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Improving radiology through feedback and metrics

By Dr. William Moore
From the August 2017 issue of DOTmed HealthCare Business News magazine

Health care informatics has many facets and is ripe with opportunities for improvement in patient care.

I recall during residency always begging for feedback on our reads. In fact, I remember one attending who would specifically add "feedback would be appreciated" to the end of many of his reports. As you could imagine, he got little or no response to these requests. For years, many of us would carry around pieces of paper, notebooks or some other manual process to follow up on interesting cases. This required us to be fastidious with our notes, but was biased toward “interesting case.”

As the PACS system became more ubiquitous, we demanded the ability to save cases. This was a revolutionary step forward, allowing saving and retrieval of cases with previously unthinkable ease. However, this practice was also flawed. The primary issue is that these systems relied on a human intervention in order to record and follow up on each case. Further, the case selection was biased toward cases the radiologist or the resident determined were interesting enough to warrant the effort to follow up. As the volume of imaging studies increases and reimbursement drops, productivity is critical and one’s ability to spend a significant amount of time on educational, quality assurance and or quality improvement processes is limited.

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In order to make systems that solve a problem, we must have an understanding of what the issues are and what a success would look like. Lack of feedback on radiology reads is a classic problem that is perfect for an informatics solution. In fact, in the book “Black Box Thinking” by Matthew Syed, mammography is used as an example of why people don’t learn from their mistakes. Currently, most health care facilities have an electronic medical record. These EMRs are packed with data organized in a variety of ways, but typically not organized in a manner designed around a radiologist workflow. Hunting though an EMR for correlative results such as pathology can be a laborious task taking several minutes in the best scenario.

We decided to take this on as a project. With all projects we go through a process of understanding the issue, planning the solution(s), determining what success would look like and determining metrics. The problem we are looking to solve is lack of feedback on the cases read by a radiologist. The importance is related to maintaining quality at the individual and group level, potentially improving quality and uncovering potential systematic bias in reporting/interpretation.
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