Journalistic Excellence in Tech-Enabled Care for Chronic Conditions

SSM Health innovates kidney care with predictive analytics and machine learning

Mar 5, 2021   |   Healthcare IT News

The health system is, for example, reducing acute utilization and ER utilization for both chronic kidney disease and end-stage renal disease populations.

SSM Health, a nonprofit with $8 billion in revenue, provides its communities with high-quality care for vulnerable populations. One of the most vulnerable populations is made up of patients with kidney disease.

THE PROBLEM

Kidney disease is complex because 90% of people with the disease do not know they have it until they need dialysis or a transplant. There is little disease education or preventive efforts in the initial stages, making chronic kidney disease expensive to treat. Patients typically wind up receiving lower outcomes and lower quality of life than physicians would like to see.

CKD and end-stage renal disease patients manage 15-20 medications daily and have multiple comorbid conditions, complicating treatment.

“Patients with kidney disease make up under 5% of our patient population, but account for more than 20% of our total costs,” said Carter Dredge, chief transformation officer at SSM Health. “We needed the focus and expertise that our partner Strive Health delivers through predictive analytics and the care team to better support our most at-risk population.

“Across the broad primary care base, providers are seeing patients with a range of health concerns, and CKD often involves just five to 10 patients in their panel,” he continued. “During each visit, PCPs have limited time to meet these complex needs, and CKD symptoms are subtle. Often, patients were under-diagnosed for advanced CKD.”

SSM Health needed a focused solution that helped predict the best time to engage patients to optimize the patient experience, improve outcomes and lower costs.

“At SSM Health, as our core clinical teams build the main programs that encompass all our patients and interventions across multiple populations, partnering with Strive Health has delivered focused care for a particularly complex condition that connects to the larger innovation pipeline, aiding the move to more risk-based contracts by helping build the required care coordination and analytics programs for more specific patient cohorts,” Dredge said.

PROPOSAL

Analytics can offer diagnostic assistance and guide treatment decisions. Combining data from several sources, including claims, clinical data, live feeds from health exchanges, dialysis machines and demographic information for social determinants of health, algorithms can predict adverse events, including kidney failure during a given time frame or a cardiology event.

“The program we developed with Strive Health delivers comprehensive clinical services for CKD and ESRD patients that significantly improve quality of care and outcomes while lowering the total cost of care for patients,” Dredge said. “Thirty-three algorithms assist with treating CKD, including one that can predict CKD progression to ESRD with 95% accuracy.” Read More

Authors

Bill Siwicki

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