Health plans are actively seeking new ways to keep members healthy amidst the COVID-19 pandemic. Health insurers are looking to Vital Data Technology’s leadership in data science driven care coordination to help them identify at-risk populations and engage them to better handle the current care challenges.
Vital Data Technology’s Data Science Models Used to Combat COVID-19 In collaboration with health plan leaders, Vital Data Technology is deploying various data science models, as the company joins the fight to stop the spread and minimize impact of novel coronavirus. These use cases imbed the results of data science and further stratify the population using real-time data points germane to at-risk members.
Use Case #1a: Members Being Tested For COVID-19 With Underlying Comorbidities This data model enables Medical Directors and Care Managers to instantly identify members who were just tested for COVID-19. Once identified, health plan workers can segment the population by comorbidity condition, risk score and prioritize high-risk conditions such as Hypertension (HTN) and Chronic Obstructive Pulmonary Disorder (COPD). These insights are used to proactively intervene with those suffering from complicating medical factors.
Use Case #1b: Family Members With Underlying Comorbidities Of Members Being Tested For COVID-19 This data model enables Medical Directors and Care Managers to identify family members of enrollees who were tested for COVID-19 and cross reference their risk due to existing comorbidity conditions and risk score. Similar insights derived in the model above can then be used to proactively intervene in order of priority based on a family member’s preexisting conditions.
Use Case #2: At Risk Of Substance Use Disorders Due to mental health issues associated with social distancing and isolation, proactively identifying members that are most at risk can help with pre-emptive outreach and communication of available resources and information.
Use Case #3: At Risk For Substance Use Disorders And Projected Top 10% Of Costs Based on existing data science models, this use case identifies those members at most at risk for high cost and high risk. Health plans can perform advanced filtering criteria like: Line Of Business, currently in Care Management, no Primary Care Provider visit, no prescription, current risk score, social vulnerability/stress, and other data points..
Use Case #4: Social Determinants Of Health (SDoH) Driven Identification of Vulnerable Populations This model identifies those members that are most vulnerable by geography based on the Centers for Medicare & Medicaid Services (CMS) defined SDoH criterion. Early data shows those who are the most socially vulnerable are more susceptible to contracting the virus and are at a higher risk of death.
If you are interested in learning more about our Data Science capabilities or just want to understand how a real time data science enabled care coordination platform can help you deal with moments like this…
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