Organizations are applying population health management (PHM) protocols to ever-increasing shares of their patients, hoping to extend the PHM care delivery model and infrastructure across a wider array of value-based programs. As providers look to transfer the industry’s best practices into their specific environments, they need some degree of comparability and commonality among PHM initiatives so they can assess them for applicability to their context. What they’re finding, though, is that tactics used with one sub-population (e.g., Medicaid) may not be entirely transferable to all populations (e.g., disease-centric or ACO programs). The characteristics of the managed population, the factors involved in varying payment models, and other differences among PHM deployments make it difficult to evaluate and extend PHM best practices and models.
In the real world, healthcare is not a one-size-fits-all model, as programs, population characteristics, objectives, incentives, and more can vary widely. Success is influenced not just by the specifics of the program itself, but the nature of the populations that are being managed – so healthcare providers tailor their approach according to the needs of their population and how their results are measured and incentivized. If a program takes on more downside risk, for example, or rewards certain activities such as outreach, healthcare providers will organize themselves accordingly. Such diversity means that success in one program may not easily translate to success in a different program.
True population health management begins when you reach beyond the specifics of an individual program to support all of care delivery. Technologies used today to support Medicaid Health Homes will support ACOs and DSRIP solutions tomorrow, and eventually become ubiquitous, not measured by what programs they support, but how we standardize care delivery across different programs. Population health management programs – and the technologies that support them – require certain fundamentals to achieve success and enable widespread collaboration that transcends the walls of an individual organization. These strategies include:
- Care teams – Effective collaboration needs a team working together to ensure the health of a patient, and a coherent vehicle for collaboration such as a care plan or other centralized mechanism so the team can understand intentions, give input, and share information. To be comprehensive, the team should span multiple organizations and care settings, accounting for behavioral and social factors in addition to medical.
- Care manager – Care teams need a quarterback to make sure the team is operating effectively and to fill in the gaps.
- Recognition that all patients served are not equal – Populations need to be stratified to identify the patients that need more extraordinary interventions versus people that do not, so that the higher-risk patients get the more intense collaboration they need.
- Feedback and learning – The team needs a way to understand how well it’s doing and get guidance on what they should be doing differently so they can improve the effectiveness of their care delivery.
These issues should sound familiar – discussions about population health and fee-for-value programs talk about all of them. However, there is a disconnect between how programs are incentivized or mandated, and the effective use of these fundamental strategies. Typical measures, such as money saved or whether a team achieved a certain quality measure or reduced emergency department usage, do not show whether population health management is effective, but whether it was applied appropriately in a specific context. As long as these context-specific measures are widely used, it will be hard to understand whether success is transferrable across operating models, systems, and programs. This is further compounded by the lack of standardization across programs for how PHM is performed, and the fact that these PHM fundamentals may not even be in use.
Another factor limiting the universality of PHM is the degree of variation among the populations across different programs. Medicaid Health Homes and Medicare ACOs, for example, highlight different population demographics, care needs, and management approaches – and have different outreach strategies, utilization patterns, and other relevant dimensions. For instance, Medicaid populations may require more social services like housing assistance, whereas Medicare populations may leverage more long-term care. These variations in care translate to different metrics for success and differences in care plans for patients, which in turn make the management of these programs appear very different on the surface. This apparent deviation of practice from population to population potentially masks transferable hallmarks of success, such as integrated longitudinal care plans and effective workflow designs for care teams.
So, the answer to the question is that no, population health management is not universal. But it can be—and should be. Understanding how PHM has been implemented successfully in other contexts and how it can be comparably deployed will guide technology, staffing, and governance decisions, and thereby propagate the best PHM has to offer. If we want the definitions of value-based programs and population health management to have true meaning, we need to look beyond incentivizing and managing the factors that have significance for an individual program, and encourage the measurement of the fundamentals of healthcare delivered using core PHM strategies. Organizations need to approach care delivery models from a more holistic viewpoint, focusing on the big picture of care rather than the rules for how they get paid. Instead of addressing the needs for a Medicaid Health Home or a particular kind of ACO, they need to change the way they do business.
Many big payers have transitioned more than half of reimbursements to a value-based model, so this type of care represents more and more of the revenue mix for providers. Organizations need to respond by setting up the infrastructure that supports the fundamentals of population health management. By thinking about these issues more broadly, healthcare providers will avoid pigeonholing their organization into what’s necessary for a specific paradigm today, and be better prepared for tomorrow.
So how do we do that?
The decisions about how to manage population health and value-based care delivery are made at the executive level among those who have a broad understanding of what the healthcare organization is trying to do. The CEOs, CIOs, CMIOs, and CFOs set strategy and determine direction, purposefully enforcing some common elements across specific instantiations.
Their challenge is to ensure that the way they’re measuring results adheres to the fundamentals for population health management, and to establish common infrastructure across the entire organization that can be leveraged by all programs that need it. They should measure effectiveness not just by what is held out by payers for reimbursement, but by how well programs are adhering to these fundamentals. This shift in focus will enable organizations to show success across the board rather than for a specific program.
When these fundamental strategies do yield success – and they will – the industry will benefit from understanding how these successes are built on more than outcome measures alone. By being true to the fundamental strategies and sharing the process measures that work within their contexts, particularly those that are expressed in terms of population variables, providers can help establish more effective best practices that move the industry toward true population health management.