SSM Health innovates kidney care with predictive analytics and machine learning


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.

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.


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.”



Strive Health’s technology and full clinical model bring a focused approach to care, he added.

“We are intervening with the right patients at the right time,” he explained. “Our care team can see when a patient is progressing more rapidly toward kidney failure and can take the time to fully educate and coach the patient through making the best renal replacement therapy option for them, whether this is home dialysis, in-center dialysis, preemptive transplant or conservative care.”


There are various vendors of predictive analytics technology on the market today. Some of these vendors include Alteryx, Anodot, Domo, Gainsight, IBM, Infer, Microsoft, Qrvey, RapidMiner, SAP, SAS Institute, Sisense and Strive Health.


“Strive Health’s CareMultiplier platform, powered by proprietary machine learning algorithms, makes sense of massive amounts of data, cuts through the noise and allows our clinicians to focus on doing what only they can do, deliver high-touch patient care,” Dredge explained.

“Our clinical teams use predictive analytics in their day-to-day care,” he continued. “Each patient receives an overall risk score that serves as a starting point for treatment and flows through our clinical care systems. As we engage our members, our team then uses focused initiatives developed through the analytics to be more proactive in their care.”

As an example, SSM Health has a patient cohort called Planned Starts. Strive’s technology has identified them as progressing toward dialysis in the next six to 12 months. These analytics allow clinicians to deploy focused interventions and care plans to help prevent these patients from “crashing” into dialysis.


“Strive Health brings economies of scale, regionalization and nationalization to a fragmented kidney care process,” Dredge reported. “The program was launched in June 2020, during the COVID-19 pandemic. While the pandemic impacted most in the country, the first four months of data are promising, showing a more than 20% reduction in acute utilization for both CKD and ESRD populations and a more than 25% reduction in emergency department utilization for both CKD and ESRD populations.”

Several patients have benefited from this approach, including one female patient who was predicted to have a 57% chance of kidney failure within two years. After more than a year of “watch and wait,” the patient avoided a crash into dialysis through a high-touch care team coordinating between her nephrologist and primary care physician. They addressed her concerns and engaged her in appropriate treatment.

“Separately, a 36-year-old patient had acquired 16 hospital stays in two years with frequent readmissions and declining health,” Dredge recalled. “This patient has since had only one emergency department visit and zero readmissions, reducing inpatient days by about 14 times her previous usage.”

“As health systems move into population health and value-based contracts, analytics are needed to identify patient populations and follow them through their care journey,” Dredge advised. “When selecting a partner, ensure there is alignment on goals and metrics.

“Understand what the healthcare organization should own versus accomplish with a partner,” he continued. “Controlling all aspects of care through internal resources can stifle innovation. SSM Health’s transformation team recognizes that a partner delivering an external, dedicated focus with tight integration and collaboration can speed innovation and raise all involved together for a better experience.”

This leads to a virtuous cycle of innovation where the more successful one is at making progress, the faster they can go, he added.

“SSM Health turned to a partner so it could dedicate its efforts to what the health system does well, which is providing quality care to its communities,” he concluded. “The partnership applied a dedicated focus to informing care that is innovating kidney care.”