A new study published in BMJ Quality & Safety reported that researchers helped to lead the way in providing hospitals a new approach to quantify and monitor diagnostic errors in their quality improvement efforts to reduce patient misdiagnoses and associated poor patient outcomes from lack of prompt treatment. The approach, called Symptom-Disease Pair Analysis of Diagnostic Error, or SPADE, is featured.
The method could be used broadly across a range of conditions to operationally measure diagnostic errors and associated bad outcomes so that we can track our performance and see whether our interventions are making a difference. Many current methods of measuring diagnostic errors rely on labor-intensive medical record reviews by hospital staff members.
The SPADE method 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. Using SPADE, we can 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. And being able to do that using big data is an important innovation for diagnostic quality and safety. SPADE, in turn, will lead to improved patient outcomes.
Many quality measures focus on hospital processes, rather than patient outcomes. But it is not about treating the charts, it is about treating the patients. The researchers focus on tracking serious adverse outcomes, such as stroke or heart attack. These measures will matter to patients. SPADE will work best with acute and subacute diseases for which a misdiagnosis that leads to hospitalization, disability or death is likely to occur within six months to a year.
Further research is needed to validate SPADE across a wider range of symptoms and diseases. The method may not ultimately be applicable to all diseases, especially chronic conditions, but the team expects it will work for what they calls "The Big Three" causes of disability and death from diagnostic error: vascular events, infections and cancers.