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Is your state’s Medicaid program ready for value-based care? Here are six things to consider.

In our last blog, we profiled several states that are transitioning their Medicaid programs to value-based care models. As we noted, some states are likely better prepared for the change than others. But how can states know if they are ready to “walk-the-walk” down the value-based care path?

Medicaid program leaders should first consider assessing readiness. Does the state have the right resources, operating model, and infrastructure to introduce a new payment model? Can the Medicaid program maintain operations while exploring and implementing a new model? More importantly, does the agency have the capacity and willingness to transform long-standing processes?

Six competencies to evaluate

A strong foundation is essential when building a new payment model. We have assembled a set of six broad guidelines to help states and Medicaid agencies gauge their readiness levels. We encourage state Medicaid leaders to consider this list before beginning their value-based care journeys.

1. Health systems and market dynamics: Value-based care strategies, particularly those that revolve around accountable care organizations, rely on collaborations between providers and health plans. That poses several questions for states. What is the relationship between these two groups within the state? Is it collaborative or adversarial? Are there dominant players? Is it an attractive market for new entrants and/or for existing entities to bear risk? Understanding these dynamics will be helpful when charting the path to value-based care.

It is also important to determine how comfortable providers are with taking on financial risk (both upside and downside). If value-based care has already taken root in commercial populations, or within Medicare, there may be more appetite for moving Medicaid in the same direction.

States also should consider that some value-based care models include community organizations as participants. States should assess the capabilities of these entities and their relationships with health plans and providers.

2. Stakeholder engagement: Internal and external communication channels are essential to solicit and receive feedback from stakeholders. How does the state typically engage stakeholders when the Medicaid program goes through a change? Many states already have robust structures in place. This includes regular communication with advocates, industry groups, and provider associations. Medicaid agencies should consider leveraging what they already have, or stand up new mechanisms to encourage regular feedback with stakeholders. If external stakeholders aren’t on board with the transition to value-based care, they might block progress—even becoming vocal critics in the media or to state lawmakers. But these groups also can help ensure the program’s success by embracing and championing the change.

Another key stakeholder is the US Centers for Medicare and Medicaid Services (CMS). This agency can help to guide a program’s success. The Medicaid agency should consider maintaining an open line of communication with CMS, which often must waive traditional Medicaid requirements for states to implement value-based care programs. More innovative programs might push the boundaries of CMS’ past approvals heightening the need for states to clearly communicate the elements of the proposed program.

3. Funding: Change is hard. It also tends to be expensive, and likely will require a dedicated funding stream (state and/or federal) to support the cost of program transformation (including technology, analytics, and operational and policy changes). What funding streams does the state have in place today? Will it be enough? Leaders should determine if existing funds are available, or if additional funding needs to be identified. New funds also may be needed to help hospitals, physicians, and other providers develop analytic, actuarial, and/or technology capabilities to succeed in the transformation to value-based reimbursement.

4. Project leadership and staff: Shifting to a new payment model is a transformative process that can’t be accomplished without a champion. The transition will likely impact all aspects of the organization. Does the state have a leader who is committed to and passionate about value-based care? A strong leader or leadership team can be essential for driving the initiative and for owning the project. If that person isn’t apparent, the department should nominate someone, or recruit talent from outside. Most importantly, everyone—from leadership on down—should support the transformation. Any apprehension should be channeled into efforts to address open questions and mitigate risks. Staff members might need to balance their daily duties with project responsibilities. Alternatively, some staff might need to transition to a dedicated project role, while others take on their day-to-day responsibilities. Leadership and staff should have the capacity and the support to participate. Outside resources might be needed.

5. Data management: Encounter and claims data can be essential in the transition to value-based care—from establishing a baseline prior to the change, to understanding member and provider relationships. The implementation’s progress should be monitored and costs and outcomes should be measured. Medicaid program leaders should determine if data from the health plans are reliable. Can the data be used to make initial program design decisions as well as support ongoing performance measurement? Medicaid programs with poor encounter data might want to dedicate time and resources up front to improve the completeness and quality of the information before considering a value-based care model. Without reliable data to measure program performance and support payments, it can be difficult to assess whether the value-based initiative is working as envisioned. It also might be impossible to operationalize the model because encounter data are critical to establishing networks, attribution models, and baseline data.

6. Technology: A move to value-based care will likely require strong technology support. This includes technology to administer the program and to support members and providers in the new environment. For example, the new program requires robust data warehousing, reporting, and analytics capabilities. The ability to process and manage new reimbursement methodologies is also needed. The existing information technology (IT) team, and the technology infrastructure, should be flexible so that required changes can be implemented smoothly. Consider how changes fit into the organization’s long-term technology strategy.

Some of the self-assessment considerations we’ve outlined are more important than others depending on the state and its vision for value-based care. If some capabilities or skill sets are missing, that shouldn’t derail efforts to change. It might only mean that more homework is needed, or that additional resources are required. But before embarking on the journey, Medicaid leaders should determine if they have the necessary foundation in place, or if more time is needed to strengthen the program’s operational and technology base.

Author bio

Jeff Burke is a Senior Manager in Deloitte’s Public Sector practice with more than nine years of state government consulting experience, focused on strategic planning, project management, organizational design and improvement, program transformation, operations improvement, and process reengineering. He has experience managing projects on a range of issues, including value-based care, payment reform, Medicaid Managed Care, and health care reform.

Matt Siegel is a Specialist Leader in the Life Sciences and Health Care practice of Deloitte Consulting.  He has led engagements with health care provider, health plan, and government clients seeking to develop and expand their use of data, analytics, and technology to position themselves for successful transition towards population health management and value-based care. Matt has more than 25 years of experience in health care strategy and solutions, predominantly in data analytics, risk stratification, and population health.