Linking Spending and Quality Indicators to Measure Value and Efficiency in Health Care

Abstract

Policy makers and stakeholders have reached a consensus that both quality and spending or resource use indicators should be jointly measured and prioritized to meet the objectives of our health system. However, the relative merits of alternative approaches that combine quality and spending indicators are not well understood. We conducted a literature review to identify different approaches that combine indicators of quality and spending measures to profile provider efficiency in the context of specific applications in health care. Our investigation identified seven alternative models that are either in use or have been proposed to evaluate provider efficiency. We then used publicly available data to profile hospitals using these approaches. Profiles of hospital efficiency using alternative models yielded wide variation in performance, underscoring the importance of model selection. By identifying the current efficiency models and evaluating their trade-offs within specific programmatic contexts, our analysis informs stakeholder and policy maker decisions about how to link quality and spending indicators when measuring efficiency in health care.

Ownership structure and hospital service costs and fees: A decomposition approach

“…See also Roseboom, van Dongen, Tompa, van Tulder, and Bosmans () for a comprehensive approach to using economic evaluations in the Dutch health care system. Lastly, see Ryan, Tompkins, Marvitz, and Burstin () for an extensive review of the impact of quality and spending on the efficiency of health care services provision.…”

Accounting for accountable care: Value-based population health management

“…As I will show, such information – structured and collected for entirely different purposes – is being repurposed in efforts to draw conclusions about patients and their health. Intensified surveillance and big data analytics (natural language processing machine learning, and predictive analytics) are used to handle the large volumes of complex data, and make it possible for information about individuals to be disaggregated and compared across population-based datasets, to compare individuals against themselves, or to compare providers against each other and to identify misalignments with the ACA quality and outcomes measures (Bates et al, 2014; Ryan et al, 2016). Once the infrastructure and arrangements are in place to collect and store data, consulting or insurance companies or ACO data analysts can then do endless variable querying, well beyond reporting requirements.…”

Value‐Based Payments in Health Care: Evidence from a Nationwide Randomized Experiment in the Home Health Sector

“…In health care, these arrangements provide financial rewards to providers to incentivize improvements in the quality of health care supplied to patients. Despite becoming a mainstay health policy approach, studies examining these programs have reported minimal effects on quality (Doran, Maurer, & Ryan, 2017; Jackson, Rockoff, & Staiger, 2014; Rosenthal & Frank, 2006; Ryan et al., 2016; Scott, Liu, & Yong, 2018). These disappointing findings have led some to argue that these types of designs are too complex or that incentives are too small to elicit responses from health care providers (Figueroa et al., 2016; Ryan et al., 2017).…”