Simple physician checklists, diagnostic decision-support systems, or second looks at medical imaging exams could help to reduce the estimated 40,000 to 80,000 hospital deaths in the U.S. from diagnostic errors.
Simple physician checklists, diagnostic decision-support systems, or second looks at medical imaging exams could help to reduce the estimated 40,000 to 80,000 hospital deaths in the U.S. from diagnostic errors.
Writing for the March 11 Journal of the American Medical Association, Johns Hopkins University School of Medicine physicians Dr. David Newman-Toker and Dr. Peter Pronovost stressed that diagnostic errors deserve the same attention as drug-prescribing errors, wrong-site surgeries, and hospital-acquired infections.
Diagnostic misadventures represent a potentially much larger source of preventable health problems and deaths than many of the more popular targets of safety reform, they said. Tort claims for diagnostic errors -- defined as diagnoses that are missed, wrong, or delayed -- are nearly twice as common as claims for medication errors.
Blaming physicians for a lack of training or necessary skill to avoid errors has not helped to reduce misdiagnosis rates, said Newman-Toker, an assistant professor of neurology with credentials in otolaryngology, informatics, epidemiology, and health policy. He supports moving away from a model that chastises individuals to one that focuses on improving the medical system as a whole. The change could result in big payoffs for improved diagnostic accuracy and cost-effectiveness.
"There is often a mismatch between who gets advanced diagnostic testing and who needs it, leading to worse outcomes and higher costs. Realigning resources with needs could improve outcomes at lower cost," he said.
For an example, Newman-Toker points to problems with emergency triage protocols that categorize patients with typically benign symptoms, such as isolated headache, as being at low risk, though such symptoms sometimes indicate dangerous conditions, such as hemorrhaging brain aneurysm.
A systematic fix that could decrease diagnostic errors might be a change in overall rules for the triage protocol to consider specific symptom details that distinguish between low-risk and high-risk types of headache, he said.
Newman-Toker and Pronovost, a professor of anesthesiology, critical care, and surgery, suggest that diagnostic errors may be reduced with checklists that help physicians remember critical diagnoses or diagnostic decision-support software that assists them in calculating the level of risk for individual patients. Health systems could further decrease diagnostic errors with time-tested low-tech tools such as independent second looks at x-rays and CT scans or rapid steering of patients with unusual symptoms to diagnostic experts.
"The first step in addressing diagnostic error problems is to shine a light on them so they are clearly visible," Pronovost said. "Then with wise investments, clinicians, researchers, and patients can discover how to prevent them."
For more information from the Diagnostic Imaging and SearchMedica archives:
Study faults regulators for relying on ‘reference man' radiation dose standardFirst-year residents not ready for call, simulation findsMissed lung cancers carry medical, legal implications
AI Algorithm Comparable to Radiologists in Differentiating Small Renal Masses on CT
May 14th 2024An emerging deep learning algorithm had a lower AUC and sensitivity than urological radiologists for differentiating between small renal masses on computed tomography (CT) scans but had a 21 percent higher sensitivity rate than non-urological radiologists, according to new research.
The Reading Room: Racial and Ethnic Minorities, Cancer Screenings, and COVID-19
November 3rd 2020In this podcast episode, Dr. Shalom Kalnicki, from Montefiore and Albert Einstein College of Medicine, discusses the disparities minority patients face with cancer screenings and what can be done to increase access during the pandemic.
FDA Clears AI-Powered Qualitative Perfusion Mapping for Cone-Beam CT
May 6th 2024Reportedly validated in more than 10 clinical trials, the AngioFlow perfusion imaging software enables timely identification of brain regions with cerebral blood flow reduction and those with significant hypoperfusion.
Can a CT-Based Radiomics Model Bolster Detection of Malignant Thyroid Nodules?
May 3rd 2024A computed tomography (CT)-based radiomics model that includes 28 radiomic features showed significantly higher accuracy, sensitivity, and specificity than conventional CT in differentiating benign and malignant thyroid nodules, according to newly published research.