Imosphere partners with US technology company to enable US-based medical college to predict renal failure

Background

Headquartered in Nashville, Tennessee, one of the nation’s oldest and largest historically Black American academic health science centers dedicated to educating physicians, dentists, researchers, and health policy experts, sought better rates of health equity by exploring renal failure in underserved populations.

Black Americans face a propensity for renal failure at 5.5x that of the standard population. But there was a huge challenge in identifying 14% of the population representing 87% of all renal failures. The college also needed to identify 50% of the subgroup which could only be done with only two tests.

Objectives

The college had two principal areas of focus. Firstly, they sought to explore their medical data to build a better understanding of the disparities surrounding Black Americans being more at risk for renal failure. Second, they wanted to develop new testing and mitigation efforts to expand resources applied to the selected population.

The process

Imosphere’s long-term strategic partnership with technology company Clearsense supported the college team’s rapid analysis of datasets with a powerful cohort discovery tool, enabling them to develop a full plan to meet their objectives.

Leveraging unique cohort discovery features, key drivers were recognized, and the college was able to build various models based on defined objectives—including coverage and precision. Further identifying drivers and unique subgroups, the datasets were elevated with auto-segmentation allowing certain behaviors to come to the forefront—better telling a story of risk and need.

The results

Providing insights in real-time to clinicians on the likelihood and reasons for renal failure, Imosphere’s partnership with Clearsense not only revealed the data to identify populations most at risk, but also helped develop key indicators to look for in datasets to enable intervention. Most importantly, the team was able to identify the best lab test for chronic kidney disease prediction without misclassification.