In addition to leveraging claims and clinical data, insurers are now relying on social determinants of health data to paint a better picture of their member populations, create meaningful interventions and manage risk.
The following article originally appeared in Health Data Management. Find the article online at https://www.healthdatamanagement.com/news/getting-social-why-health-plans-need-to-go-beyond-clinical-and-claims-data.
As value-based care models become more common, health plans are increasingly looking to address the specific needs of various populations to improve outcomes. In addition to leveraging claims and clinical data, insurers are now relying on social determinants of health data — information about the conditions in which people are born, grow, live, work and age1 — to paint a better picture of their member populations, create meaningful interventions and manage risk.
Consider the following examples:
A health plan experiences a resurgence of mumps within its member population. Claims data reveals that a large number of the children who are developing this disease have not received standard vaccinations. When the plan adds social determinants of health (SDOH) data into the mix, leaders realize that these mumps cases are emanating from children within the same school district or even the same neighborhood. To intervene, the insurer develops a care plan that prompts the parents to have their children to take part in well-care visits and receive vaccinations at age-appropriate intervals. As some of the children may come from non-English speaking families, the plan must also address language barriers by partnering with the school district to offer educational materials and presentations in various languages so parents can fully understand the importance of vaccinations.
Another example is if a health insurer is considering expanding into a new geographic area. Claims data shows that there is an unusually low usage of dental services in this area. The insurer could feel there is adequate network coverage but an analysis of SDOH data could reveal that a significant portion of residents in the area have transportation issues and cannot get to the service locations. As such, that analysis reveals that the health plan should consider adding transportation services if it expands into the area.
These examples illustrate how health insurers can leverage SDOH data to better serve members and manage their business.
“SDOH data, when used in combination with claims and clinical data, enables a health plan to build a model of a person. And when health plans have a cohort of individuals that share the same attributes, they can drill down and uncover valuable insights that can help the plan more successfully develop care and business plans,” said Ted Jones, Vice President, Government Engagement, Medecision.
Indeed, an analysis of SDOH information can help health plans go beyond simply developing care plans and offer the support that will help members adhere to these plans. For example, with SDOH information, health plans can ensure that members can access needed services.
“It’s one thing to have a care plan that directs a patient to attend therapy twice a month, but if members don’t drive, then the plan also needs to consider providing transportation services to ensure that the members can get to the therapy appointments,” Jones said.
Similarly, a health plan could create a care management plan that directs diabetic patients to eat a healthy diet but if members live in a food desert, then it’s unlikely that they will stick to the plan. To overcome this hurdle, the health plan could partner with a meal delivery service to ensure that members are eating healthy foods.
SDOH data’s potential, however, can only be realized if health insurers address the challenges that come with working with such data.
“The major challenge in using it is getting it. If health plans don’t have access to the appropriate data, then obviously they can’t use it,” Jones said.
While some SDOH data can be culled from EHRs and public sources, health plans also need to collect information from employers and members. When working with employers, it is important to garner details about the working environment. “Does everyone work in an office environment? Or do they work in a manufacturing environment? Or, are people working out in the field or in construction? Members working in various environments are likely to have different risks and different care needs. The chance of an office worker getting cut on construction equipment is very low but, of course, that risk is present for employees who are working in the field,” Jones said.
Care managers also can conduct interviews to collect SDOH information directly from members. During these assessments, care managers can ask extensive questions about an individual’s economic, employment, social and living situation.
When branching and skip logic are incorporated into assessments, the interviews can unfold just as normal conversations would. For example, “in the case of an individual that has difficulty walking, one of the questions might be, ‘Can you walk 20 feet without assistance?’ If the member answers ‘no’ the next question would address if the individual could walk those 20 feet with the assistance of a cane or walker,” Jones said.
After collecting SDOH information, health plans then need to use the information. A platform such as Medecision’s Aerial can help health plans integrate SDOH data with clinical and claims data, manage data in one central location and leverage analytics tools to “create the 360-degree picture of patients needed to develop the care management plans that can truly improve outcomes,” Jones concluded.
1 World Health Organization. Social Determinants of Health https://www.who.int/social_determinants/sdh_definition/en/