Michael Trisolini

Pay for performance in health care: Methods and approaches

document when you quote from it. You must not sell the document or make a profit from reproducing it. Chapter 4 Concerns about quality of care have accelerated since the 1990s, as studies by Wennberg, Fisher, and others have documented large and unexplained variations in rates of health care utilization and clinical outcomes across geographic areas, calling into question the traditional approach of relying on the medical profession to deliver high-quality care uniformly (Davis & Guterman, 2007; Wennberg et al., 2002). Since about 2000, several landmark publications have highlighted widespread problems with patient safety and quality of care, most notably from the Institute of Medicine (IOM) and the These studies helped to galvanize a policy consensus, leading the federal government and private health insurance plans to increasingly focus policy, regulatory, and management interventions more directly on quality of care measurement, quality improvement programs, and financial incentives for quality improvement through pay for performance (P4P). P4P programs have focused primarily on quality of care measures to assess provider performance. Although other performance evaluation approaches, such as efficiency measures, are possible for P4P, those in policy circles currently perceive the lack of incentives for improved quality in the prevailing fee-for-service (FFS) payment systems as a major problem in the US health care system. As a result, P4P programs have focused mainly on addressing this problem. This chapter reviews issues regarding the application of quality measures in P4P programs. The first section of the chapter provides background, including conceptual frameworks for quality of care, and reviews organizations that develop and certify quality measures. The second section discusses different types of quality measures, including structure, process, and outcome measures (Donabedian, 1966). The third section reviews issues in selecting quality measures for P4P programs. The fourth section describes methods for 100 Chapter 4 analyzing quality measures for P4P. The fifth section discusses public reporting of quality measures and how that separate approach to quality improvement can be integrated with P4P programs.

Financial and Quality Impacts of the Medicare Physician Group Practice Demonstration

OBJECTIVE To examine the impact of the Medicare Physician Group Practice (PGP) demonstration on expenditure, utilization, and quality outcomes. DATA SOURCE Secondary data analysis of 2001-2010 Medicare claims for 1,776,387 person years assigned to the ten participating provider organizations and 1,579,080 person years in the corresponding local comparison groups. STUDY DESIGN We used a pre-post comparison group observational design consisting of four pre-demonstration years (1/01-12/04) and five demonstration years (4/05-3/10). We employed a propensity-weighted difference-in-differences regression model to estimate demonstration effects, adjusting for demographics, health status, geographic area, and secular trends. PRINCIPAL FINDINGS The ten demonstration sites combined saved

The Chemistry Laboratory: Development of Average, Fixed, and Variable Costs for Incorporation into a Management Control System

171 (2.0%) per assigned beneficiary person year (p<0.001) during the five-year demonstration period. Medicare paid performance bonuses to the participating PGPs that averaged

Family-based detection for hereditary hemochromatosis.

102 per person year. The net savings to the Medicare program were

Evaluating the performance of medicare fee-for-service providers using the health outcomes survey: a comparison of two methods.

69 (0.8%) per person year. Demonstration savings were achieved primarily from the inpatient setting. The demonstration improved quality of care as measured by six of seven claims-based process quality indicators. CONCLUSIONS The PGP demonstration, which used a payment model similar to the Medicare Accountable Care Organization (ACO) program, resulted in small reductions in Medicare expenditures and inpatient utilization, and improvements in process quality indicators. Judging from this demonstration experience, it is unlikely that Medicare ACOs will initially achieve large savings. Nevertheless, ACOs paid through shared savings may be an important first step toward greater efficiency and quality in the Medicare fee-for-service program.

Medicare Physician Group Practice Demonstration Design: Quality and Efficiency Pay-for-Performance

In order to estimate real cost savings achievable from reductions in laboratory test volume and in order to provide a management tool to help achieve such savings, we developed a management system for our chemistry laboratory. The system estimates the fixed costs (i.e., equipment, direct overhead, and indirect overhead costs), the variable costs (i.e., labor and supplies), and the total costs for each of the 81 tests performed in our hospitals chemistry laboratory. A monthly management report compares predicted changes in total variable costs (based on test volume) to actual variable cost changes. One useful insight from the system is that substantial savings may be realized from reducing low-volume, high-variable cost tests that are not normally the target of test-reducing strategies. The savings per test not ordered was estimated to be

THE MEDICARE PHYSICIAN GROUP PRACTICE DEMONSTRATION: LESSONS LEARNED ON IMPROVING QUALITY AND EFFICIENCY IN HEALTH CARE

5.24 for the low-volume, high-variable cost tests but only

Applying business management models in health care

0.45 for the high-volume, low-variable cost tests, nearly a 12-fold difference. A 10% volume reduction of the former (a reduction of only 6,400 tests annually) would achieve 63% of the savings from a 10% volume reduction of the latter (a reduction of 120,000 tests annually). An effective management reporting system, which tracks actual cost savings, is probably necessary to achieve these savings.

Activating chronic kidney disease patients and family members through the Internet to promote integration of care

The purpose of this study was to examine motivators for and barriers to family-based detection for hereditary hemochromatosis (HH). HH patients (n = 60) and HH siblings (n = 25) participated in one-on-one or group interviews. Patients and siblings understood that HH “runs in families,” but not that siblings are at higher HH risk than other family members. Patient motivators included concern for siblings’ health, seriousness of untreated HH, and doctor’s encouragement to tell siblings that they need to seek diagnostic testing. Siblings were motivated by the seriousness of HH. Barriers included lack of symptoms, belief that HH was rare, and assumption that their doctor would have mentioned the risk of HH. Family-based detection continues to be a feasible part of an overall public health strategy to promote early detection of HH. Greater awareness of HH and its potential consequences, especially among high-risk groups, provides an additional potential avenue for public health action.

Radiology work-load measurements reflecting variables specific to hospital, patient, and examination: results of a collaborative study.

Background:Health status measures are now being used for evaluating the performance of health care organizations. Trends in SF-36 component scores have previously been examined for Medicare-managed care plans but not for providers serving Medicare fee-for-service (FFS) beneficiaries. We compared 2 methods for evaluating the performance of Medicare FFS providers, the Research Triangle Institute (RTI) and Health Assessment Laboratory (HAL) methods. Methods:Data were collected from 6547 Medicare FFS beneficiaries in 10 cohorts. SF-36 Physical Health (PCS) and Mental Health (MCS) component scores were computed at baseline and after a 2-year follow-up. The RTI approach predicts follow-up scores based on a standard care regression model. The HAL approach determines the percentage of beneficiaries whose status is the “same or better” at follow-up. Both approaches then compare observed to expected scores for each cohort. Results:The HAL method did not detect any statistically significant differences for the PCS; the RTI method detected a small PCS difference for one cohort. The HAL method identified 4 cohorts that had significantly higher MCS scores; the RTI approach identified one cohort with significantly lower scores. Conclusions:The 2 approaches provided consistent assessments of provider performance for the PCS but not for the MCS. The differences in the MCS results may have been affected by differing treatment of deaths during follow-up. The HAL approach disregards deaths for the MCS, whereas the RTI method imputes values for death. Implications of using self-reported health status for monitoring provider performance are discussed.