Managing the health of your member population is an important responsibility, but also introduces some challenges. Identifying the right members, at the right time, for the right interventions, is no small feat – especially with limited resources. If we could wave a magic wand, we’d strive to impact every member in some way. The reality is that every member is unique and requires different levels of care, communication, and management. The sheer volume of members compared to the limited resources for engagement poses a challenge. It’s a balancing act to find the right members within the capacity of limited resources, time, and money, while also optimizing your digital strategy.
Consider the following members with type 2 diabetes mellitus (T2DM):
Although all are identified based on their type 2 diabetes mellitus, their circumstances and clinical profiles are very different. Advanced healthcare analytics can enable this kind of population classification, helping you to stratify your members by their anticipated care needs quickly and easily. The complexity and variation of clinical profiles and a member’s journey make the method you choose to categorize and stratify your members vital. Let’s discuss some of the key considerations, and how advanced healthcare analytics enhance population stratification.
Identifying the right members starts with a robust model that considers many different inputs. You also want to track and monitor the entire population over time as healthcare needs change. It is not as simple as knowing a member’s demographics, diseases, and utilization. While those are certainly important, there are many other factors that can help tell the story, such as socioeconomic circumstances, lack of engagement with a Primary Care Physician, or disease complexity. Sudden or acute situations may arise that warrant consideration as well, such as being post-surgery or receiving a brand-new diagnosis. It is only by looking at all possible factors together that we can get the most holistic picture of someone’s health. As that picture changes over time, we must be vigilant in re-evaluating all these elements so that we can be alerted when someone’s needs change.
“The custom analytic solution we developed lets us evaluate more patients, more efficiently, at every step. This allows us to align patients with end-of-life services that they can benefit from.”
– Corp Director, Facility Payor Strategy, ISHN Medical Informatics
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Once the identifying model factors are in place, think about how members will be stratified. To best plan for care manager resource allocation and your digital strategy, consider a model that will assign mutually exclusive categories, be time-sensitive, and based on the anticipated intervention needs. By doing so, care managers don’t need to spend time sifting through vast amounts of data, and instead are provided with pre-defined lists that have already been associated with an expected level and appropriate type of care management intervention. Because factors impacting a member’s health can change over time, you want the flexibility to re-classify members at any time to know whether they have moved in and out of different categories. This allows you to quickly respond to changes in an individual member’s health while also assessing overall emerging population trends and the level of resources needed to support them.
Once members have been bucketed into thoughtful groups based on anticipated member needs, determining the appropriate outreach for those groups should be straightforward and require minimal effort from a care management team. You may still need to consider things like what disease management programs you have available, what communication channel to use, which groups are the most actionable, or which groups would save the most costs in the long-term. Let’s revisit the members we mentioned above and see what this approach can show us:
Now knowing the classification category for each member, you’re ready to move to outreach. We know from the above that there are various factors that impact which category a member gets assigned to, and that information can be integrated and prioritized to a care manager’s workflow to provide a holistic view of the member. For example, Mark needs care coordination, but by pulling in his utilization, episodes, and gaps in care information as shown below, we get a better understanding of his 360-degree health snapshot. This provides the care manager with what they need to better serve the member, coordinate with multiple providers across complex care, and improve outcomes.
Managing your population’s health in the face of limited resources can be an overwhelming challenge. Members’ health status is complex, can be impacted by many different factors, and can change over time. To improve the health of your population while also making the most of care management resources, a stratification model that buckets members into meaningful groups with logical intervention strategies will accelerate your time to insight and drive real change. The right person, the right intervention, at the right time.