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Policy makers are increasingly using performance feedback that compares physicians to their peers as part of payment policy reforms. However, it is not known whether peer comparisons can improve br...

To evaluate whether the implementation of a new population-based primary care payment system, Population-Based Payments for Primary Care (3PC), initiated by Hawaii Medical Service Association (HMSA; the Blue Cross Blue Shield of Hawaii), was associated with changes in spending and utilization for outpatient imaging in its first year.In this observational study, we used claims data from January 1, 2012, to December 31, 2016. We used a propensity-weighted difference-in-differences design to compare 70,284 HMSA patients in Hawaii attributed to 107 primary care physicians (PCPs) and 4 physician organizations participating in 3PC in its first year of implementation (2016) and 195,902 patients attributed to 312 PCPs and 14 physician organizations that used a fee-for-service model during the study period. The primary outcome was total spending on outpatient imaging tests, and secondary outcomes included spending and utilization by modality.The study included 266,186 HMSA patients (mean age of 43.3 years; 51.7% women) and 419 PCPs (mean age of 54.9 years; 34.8% women). The 3PC system was not significantly associated with changes in total spending for outpatient imaging. Of 12 secondary outcomes, only 3 were statistically significant, including changes in nuclear medicine spending (adjusted differential change = -20.1% [95% confidence interval = -27.5% to -12.1%]; P.001) and utilization (adjusted differential change = -18.1% [95% confidence interval = -23.8 to -11.9%]; P.001).The HMSA 3PC system was not associated with significant changes in total spending for outpatient imaging, though spending and utilization on nuclear medicine tests decreased.

Policy makers are increasingly using performance feedback that compares physicians to their peers as part of payment policy reforms. However, it is not known whether peer comparisons can improve broad outcomes, beyond changing specific individual behaviors such as reducing inappropriate prescribing of antibiotics. We conducted a cluster-randomized controlled trial with Blue Cross Blue Shield of Hawaii to examine the impact of providing peer comparisons feedback on the quality of care to primary care providers in the setting of a shift from fee-for-service to population-based payment. Over 74,000 patients and eighty-eight primary care providers across sixty-three sites were included over a period of nine months in 2016. Patients in the peer comparisons intervention group experienced a 3.1-percentage-point increase in quality scores compared to the control group-whose members received individual feedback only. This result underscores the effectiveness of peer comparisons as a way to improve health care quality, and it supports Medicare's decisions to provide comparative feedback as part of recently implemented primary care and specialty payment reform programs.

Background Cardiac interventions account for a significant share of overall healthcare spending and have been the focus of several large-scale interventions to develop effective bundled payments. To date, however, none have proven successful in commercially insured populations. In 2018, we worked with Hawaii Medical Service Association (HMSA), the Blue Cross Blue Shield of Hawaii, to design a novel commercial bundled payment for percutaneous coronary interventions, the Percutaneous Coronary Intervention Episode Payment Model (PCI EPM). Methods Descriptive analysis of HMSA's PCI EPM, including its inclusion criteria , contents of the bundle, target prices, shared savings model, and incentivized quality metrics. We also compare HMSA's PCI EPM to Medicare's Bundled Payment for Care Improvement programs and the cancelled Cardiac Care Model. Results HMSA's PCI EPM was designed through an iterative process with cardiologists and is the first commercial bundle to specifically target a cardiac procedure. PCI EPM incorporates site neutrality and incentivizes providers to shift care to the outpatient setting when medically permissible. Compared to existing non-commercial models, PCI EPM incorporate first-dollar shared savings and incentivized fewer quality metrics. Conclusions Reviewing features of the Percutaneous Coronary Intervention Episode Payment Model in comparison to existing Medicare programs is intended to help guide health plan and health policymakers when designing programs and policies related to cardiac interventions. Implications Bundled commercial payments for interventional cardiology procedures are promising and should continue to be further explored. Level of evidence VI.

