Migrating Incentives from Measurement to Learning

Over the past three decades, an overreliance on quality measures as a material driving factor in value-based payment (VBP) arrangements has created an adverse trade-off within delivery systems: achieve short term performance goals versus establish continuous learning and improvement as a basis of developing a learning organization. Whether applied to large integrated delivery systems or among primary care practices, quality measure-based VBP designs continue to limit the ability of providers and groups to explore novel ways of improving patient care through systematic quality improvement efforts.

In other words, the fundamental constructs underlying most VBP systems incentivize the implementation of a care model believed to be evidence-based, as opposed to incentivizing the capability to implement any care model ad infinitum.

Innovation is one of the hallmarks of the U.S. healthcare system. Technical innovation, care delivery innovation, innovative partnerships, and more—the list of innovations in the American healthcare system is long, and for the most part, contributes to the capacity of its delivery system to occasionally provide the highest quality care in the world. The most common way that public and private payers attempt to incentivize the adoption of new innovations is through some kind of VBP arrangement. These arrangements, however, frequently target a single innovation (e.g., adopt EHRs that have certain capacities, establish a patient-centered medical home, implement medication management programs, improve patient hands-offs), as opposed to targeting the underlying functional requirements needed to adopt all current and future innovation. This—the capacity to perform systematic quality improvement—is the base element of a learning organization.  Innovation is inevitable, but the way an organization pays for adopting it must reflect the agile nature of the innovation itself.

Drawbacks of Reliance on Quality Measures

Over the past 10 years, the Centers for Medicare and Medicaid Services (CMS) has paid commercial vendors over $1.3 billion dollars to develop over 2,300 quality measures used across 34 federal and state programs. These measures are also used in many commercial VBP arrangements nationwide. The assumption driving this obsession with measures is that some point in the past represents an accurate baseline—or, if projected forward, a counter-factual against which the impacts of an intervention can accurately be measured. However, empirical evidence does not support this. Mounting evidence shows that increasing the number and specificity of quality measures in pay-for-performance programs has promoted adverse behaviors amongst providers (for example, reducing tracking efforts of hospital acquired infections; increasing the diversion of needed resources away from improving patient care and toward reporting activities; and driving provider animosity and isolation from larger efforts to improve care). Beyond this, developing static baselines is inherently an effort that disregards exogenous conditions of the delivery environment. Risk adjustment is also an infinitely complex effort, often producing unintended consequences—which will always be the case. Reporting on these measures costs providers an estimated $15.4 billion dollars annually.

CMS reports that it has reached its goal of 90% of payment tied to value-based reimbursement methodologies—nearly all of which rest on a chassis of performance metrics. Not surprisingly, many of these flagship programs, like the Hospitals Value-Based Purchasing Program (which uses 20 separate quality metrics to measure improvement), have been found to have no effect on quality of care, patient satisfaction, or mortality.

Considerations for VBP Program Design

Quality measures serve an important role in monitoring patient outcomes and care processes. However, their role in payment systems should primarily support surveillance and provide indications of when and where further root cause analysis may be needed to delineate between systematic failures in care delivery from statistical aberrations in measurement values. VBP arrangements should instead orient incentive payments toward the development and application of the technical capacities needed to implement systematic quality improvement efforts. In short, organizations must stop paying for measurement results and start paying for proof that results are realizable.

PCG’s quality experts have created VBP programs for public and private payers that do not put quality metrics at the center of incentive designs (whether they are based on prospective or episodic payments, total cost of care, or simple pay-for-performance methods). We have found that reorienting and repositioning quality metrics as imperfect surveillance tools that primarily assist in indicating directional validity of quality improvements, and which can be leveraged to impact overall program oversight, is essential for deconstructing the false trade-offs that current VBP arrangements have created.  Once this shift has taken place, an emphasis on targeting and implementing the base elements of a learning organization can take place. Only then will VBP arrangements stop targeting one single source of innovation and instead begin targeting all current and future innovations.

To learn more about designing VBP programs that do not center quality metrics in their incentives, feel free to contact Aaron Holman (AHolman@pcgus.com).

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