Technology continues to improve many areas of our lives, including healthcare. Using emerging technologies such as artificial intelligence (AI) and predictive analytics, diagnostic efficiencies have improved significantly. Healthcare IT News brought this interesting information to our attention in their article, “SSM Health innovates kidney care with predictive analytics and machine learning.”
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.
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 (SDOH), algorithms can predict adverse events, including kidney failure during a given time frame or a cardiology event.
Health systems continue to move into population health and value-based contracts paving the way for analytics to identify patient populations and follow them through their care journey.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
