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Abstract
Background Diagnostic 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.
Objective We 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.
Methods Cross-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.
Results Annual 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%.
Conclusion An 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.
- diagnostic errors
- medical error, measurement/epidemiology
- adverse events, epidemiology and detection
Data availability statement
Data are available in a public, open access repository. Data on disease incidence used for the study are all publicly available; these public-use datasets and accompanying standard data dictionaries may be found at the URL locations cited in the references list. Additional details regarding sources and methods for diagnostic error and harm rate calculations may be found in three prior publications (PMID: 31535832, 32412440, 36574484), including their associated appendices and online supplemental materials.
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Data availability statement
Data are available in a public, open access repository. Data on disease incidence used for the study are all publicly available; these public-use datasets and accompanying standard data dictionaries may be found at the URL locations cited in the references list. Additional details regarding sources and methods for diagnostic error and harm rate calculations may be found in three prior publications (PMID: 31535832, 32412440, 36574484), including their associated appendices and online supplemental materials.
Footnotes
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Contributors DEN-T (guarantor): I accept full responsibility for the finished work and the conduct of the study, had access to the data, and controlled the decision to publish. I declare that I designed the study; had primary oversight over the data analysis; designed the figures; authored the primary manuscript draft and all major revisions and that I have seen and approved the final version. I served as an unpaid member of the Board of Directors of the Society to Improve Diagnosis in Medicine, and as its President (2018–2020). I serve as a medico-legal consultant for both plaintiff and defence in cases related to diagnostic error. I have no other relevant conflicts of interest. NN: I declare that I assisted in study design and conduct; edited the manuscript for scientific content and that I have seen and approved the final version. I have no conflicts of interest. ACS: I declare that I assisted in study design and conduct; edited the manuscript for scientific content and that I have seen and approved the final version. I have no conflicts of interest. CWY-M: I declare that I assisted in study conduct; edited the manuscript for scientific content and that I have seen and approved the final version. I have no conflicts of interest. ASST: I declare that I assisted in study conduct; edited the manuscript for scientific content and that I have seen and approved the final version. I have no conflicts of interest. GDC: I declare that I assisted in study conduct; edited the manuscript for scientific content and that I have seen and approved the final version. I have no conflicts of interest. ZW: I declare that I designed the statistical analysis, including Monte Carlo simulations to create probabilistic plausible range estimates; edited the manuscript for scientific content and that I have seen and approved the final version. I have no conflicts of interest. YZ: I declare that I assisted in the design and conduct of the statistical analysis, including Monte Carlo simulations to create probabilistic plausible range estimates; edited the manuscript for scientific content and that I have seen and approved the final version. I have no conflicts of interest. MF: I declare that I assisted in study conduct; edited the manuscript for scientific content and that I have seen and approved the final version. I have no conflicts of interest. AH: I declare that I assisted in study conduct; edited the manuscript for scientific content and that I have seen and approved the final version. I have no conflicts of interest. DS: I declare that I assisted in study design and conduct; edited the manuscript for scientific content and that I have seen and approved the final version. I previously served as an unpaid member of the Board of Directors of the Society to Improve Diagnosis in Medicine.
Funding This study was funded by Society to Improve Diagnosis in Medicine, Agency for Healthcare Research and Quality (EPC VI (TOPIC ID 503-4262), R01 HS 27614, R18 HS 029350) and Armstrong Institute Center for Diagnostic Excellence at the Johns Hopkins University School of Medicine.
Competing interests DEN-T has a career focus and conducts research related to diagnostic errors, including in patients with dizziness and stroke. He serves as the principal investigator for multiple grants and contracts on these topics. DEN-T is a former volunteer President and member of the Board of Directors of the Society to Improve Diagnosis in Medicine. Johns Hopkins has been loaned research equipment (video-oculography (VOG) systems) by two companies for use in DEN-T’s research; one of these companies has also provided funding for DEN-T’s research on diagnostic algorithm development related to dizziness, inner ear diseases and stroke. DEN-T has no other financial interest in these or any other companies. DEN-T is an inventor on a provisional patent (US PCT/US2020/070304) for smartphone-based stroke diagnosis in patients with dizziness. He gives frequent academic lectures on these topics and occasionally serves as a medico-legal consultant for both plaintiff and defence in cases related to dizziness, stroke and diagnostic error. DS is also a former volunteer member of the Board of Directors of the Society to Improve Diagnosis in Medicine. There are no other conflicts of interest. None of the authors have any financial or personal relationships with other people or organisations that could inappropriately influence (bias) their work.
Provenance and peer review Not commissioned; externally peer reviewed.
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