Burden of serious harms from diagnostic error in the USA.

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.

Cerebrovascular disease hospitalizations following emergency department headache visits: A nested case-control study.

BACKGROUND: Delayed diagnosis of cerebrovascular disease (CVD) among patients can result in substantial harm. If diagnostic process failures can be identified at emergency department (ED) visits that precede CVD hospitalization, interventions to improve diagnostic accuracy can be developed. METHODS: We conducted a nested case-control study using a cohort of adult ED patients discharged from a single medical center with a benign headache diagnosis from October 1, 2015 to March 31, 2018. Hospitalizations for CVD within 1 year of index ED visit were identified using a regional health information exchange. Patients with subsequent CVD hospitalization (cases) were individually matched to patients without subsequent hospitalization (controls) using patient age and visit date. Demographic, clinical, and ED process characteristics were assessed via detailed chart review. McNemar's test for categorical and paired t-test for continuous variables were used with statistical significance set at ≤0.05. RESULTS: Of the 9157 patients with ED headache visits, 57 (0.6%, 95% confidence interval [CI] = 0.5-0.8) had a subsequent CVD hospitalization. Median time from ED visit to hospitalization was 107 days. In 25 patients (43.9%, 25/57) the CVD hospitalization and the index ED visit were at different hospitals. Fifty-three cases and 53 matched controls were included in the final study analysis. Cases and controls had similar baseline demographic and headache characteristics. Cases more often had a history of stroke (32.1% vs. 13.2%, p = 0.02) and neurosurgery (13.2% vs. 1.9%, p = 0.03) prior to the index ED visit. Cases more often had less than two components of the neurologic examination documented (30.2% vs. 11.3%, p = 0.03). CONCLUSION: We found that 0.6% of patients with an ED headache visit had subsequent CVD hospitalization, often at another medical center. ED visits for headache complaints among patients with prior stroke or neurosurgical procedures may be important opportunities for CVD prevention. Documented neurologic examinations were poorer among cases, which may represent an opportunity for ED process improvement.

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

OBJECTIVES: Diagnostic errors are pervasive in medicine and most often caused by clinical reasoning failures. Clinical presentations characterized by nonspecific symptoms with broad differential diagnoses (e.g., dizziness) are especially prone to such errors. METHODS: We hypothesized that novice clinicians could achieve proficiency diagnosing dizziness by training with virtual patients (VPs). This was a prospective, quasi-experimental, pretest-posttest study (2019) at a single academic medical center. Internal medicine interns (intervention group) were compared to second/third year residents (control group). A case library of VPs with dizziness was developed from a clinical trial (AVERT-NCT02483429). The approach (VIPER - Virtual Interactive Practice to build Expertise using Real cases) consisted of brief lectures combined with 9 h of supervised deliberate practice. Residents were provided dizziness-related reading and teaching modules. Both groups completed pretests and posttests. RESULTS: For interns (n=22) vs. residents (n=18), pretest median diagnostic accuracy did not differ (33% [IQR 18-46] vs. 31% [IQR 13-50], p=0.61) between groups, while posttest accuracy did (50% [IQR 42-67] vs. 20% [IQR 17-33], p=0.001). Pretest median appropriate imaging did not differ (33% [IQR 17-38] vs. 31% [IQR 13-38], p=0.89) between groups, while posttest appropriateness did (65% [IQR 52-74] vs. 25% [IQR 17-36], p<0.001). CONCLUSIONS: Just 9 h of deliberate practice increased diagnostic skills (both accuracy and testing appropriateness) of medicine interns evaluating real-world dizziness 'in silico' more than ∼1.7 years of residency training. Applying condensed educational experiences such as VIPER across a broad range of common presentations could significantly enhance diagnostic education and translate to improved patient care.

Rate of diagnostic errors and serious misdiagnosis-related harms for major vascular events, infections, and cancers: toward a national incidence estimate using the "Big Three".

BACKGROUND: Missed vascular events, infections, and cancers account for ~75% of serious harms from diagnostic errors. Just 15 diseases from these "Big Three" categories account for nearly half of all serious misdiagnosis-related harms in malpractice claims. As part of a larger project estimating total US burden of serious misdiagnosis-related harms, we performed a focused literature review to measure diagnostic error and harm rates for these 15 conditions. METHODS: We searched PubMed, Google, and cited references. For errors, we selected high-quality, modern, US-based studies, if available, and best available evidence otherwise. For harms, we used literature-based estimates of the generic (disease-agnostic) rate of serious harms (morbidity/mortality) per diagnostic error and applied claims-based severity weights to construct disease-specific rates. Results were validated via expert review and comparison to prior literature that used different methods. We used Monte Carlo analysis to construct probabilistic plausible ranges (PPRs) around estimates. RESULTS: Rates for the 15 diseases were drawn from 28 published studies representing 91,755 patients. Diagnostic error (false negative) rates ranged from 2.2% (myocardial infarction) to 62.1% (spinal abscess), with a median of 13.6% [interquartile range (IQR) 9.2-24.7] and an aggregate mean of 9.7% (PPR 8.2-12.3). Serious misdiagnosis-related harm rates per incident disease case ranged from 1.2% (myocardial infarction) to 35.6% (spinal abscess), with a median of 5.5% (IQR 4.6-13.6) and an aggregate mean of 5.2% (PPR 4.5-6.7). Rates were considered face valid by domain experts and consistent with prior literature reports. CONCLUSIONS: Diagnostic improvement initiatives should focus on dangerous conditions with higher diagnostic error and misdiagnosis-related harm rates.

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

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.