Healthcare data analytics provider Advanced Plan for Health (APH) has added predictive modeling functionality to its platform for population health management, the company revealed.

APH’s flagship product, Poindexter, will now enable providers to determine the likelihood of an occurrence of coronary, neurological or orthopedic events and chronic kidney disease. In addition, Poindexter now has the ability to predict hospital length of stay and general likelihood of an ER visit for any member of a patient population.  

The company said third-party administrators and brokers can leverage Poindexter's new functionality to better identify at-risk individuals in their customers' insured population. Employers with self-funded health plans can directly benefit, too. APH’s data services are used by brokers, employers, providers, health plans and others to optimize health benefit programs.

Currently, the Poindexter engine calculates care gaps and predicts the likelihood of hospital admissions, as well as readmissions, 6 to 12 months in advance for any given patient population — typically covered lives in a self-insured employer's health plan. The tool also examines data from claims, pharmacy and clinical sources, benchmarking against real-world health data adjusted for comparable demographics, geography and industry of the employer.

Poindexter assigns risk scores to individuals within that population – identifying people whose health profile suggests elevated risk. With this information, case managers can improve outcomes and lower costs when they help patients avoid catastrophic events by improving their health through timely interventions.

"As data science and predictive analytics technologies get sharper every year, we hardwire new innovations into Poindexter so self-insured employers can mine actionable data and help their employees live healthier lives," Neil Godbey, CEO, Advanced Plan for Health, said in a statement. 

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