections and 1.5 M cancers. Per 'Big Three' dangerous disease case, weighted mean error and serious harm rates were 11.1% and 4.4%, respectively. Extrapolating to all diseases (including non-'Big Three' dangerous disease categories), we estimated total serious harms annually in the USA to be 795 000 (plausible range 598 000-1 023 000). Sensitivity analyses using more conservative assumptions estimated 549 000 serious harms. Results were compatible with setting-specific serious harm estimates from inpatient, emergency department and ambulatory care. The 15 dangerous diseases accounted for 50.7% of total serious harms and the top 5 (stroke, sepsis, pneumonia, venous thromboembolism and lung cancer) accounted for 38.7%.

conclusionAn estimated 795 000 Americans become permanently disabled or die annually across care settings because dangerous diseases are misdiagnosed. Just 15 diseases account for about half of all serious harms, so the problem may be more tractable than previously imagined.

Indexed as

Lung NeoplasmsStrokeCross-Sectional StudiesDiagnostic ErrorsHumansMorbidityUnited Statesadverse events, epidemiology and detectiondiagnostic errorsmedical error, measurement/epidemiology

Identifiers

PMID37460118
PMCPMC10792094

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.