It’s fair to say that a primary goal of population health management is to move from illness treatment to illness prevention—and to improve health outcomes along the way. Getting there, however, is another story.
Until recently, care management has been a largely retrospective endeavor. While care management tools have done a good job of collecting data on individuals’ diagnoses, visit histories and claims activity, most have fallen short of enabling deep insights into both historical and real-time events.
Going forward, next-generation care management will require organizations to do a better job of understanding and predicting factors relevant to care delivery and outcomes. Payers must be able to transition from thinking about members in terms of existing disease (e.g., diabetes) and instead thinking of them more holistically and prospectively, as unique individuals.
Flexible data strategies will be essential.
Take a predictive approach
For next-generation care management models to succeed, analytics and predictive modeling must be used to proactively determine how, when, where and why to provide care. These models should be deployed quickly and broadly to the highest cost populations first, to start driving outcomes while engaging members more fully in their own care.
Here are three strategies to navigate toward next-generation care management and increase member engagement in the process:
- Build a Strong Data Strategy
Next-generation care management relies on solutions that ingest data from disparate systems and store it in a single location. From there, data can be visualized by the care management team, which can develop actionable care plans for members and member populations.
By interacting with all member data, organizations can achieve deeper analytics insights that drive more effective interventions. But while integrated data is needed from internal and external sources, a strong data strategy isn’t about volume. More data doesn’t improve health if it can’t be integrated to build a holistic view of members.
To be most effective, data needs to be available in real time.
“Delayed or historical data hinders the ability to make timely decisions that impact both the member and the providers across the continuum of care,” says Mary Kay Plona, principal with Medecision Aerial Advisory Services.
“Old data doesn’t help organizations meet the growing demands of the populations they serve,” agrees Jackie Luchsinger, RN, MS, MBA, PMP, a principal with Medecision Aerial Advisory Services. By contrast, “data that’s as close to real-time as possible can assist providers in making the right care decisions, at the right time using the right resources—a huge transformation in proactive care management.”
To move forward, stakeholders should hold working sessions to outline what data they currently have available, and identify the internal and external data that’s needed to solve key business objectives. The next step is to pinpoint the gap between the two. This valuable insight can be used to solidify a data strategy, as well as prioritize funding and timelines.
A strong data strategy may also require new partnerships. Organizations should partner with population health management experts and leverage their ability to ingest, manage and analyze data quickly—and without bias or allegiance to specific technology vendors.
2. Glean Insights Through Analytics.
Data is only as good as the insight that can be gleaned from it. That takes powerful analytics that can separate overall populations into meaningful, manageable segments. With more insight into the care needs of each segment, organizations can deliver more targeted and proactive services to engage members and reach better outcomes at lower costs.
To do that, organizations should look for key analytics capabilities. These might include the ability to identify and stratify risk, find gaps in care, provide predictive modeling, use clinical intelligence rules, and offer dashboard reporting.
Visualization and discovery tools bring all of these capabilities together. “Connecting large, complex, multistructured data sets helps users predict and discover trends and hidden patterns,” notes Carolann Engler, another principal with Medecision Aerial Advisory Services. However, it’s important for visualization tools to be flexible based on who is accessing information. Executives need aggregated data and reports in a dashboard format, so they can see the high-level picture and spot trends within the populations they’re accountable for. Clinicians need to be able to deep-dive into data for insight at the member level, and then help them understand what clinical and social interventions best apply.
3. Connect Insights to Programs
Changing payment models put pressure on care management teams to focus intervention efforts on specific clinical programs. These can include bundled payment programs, quality reporting programs, ACO programs, and others that target specific disease states or socio-economic issues. With the ability to apply clinical intelligence rules and predictive modeling to data sets — and thus identify population concerns automatically—care managers can focus on connecting directly with members instead of having to mine data themselves. That saves time and increases care management effectiveness overall.
“Ultimately,” says Engler, “a successful care management program needs to answer the questions: Are we reaching and managing the right group of individuals? Are our efforts making an impact? Are there variations across care teams that we can standardize for improved outcomes? Where are the opportunities to change how we identify members, and how we direct them to the level of support that can positively impact health and costs?”
Better patient engagement is within reach
Next-generation care management that is tailored to the pursuit of improved population health is within reach. By building a strong data strategy, gathering insights through analytics, and connecting those insights to care programs, health plans can pave the way to better member engagement and outcomes. In so doing, they can make marked progress in the evolution from disease treatment to prevention and wellness.