For patients with low grade prostate cancer, there is an alternative to immediate treatment that can allow them to live out healthy lives without going through invasive procedures. The Active Surveillance program at Johns Hopkins helps patients make these difficult decisions with their doctors as they are regularly monitored. A research team interpreted decades of active surveillance data into a complex algorithm (demographic, biopsy, MRI, and lab data) that created predictions to help aide those conversations. The challenge for the Technology Innovation Center team was to figure out a way to integrate and display those predictions through clear visualizations so that patients could better understand their risks and feel more confident about their decision to remain in the Active Surveillance program.
Active Care uses the prediction model and database developed by researchers to interactively chart a patient’s past lab and MRI values and the likelihood of finding a higher grade cancer on biopsy. It also displays the likelihood of each grade of cancer as well as long-term outcomes for specific subsets of patients if the prostate is removed. Since the tool was deployed in 2016, the Active Surveillance team have regularly used it to make data-driven decisions regarding whether a patient needs to do a biopsy or seek further treatment. Previously, patients were recommended to get a biopsy annually, but with the tool most patients can wait sometimes years longer before undergoing the procedure.