Breakdowns in the diagnostic process can result in missed or delayed diagnoses and subsequent patient harm. Researchers from the Johns Hopkins Armstrong Institute for Patient Safety and Quality are taking a look at how better measurement of diagnostic errors could help physicians track performance, gauge the effectiveness of interventions, reduce errors and improve patient outcomes.
As described here in Science Daily, the method being examined by these researchers “mines large, readily available databases with hundreds of thousands of patient visits, using specific algorithms to look for common symptoms prompting a doctor visit and then pairing them with one or more diseases that could be misdiagnosed in those clinical contexts. The method uses statistical analyses to identify critical patterns that measure the rate of diagnostic error and could be incorporated into diagnostic performance dashboards.”
What would that look like in practice? David Newman-Toker, director of the Armstrong Institute Center for Diagnostic Excellence, says providers would be able to “measure how often a patient comes to the hospital with dizziness, is mistakenly told it’s a benign ear condition, is sent home, and comes back with a big stroke. We can also measure how often a patient comes to a clinic with a fever, is told it’s a viral infection, but is later admitted to the hospital with bacterial sepsis. Being able to do that using big data is an important innovation for diagnostic quality and safety.”
MLMIC supports a proactive approach to improving diagnostic accuracy and preventing errors. Through MLMIC Analytics, we offer insured facilities and large group practices a personalized analysis of their claims and suits which includes identifying cases that involve diagnostic error. By utilizing data and analytics, providers can put in place procedures and protocols that help them manage risk and improve patient care.
Additionally, MLMIC offers Continuing Medical Education programs which address diagnostic error, including:
- High-Exposure Liability: Delay in Diagnosis of Breast Cancer – Part 1
- High-Exposure Liability: Delay in Diagnosis of Breast Cancer – Part 2
- High-Exposure Liability: A Case Study Analysis – Part I
- High-Exposure Liability: A Case Study Analysis – Part II
MLMIC policyholders can register for, begin or continue CME programs online here.