Published on August 28, 2020
Using traditional data sources, like claims history, is a fair way to predict your members’ future needs — providing nothing unexpected happens. For example, when the COVID-19 pandemic reached the U.S., long-standing risk prediction methods weren’t able to help health plans and providers to identify and meet the urgent needs of the populations they serve.
Health Alliance Plan of Michigan (HAP) knew that the pandemic would exacerbate its most vulnerable members’ underlying Social Determinants of Health (SDoH). HAP wanted to take immediate action to limit the adverse health outcomes that could come from changes in income, food availability, or housing circumstances.
HAP approached Carrot Health looking for a way to identify the top 10% of its members with SDoH-related concerns so it could prioritize and customize outreach to them, moving quickly to fulfill their immediate needs.
Carrot Health’s COVID-19 Index ranks the populations most likely to have a critical illness after contracting the SARS-CoV-2 virus. Our Social Risk Grouper (SRG) is an SDoH taxonomy that uses consumer data and predictive analytics to assign risk to every adult in the U.S.
By combining these tools and applying them to the entire HAP group, we could identify members at the highest risk for poor COVID health outcomes. Then, we stratified individuals within that group into four subcategories — those at mild, moderate, moderate-high, and high risk. HAP assigned a specific action plan to each subgroup and began its outreach program.
The HAP team contacted 42% of the 7,676 members identified for phone outreach. During those conversations, callers referred to Carrot SRG scores to triage at-risk members and match them with internal resources. Among other positive results, HAP staff connected more than 2,000 people to community programs that provided them with meal benefits. The response from members who received phone calls was overwhelmingly positive.
By leveraging Carrot Health’s predictive analytics, HAP moved swiftly and efficiently during an unprecedented health crisis to address its most vulnerable members’ immediate needs. Targeting SDoH-related risk factors well ahead of illness helps reduce the long-term cost of treating subsequent health outcomes. HAP’s proactive approach also made an impression on members who expressed surprise and delight that their health plan was actively concerned for their well-being.
For a closer look at how our predictive analytics can help payers and providers stay agile in a changing health landscape while building member loyalty, download the case study, “Proactively Addressing Member SDoH Needs During COVID-19.”