The Health Care Payment Learning Action Network (HCPLAN) has released a white paper on performance measurement within alternative payment models (APMs). HCPLAN work products will be considered by the Centers for Medicare and Medicaid Services (CMS) for implementation of the Medicare Access and Children’s Health Insurance Program Reauthorization Act (MACRA) and other health care payment reform initiatives. This white paper was developed by the Population-Based Payment Work Group and documents principles and recommendations for performance measurement.
Performance measurement currently faces multiple challenges, including a cacophony of measures with confusing results, the lack of available data to calculate important metrics, and burdens associated with capturing and reporting data. The Work Group conceives of measurement systems as being composed of three components, each of which is needed to reward providers who deliver high-value health care: 1) measure sets; 2) methods for evaluating performance on measures (e.g., performance scoring); and 3) methods for using performance assessments to adjust payment. In other words, in order to explicitly reward providers who deliver high-value health care via the payment model, measurement systems must necessarily specify measures, employ some method for calculating overall performance scores, and adopt some approach for adjusting payments in light of those performance scores.
The white paper outlines the following principles for performance measurement:
- Performance measurement is foundational to the success of population-based payment models to advance better outcomes for all patients and populations;
- Because population-based payment models address the full continuum of care, measure sets have to span the full continuum across time, across providers, and across settings;
- The measures required for the long-term success and sustainability of population-based payment models are fundamentally different from the measures used in traditional fee-for-service payment models; and
- To promote better results for patients and populations, the use of performance measurement for payment in population-based payment models must create meaningful incentives for improvement.
The white paper makes the following recommendations:
- To support the long-term success and sustainability of population-based payment models, future-state measures must be based as much as possible on results that matter to patients (e.g., functional status) or the best available intermediate outcomes known to produce these results;
- Because fragmentation across population-based payment models can undercut success, reliance on core measure sets is valuable; continued innovation and refinement are needed to ensure measure sets are comprehensive, parsimonious, and outcome oriented;
- A governance process is needed to oversee and accelerate the development, testing, and use of new, high priority measures for population-based payment models;
- In service of a future state that employs measures that are outcomes-oriented, the infrastructure nationally must be sufficient to systematically collect, use, and report clinically rich and patient-reported data;
- Providers in population-based payment models should have meaningful incentives to deliver high-quality care, achieve favorable health outcomes, improve patient care experiences, and manage the total cost of care;
- Measurement systems should define performance targets in a way that motivates ongoing improvement across the performance continuum, promotes best practice sharing, avoids a forced curve that mandates winners and losers, and enables long-term planning and commitment to improvement;
- Whenever possible, measure targets should be set in absolute (not relative) terms, established prior to the measurement period and fixed for a minimum of one year, although ideally for the full contract term;
- Measure targets should include a range of scores on each measure to enable the incentive system to reward both performance and improvement; and
- Adherence to good measurement science and implementation (e.g., sample size requirements, demonstrated reliability and validity, national acceptability, clinical importance, and the opportunity for a provider to improve before being held accountable under the new model) is critical to achieving the desired results from performance measurements in population-based payment models.