A Technology Solutions Company Used Advanced Analytics to Achieve a 39% Lower Recertification Failure Rate


A technology solutions company serving health plans and other risk-bearing organizations wanted to help their customers identify Medicaid-eligible members who were unlikely to recertify in order to:

  • improve recertification rates and retention
  • improve intervention targeting to increase reimbursement


The company brought in Welltok’s analytics team to analyze the Medicaid population of 17,000 enrollees across fi ve states, including CA, GA, FL, NC, and TX. Welltok leveraged its proprietary consumer database to supplement the client’s data and create a longitudinal view of each Medicaid member.

Welltok applied advanced analytics to build models that determined likelihood of an individual not recertifying, but still Medicaid eligible. They identifi ed key predictors, like previous year results, education level, health status, home value, and age.

Welltok 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. 


By applying its advanced analytics capabilities, Welltok was able to deliver an effective target list for consumer outreach. The intervention programs were successful in helping Medicaid members recertify.

Welltok’s 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. 


  • 25% of most at-risk members were identified
  • 39% lower recertification failure rate