A new U.S. federal government study made emergency department diagnostic accuracy a mainstream news story, showing that although ED diagnostic errors are somewhat rare, they occur in high volumes and can carry serious consequences.
The U.S. Agency for Healthcare Research and Quality and Johns Hopkins University teamed up to analyzed 279 international studies published between 2001 and 2021, finding that:
- Diagnostic errors occur in an estimated 5.7% of ED visits
- Generalized to the U.S., ED diagnostic errors impact 7.4M patients annually
- Those diagnostic errors lead to “preventable harms” in roughly 2.6M patients, and “serious harms” in 371k patients, including 250k deaths
- The top 5 and 15 diseases account for 39% and 68% of “serious misdiagnosis-related harms”
Although “not all diagnostic errors are preventable,” error rate variations revealed key areas for improvement:
- Women and people of color were 20% to 30% more likely to be misdiagnosed
- Misdiagnosis is far more common among patients with “atypical” and “subtle” disease presentation
- Hospital and disease-specific error rates varied widely
Imaging played a major role in the study, as most of the top-15 diseases associated with “serious misdiagnosis-related harms” are typically diagnosed with imaging exams (including all of the top-5), and the report mentioned “radiology,” “imaging,” “image,” “scan,” or “ultrasound” a whopping 419 times.
Emergency medicine societies objected to these results, but the consensus among study authors and most observers was that more efforts are needed to understand and address ED diagnostic errors, with a specific focus on the diseases associated with serious misdiagnosis harms.
Most efforts to improve ED safety over the last 20 years have targeted glaring mistakes (e.g. wrong medications, ED-acquired infections), but this report clearly calls for increased focus on improving EDs’ diagnostic accuracy.
Those efforts would start at the bedside, but they would definitely involve medical imaging (and potentially error-catching AI tools), especially considering that most of the diseases associated with “serious misdiagnosis-related harms” are diagnosed via imaging.