Background Oncology care is expensive and exhibits substantial variation in cost and quality across clinicians and patients. Unlike many conditions with established bundled payment programs, cancer care includes a mix of inpatient and outpatient care that precludes hospital-based designs. In 2018, we worked with Hawaii Medical Service Association (HMSA), the Blue Cross Blue Shield of Hawaii, to design a novel commercial bundle for cancer care, the Cancer Episode Model. Methods Descriptive analysis of HMSA's Cancer Episode Model, including its inclusion criteria, episode definitions, suite of enhanced services, shared savings model, and incentivized quality metrics. We also compare HMSA's Cancer Episode Model to Medicare's Oncology Care Model and three major commercial oncologic alternative payment models offered by Anthem, UnitedHealthcare, and Aetna. Results HMSA's Cancer Episode Model builds upon the successes and limitations of Medicare's Oncology Care Model and existing commercial alternative payment models. Compared to Medicare's Oncology Care Model, HMSA's Cancer Episode Model has stricter inclusion criteria, fewer incentivized quality metrics, a higher proportion of regional pricing, a different risk-adjustment model, and first-dollar shared savings. Compared to the majority of existing commercial models, HMSA's Cancer Episode Model includes total cost of care and a different risk-adjustment model. Conclusions Reviewing features of the Cancer Episode Model in comparison to other programs is intended to provide guidance to health plans and health policymakers in the design of programs and policies aimed at improving cancer care value. Level of evidence Level IV.

Objectives To describe the process of developing a new physician payment system based on value and transitioning away from a fee-for-service payment system Study design Descriptive. This paper describes a recent initiative involving redesign of primary care provider payment in the State of Hawaii. While there has been extensive discussion about switching payment from volume to value in recent years, much of this change has happened at the organizational level and this initiative focused on changing the incentives for individual providers. Methods Descriptive paper. In this paper we discuss the approach taken to shift incentives from fee-for-service towards value using behavioral economics as a conceptual framework for program design. We summarize the new payment system, challenges in its design, and our approach to piloting of different behavioral economic strategies to improve performance. Results None. Conclusions This paper will provide useful guidance to health plans or health delivery systems considering shifting primary care payment away from fee-for-service towards value highlighting some of the design challenges and necessary compromises in implementing such a system at scale.

IMPORTANCE: Hawaii Medical Service Association (HMSA), the Blue Cross Blue Shield of Hawaii, introduced Population-based Payments for Primary Care (3PC), a new capitation-based primary care payment system, in 2016. The effect of this system on quality measures has not been evaluated. OBJECTIVE: To evaluate whether the 3PC system was associated with changes in quality, utilization, or spending in its first year. DESIGN, SETTING, AND PARTICIPANTS: Observational study using HMSA claims and clinical registry data from January 1, 2012, to December 31, 2016, and a propensity-weighted difference-in-differences method to compare 77 225 HMSA members in Hawaii attributed to 107 primary care physicians (PCPs) and 4 physician organizations participating in the first wave of the 3PC and 222 233 members attributed to 312 PCPs and 14 physician organizations that continued in a fee-for-service model in 2016 but had 3PC start dates thereafter. EXPOSURES: Participation in the 3PC system. MAIN OUTCOMES AND MEASURES: The primary outcome was the change in a composite measure score reflecting the probability that a member achieved an eligible measure out of 13 pooled Healthcare Effectiveness Data and Information Set quality measures. Primary care visits and total cost of care were among 15 secondary outcomes. RESULTS: In total, the study included 299 458 HMSA members (mean age, 42.1 years; 51.5% women) and 419 primary care physicians (mean age, 54.9 years; 34.8% women). The risk-standardized composite measure scores for 2012 to 2016 changed from 75.1% to 86.6% (+11.5 percentage points) in the 3PC group and 74.3% to 83.5% (+9.2 percentage points) in the non-3PC group (differential change, 2.3 percentage points [95% CI, 2.1 to 2.6 percentage points]; P

Two Sounding Board articles, by Emanuel et al. and Antos et al., discuss different approaches to controlling rising health care costs in the United States. The editors hope that the range of options presented will stimulate discussion and debate on the best ways to bend the health care cost curve.

The United States spends nearly $8000 per person on health care annually. Even for a wealthy country, this amount is substantially more than would be expected and 2.5 times the average spent by other Organization for Economic Cooperation and Development (OECD) countries. The growth rate of health care spending in the United States has also far outpaced that in all other high-income OECD countries since 1970, even accounting for population growth. This increase in health spending threatens to squeeze out critical investments in education and infrastructure. To successfully develop and implement policies that effectively address both the level and growth of U.S. health care costs, it is critical to first understand cost drivers. Many health policy and economics scholars have contributed to an ongoing debate on whether to blame high prices or high utilization of services for escalating health care spending in the United States. This paper argues that price and volume both contribute to high and increasing health care costs, along with high administrative costs, supply issues, and the fee-for-service payment system. Initial strategies to contain costs might include implementation and expansion of bundled payment systems and competitive bidding.