Predictive Modeling
Identifying Risks. Roughly 20% of the employee population generates approximately 80% of all healthcare costs. The best way to contain rising healthcare costs is to improve the outcomes experienced by the 20% who drive those costs. Likewise, analysis of our members' claims histories over time shows that 3.4% of the population generates 50% of the total healthcare cost.
Health plans need a way to identify members with the highest risk for incurring significant healthcare costs so an intervention can be arranged. Also, improving overall member health status has many benefits to the employee and the employee and their families. Here's how an average member population would be divided into risk categories, and the suggested interventions for each group:
Member Population
Chronic Member Identification
Strategies for Intervention. Primary PhysicianCare has developed a predictive modeling software program which identifies and ranks members with chronic diseases based on the risk and severity of the disease. Our predictive modeling program analyzes up to four data sources: medical claims, prescription drug history, health risk assessments, and screening data. The software generates a report that ranks members by health risk, indicating their primary diseases, co-morbidities, and risk scores. The Chronic Member Report can be used to determine the most appropriate intervention plan and programs for intervening with this group.
Primary PhysicianCare also has the capability to import claims data or prescription data from any vendor or carrier and to combine HRA and screening data to produce a comprehensive Chronic Member Identification Report.
First, our predictive modeling software processes medical claims data, prescription drug data, health risk assessment data, and lab test results. Demographic and lifestyle data is included to increase the accuracy of predictions.
Next, a heuristic algorithm assigns risk factor scores to each piece of collected data, and these scores are used to generate a weighted score for each disease state. The weighted scores are combined and adjusted based on age and lifestyle factors
Finally, members are stratified by their combined and adjusted scores. This stratification is detailed in the DM Identification Report, and the number of members requiring Disease Management is determined. These members are electronically loaded into our database for intervention.
informed choices ... healthier lives.
