The health system is reducing acute utilization with ER utilization for chronic kidney disease and the end-stage of renal disease.
SSM Health, a nonprofit, along with $8 billion in revenue, is providing the community with high-quality care for vulnerable populations. The most vulnerable populations is made up for benefiting the patients with kidney disease. This innovation offers care with predictive analysis and machine learning.
Kidney disease is much more complex as 90% of people with kidney disease do not know they have it. The situation comes to light until they need a transplant or dialysis.
There are many little disease educations with preventive methods for the initial stage. However, it makes kidney disease much more expensive to treat.
CKD and end-stage renal disease in patients require 15-20 medications daily. Also, it requires many comorbid conditions, which make the treatment complicated. According to Carter Dredge, patients with kidney disease usually make up to 5% of the population, yet they account for more than 20% of the cost.
The health providers are seeing a major range of health concerns and CKD, which often involves five to 10 patients in their panel. SSM Health needed a solution with much focus to help the prediction at the best time to engage in effective treatment with lower cost.
Analytics is capable of offering diagnostic assistance with guiding treatment decisions. With the combining of data from various sources, with claims, clinical data services for CKD and ESRD patients to improve the care quality.
Also, it lowers the total cost of care for patients. Thirty-three of algorithms assist with the treatment of CKD. It includes one that can predict the progression of CKD to ESRD with 95% of accuracy.
The platform of Strive Health CareMultiplier is powered by a proprietary machine-learning algorithm. It also includes a massive amount of data which cuts the noise and allows the clinicians to focus on doing what they can do. Hence it delivers high-quality patient care.
Their clinical team is using predictive analytics in their day-to-day care. Each of the patients receives an overall risk score which is serving as a starting point for treatment.
It has benefited several patients, including one female patient with a 57% chance of kidney failure within two years.