Research shows that harmful diagnostic errors can occur in 1 in 14 general medical hospital patients

Harmful diagnostic errors may occur in as many as 1 in 14 (7%) hospital patients – at least among those receiving general medical care – suggest the findings of a single-center study in the US, published online in the journal BMJ quality and safety.

Most (85%) of these errors are likely preventable and underscore the need for new approaches to improve supervision to prevent these errors from happening in the first place, the researchers say.

Previously published reports suggest that current trigger tools for spotting medical errors are not good enough to detect harmful diagnostic errors, including errors with less serious consequences, the researchers suggest.

Therefore, they developed and validated a structured case review process to enable physicians to interrogate the electronic health record (EHR) to evaluate the diagnostic process for hospitalized patients, assess the likelihood of diagnostic error, and characterize the impact and severity of harm.

They used the process to retrospectively estimate the prevalence of harmful diagnostic errors in a randomly selected sample of 675 hospital patients out of a total of 9,147 who received general medical care between July 2019 and September 2021, excluding the height of the COVID-19 pandemic. (April-December 2020).

Cases considered at high risk for diagnostic error were categorized as: transfer to intensive care 24 or more hours after admission (130; 100%); death within 90 days of hospital admission or discharge (141; 38.5%); complex clinical problems, but no transfer to intensive care or death within 90 days of admission (298; 7%).

Complex clinical problems include clinical deterioration; treatment by different medical teams; unexpected events, such as canceled operations; unclear or conflicting diagnostic information recorded in the medical notes.

Cases considered low risk were those that did not meet any of the high-risk criteria (106; 2.5%).

Each case was reviewed by two raters trained to assess the likelihood of diagnostic errors and identify associated process errors using the Diagnostic Error Evaluation and Research Taxonomy, adapted for acute care.

The damage was classified as mild, moderate, severe and fatal, and it was also assessed whether the diagnostic error contributed to the damage and whether it was preventable.

Cases with discrepancies or uncertainty about the diagnostic error or its impact were further reviewed by a panel of experts.

Of all cases reviewed, diagnostic errors were found in 160 cases (154 patients). These include: intensive care transfer (54); death within 90 days (34); complex clinical problems (52); low-risk patients (20).

Adverse diagnostic errors were found to have occurred in 84 cases (82 patients), 37 (28.5%) of which occurred during intensive care unit transfers; 18 (13%) among those who died within 90 days; 23 (8%) among those with complex clinical problems; and six (6%) in low-risk cases.

The severity of damage was characterized as minor in five (6%), moderate in 36 (43%), major in 25 (30%) and fatal in 18 (21.5%).

Overall, an estimated 85% of harmful diagnostic errors were preventable, with older, white, non-Hispanic, non-privately insured, and high-risk patients at greatest risk.

Weighted to account for population, the researchers estimated the proportion of harmful, preventable, and seriously harmful diagnostic errors in general medical hospital patients at just over 7%, 6%, and 1%, respectively.

Process errors were significantly associated with diagnostic errors, specifically uncertainty in initial assessments and complex diagnostic tests and interpretations (four times the risk), suboptimal subspecialty consultation (three times the risk), patient-reported concerns (three times the risk), and anamnesis. (2.5 times the risk).

Forty (48%) diagnostic errors were related to the primary diagnosis at admission or discharge and 44 (52.5%) to a secondary diagnosis; 52 (62%) were characterized as delays. Errors associated with major or fatal damage were common in the high-risk group (55%, 43/78) and rare in the low-risk group (0/6).

The most common diagnoses associated with diagnostic errors included heart failure, acute renal failure, sepsis, pneumonia, respiratory failure, altered mental status, abdominal pain, and hypoxemia (low blood oxygen).

Careful analysis of the errors and integrating AI tools into the workflow should help minimize their prevalence, by improving monitoring and triggering timely interventions, the researchers suggest.

This is an observational study, based on estimates drawn from data on patients receiving general medical care at a single center, and should be interpreted in that context, the researchers caution.

They also acknowledge that the sample was limited to patients with hospital stays of less than 21 days, and that the study was based on information recorded in the electronic health record, which is prone to inaccurate recording of deaths within 90 days.

Nevertheless, they conclude: ‘We estimate that this is harmful [diagnostic error] occurred in one in 14 patients admitted to hospital with general medicine, the majority of which were preventable. Our findings underscore the need for new approaches to adverse outcomes [diagnostic error] supervision.”