Challenge
A technology solutions company serving health plans and other risk-bearing organizations wanted to help their customers identify Medicaideligible members who were unlikely to recertify in order to:
- improve recertification rates and retention
- improve intervention targeting to increase
reimbursement
Solution
The company brought in Personify Health’s analytics team to analyze the Medicaid population of 17,000 enrollees across five states, including CA, GA, FL, NC, and TX. Personify Health leveraged its proprietary consumer database to supplement the client’s data and create a longitudinal view of each Medicaid member.
Personify Health applied advanced analytics to build models that determined likelihood of an individual not recertifying, but still Medicaid eligible. They identified key predictors, like previous year results, education level, health status, home value, and age.
Personify Health then prioritized the list of individuals at risk of not recertifying for interventions. This list was segmented by region and by the client’s customers. The interventions included IVR and phone call outreach. A control group was put in place to measure the success rate of the program.
Results
By applying its advanced analytics capabilities, Personify Health was able to deliver an elective target list for consumer outreach.
The intervention programs were successful in helping Medicaid members recertify.
Personify Health models successfully identified the top 25% that were 1.8x more likely to not recertify. Results also showed that there was a 39% decrease in recertification failure rate between the control and intervention groups.
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