Understanding the Opportunities and Challenges of Value-Based Purchasing

May 02, 2018

Value-based purchasing is a growing effort in the United States to pay health care providers on the basis of quality and efficiency rather than the volume of services provided, as is the case with conventional fee-for-service reimbursement. In a recent speech to the Federation of American Hospitals, U.S. Secretary of Health and Human Services Alex Azar called for bold new approaches to accelerate the adoption of value-based purchasing in health care. He also noted the need to create stronger incentives for providers to improve care while also giving them the flexibility to experiment to find out what works.

Mathematica has been at the forefront of designing, implementing, and evaluating current value-based purchasing efforts and working with the Centers for Medicare & Medicaid Services and other federal and state agencies to provide technical assistance and data feedback to participating providers. In light of Secretary Azar’s speech, we talked with two senior health researchers at Mathematica, Sue Felt-Lisk and Craig Schneider, to get their perspectives on how providers are responding to value-based purchasing, what challenges they face, and how to better support providers to achieve success as additional reforms are underway.

What strategies have health care organizations pursued to make the changes they want when faced with new incentives under value-based purchasing? 

Craig:

First, it’s important to understand the challenges that clinical organizations face when trying to make the transition from fee-for-service to value-based care. Mathematica has identified a dozen or so core competencies required to meet these challenges, including integrating health information technology systems, engaging physicians in changing their practices, engaging patients in their care, creating patient loyalty, coordinating care across the continuum, capturing data, making data timely and actionable, improving quality measures, integrating behavioral health care and social determinants of health with clinical care, and transforming the organizational culture to make these changes effectively and efficiently.

Health organizations use a number of strategies to meet these challenges. First, health leaders must be fully committed to changing structures, incentives, and culture to facilitate the transition from volume-based care to value-based care. Engaging physicians is critical, and identifying physician champions who are respected by their colleagues and will embrace the new procedures to improving quality and efficiency is an effective strategy. In addition, nurse care managers play an important role working with patients to involve them in their care. We’ve also seen the importance of engaging high-use patients early—and developing predictive analytics algorithms to identify who those patients will be—to reduce costs in the long run.

Sue:

 

How has implementation of these strategies for delivery system transformation proceeded?

Craig: The Centers for Medicare & Medicaid Services has shown impressive leadership in developing a number of different models enabling clinical organizations to select the best approach for them with an appropriate level of risk. Multiple private sector plans and state Medicaid agencies have joined the effort to develop value-based payment systems. It wasn’t long ago that value-based care was seen as a niche effort, but it is increasingly becoming the way the majority of care is delivered in the United States.

Frankly, the results to date have been mixed, but that’s to be expected in a challenging, experimental effort. The barriers to success are formidable, and it might be hard for providers to see how the actions they take today might benefit their patients and result in shared savings in the future. One approach that Mathematica has found effective and valuable is for clinical organizations to participate in learning collaboratives, in which they share lessons learned and promising practices. With multiple challenges and various pilot projects to test out solutions to these challenges, organizations have a lot of experience to share with and learn from each other.

Sue:

 

What types of technical assistance have these health care organizations sought out as they attempt to make complex changes? In particular, what types of data or sources of information have been useful to these organizations?

Sue: There’s a perception that so much of the data that providers receive is not very useful because the data are too old, are limited to one payer’s population, appear incomplete or inaccurate, cover things outside their control, or are focused on measures that they don’t view as important.

But there are many examples of providers that use carefully produced data to prompt friendly competition that ends up raising the performance of all involved. The key is full transparency—including non-blinded data—and that involves getting everyone to buy in and see the value. Within an organization, versions of this have worked down to the unit or individual physician level. The units or providers that appear on the bottom are typically extremely motivated to move up, and others not yet at the top set their sights on becoming number one. Because everyone knows where everyone else stands, peers lagging behind can find others who they consider similar and are doing much better and can talk to them about how to improve. In hospitals, electronic health record systems often produce real-time or near real-time alerts when it looks like a protocol is not being followed so that the individual situation can be addressed right away. Our sense is that a lot of that really happens and improves care. So far, we have not heard of a successful parallel among physician practice systems; complaints abound that their systems often alert them excessively to things that are not really important.

Craig:

 

What lessons have you learned from technical assistance initiatives and providing data feedback as health care organizations undertake efforts to change?

Sue: You have to meet health care provider organizations where they are. Practices and hospitals range from completely old-school organizations to modern transformed practice concepts that include population health and effective links to community supports. Any assistance to providers must start with understanding where they are and bringing next steps to them.

A second lesson is to find quick wins to go along with the more challenging aspects of change. Helping practices address something that is bothering them, even if it isn’t very important to long-term change, can build momentum and lay the groundwork for more complex aspects of change.

Also, because electronic health records are key enablers of improvement, it’s really important to help make practices’ electronic health records work better to support change. Sometimes this can be done through user groups focused on using specific systems to improve, in which participants can share tips and experiences. Hands-on expertise is also key to getting past hurdles, whether that expertise is available from a supportive organization or has to be provided through the electronic health record vendor.

Many people in health care organizations don’t have time to sift through all of the tools and information sources and decide on an optimal solution. They need a trusted individual to steer them to tools and knowledge that not only are effective but also fit their organizational situation, including their resources and systems.

Making effective changes to improve care and show results is usually harder and takes longer than anyone thinks, but we can’t let that discourage us from the work. Health care is such a complex process, and patients are a key component whose behavior can sometimes be influenced but not controlled. There is a growing belief across practices and hospitals that more effective engagement of patients and families in their own care is going to be a critical way of improving health and health care over the next decade.

Craig:

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The opinions expressed are those of the author(s) and do not represent those of Mathematica Policy Research.

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