Real-time Feedback in Pay-for-Performance: Does More Information Lead to Improvement?

BACKGROUND: Pay-for-performance (P4P) has been used expansively to improve quality of care delivered by physicians. However, to what extent P4P works through the provision of information versus financial incentives is poorly understood. OBJECTIVE: To determine whether an increase in information feedback without changes to financial incentives resulted in improved physician performance within an existing P4P program. INTERVENTION/EXPOSURE: Implementation of a new registry enabling real-time feedback to physicians on quality measure performance. DESIGN: Observational, predictive piecewise model at the physician-measure level to examine whether registry introduction associated with performance changes. We used detailed physician quality measure data 3 years prior to registry implementation (2010-2012) and 2 years after implementation (2014-2015). We also linked physician-level data including age, gender, and board certification; group-level data including registry click rates; and patient panel data including chronic conditions. PARTICIPANTS: Four hundred thirty-four physicians continuously affiliated with Advocate from 2010 to 2015. MAIN MEASURES: Physician performance on ten quality metrics. KEY RESULTS: We found no consistent pattern of improvement associated with the availability of real-time information across ten measures. Relative to predicted performance without the registry, average performance increased for two measures (childhood immunization status-rotavirus (p < 0.001) and diabetes care-medical attention for nephropathy (p = 0.024)) and decreased for three measures (childhood immunization status-influenza (p < 0.001) and diabetes care-HbA1c testing (p < 0.001) and poor HbA1c control (p < 0.001)). Results were consistent for subgroup analysis on those most able to improve, i.e., physicians in the bottom tertile of performance prior to registry introduction. Physicians who improved most were in groups that accessed the registry more than those who improved least (8.0 vs 10.0 times per week, p = 0.010). CONCLUSIONS: More frequent provision of information, provided in real-time, was insufficient to improve physician performance in an existing P4P program with high baseline performance. Results suggest that electronic registries may not themselves drive performance improvement. Future work should consider testing information feedback enhancements with financial incentives.

Association Between the Implementation of a Population-Based Primary Care Payment System and Achievement on Quality Measures in Hawaii.

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 < .001). Of 15 prespecified secondary end points for utilization and spending, 11 showed no significant difference. Compared with the non-3PC group, the 3PC system was associated with a significant reduction in the mean number of primary care visits (3.3 to 3.0 visits vs 3.3 to 3.1 visits; adjusted differential change, -3.9 percentage points [95% CI, -4.6 to -3.2 percentage points]; P < .001), but there was no significant difference in mean total cost of care ($3344 to $4087 vs $2977 to $3564; adjusted differential change, 1.0% [95% CI, -1.3% to 3.4%]; P = .39). Conclusions and Relevance: In its first year, the 3PC population-based primary care payment system in Hawaii was associated with small improvements in quality and a reduction in PCP visits but no significant difference in the total cost of care. Additional research is needed to assess longer-term outcomes as the program is more fully implemented and to determine whether results are generalizable to other health care markets.

Designing a commercial medical bundle for cancer care: Hawaii Medical Service Association's Cancer Episode Model.

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.

Assessing The Effectiveness Of Peer Comparisons As A Way To Improve Health Care Quality.

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.

Changes in Outpatient Imaging Utilization and Spending Under a New Population-Based Primary Care Payment Model.

OBJECTIVE: 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. METHODS: 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. RESULTS: 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). DISCUSSION: 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.

Effect of Financial Bonus Size, Loss Aversion, and Increased Social Pressure on Physician Pay-for-Performance: A Randomized Clinical Trial and Cohort Study.

Importance: Despite limited effectiveness of pay-for-performance (P4P), payers continue to expand P4P nationally. Objective: To test whether increasing bonus size or adding the behavioral economic principles of increased social pressure (ISP) or loss aversion (LA) improves the effectiveness of P4P. Design, Setting, and Participants: Parallel studies conducted from January 1 to December 31, 2016, consisted of a randomized clinical trial with patients cluster-randomized by practice site to an active control group (larger bonus size [LBS] only) or to groups with 1 of 2 behavioral economic interventions added and a cohort study comparing changes in outcomes among patients of physicians receiving an LBS with outcomes in propensity-matched physicians not receiving an LBS. A total of 8118 patients attributed to 66 physicians with 1 of 5 chronic conditions were treated at Advocate HealthCare, an integrated health system in Illinois. Data were analyzed using intention to treat and multiple imputation from February 1, 2017, through May 31, 2018. Interventions: Physician participants received an LBS increased by a mean of $3355 per physician (LBS-only group); prefunded incentives to elicit LA and an LBS; or increasing proportion of a P4P bonus determined by group performance from 30% to 50% (ISP) and an LBS. Main Outcomes and Measures: The proportion of 20 evidence-based quality measures achieved at the patient level. Results: A total of 86 physicians were eligible for the randomized trial. Of these, 32 were excluded because they did not have unique attributed patients. Fifty-four physicians were randomly assigned to 1 of 3 groups, and 33 physicians (54.5% male; mean [SD] age, 57 [10] years) and 3747 patients (63.6% female; mean [SD] age, 64 [18] years) were included in the final analysis. Nine physicians and 864 patients were randomized to the LBS-only group, 13 physicians and 1496 patients to the LBS plus ISP group, and 11 physicians and 1387 patients to the LBS plus LA group. Physician characteristics did not differ significantly by arm, such as mean (SD) physician age ranging from 56 (9) to 59 (9) years, and sex (6 [46.2%] to 6 [66.7%] male). No differences were found between the LBS-only and the intervention groups (adjusted odds ratio [aOR] for LBS plus LA vs LBS-only, 0.86 [95% CI, 0.65-1.15; P = .31]; aOR for LBS plus ISP vs LBS-only, 0.95 [95% CI, 0.64-1.42; P = .81]; and aOR for LBS plus ISP vs LBS plus LA, 1.10 [95% CI, 0.75-1.61; P = .62]). Increased bonus size was associated with a greater increase in evidence-based care relative to the comparison group (risk-standardized absolute difference-in-differences, 3.2 percentage points; 95% CI, 1.9-4.5 percentage points; P < .001). Conclusions and Relevance: Increased bonus size was associated with significantly improved quality of care relative to a comparison group. Adding ISP and opportunities for LA did not improve quality. Trial Registration: ClinicalTrials.gov Identifier: NCT02634879.

Redesigning provider payment: Opportunities and challenges from the Hawaii experience.

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.

Effect of Electronic Reminders, Financial Incentives, and Social Support on Outcomes After Myocardial Infarction: The HeartStrong Randomized Clinical Trial.

Importance: Adherence to medications prescribed after acute myocardial infarction (AMI) is low. Wireless technology and behavioral economic approaches have shown promise in improving health behaviors. Objective: To determine whether a system of medication reminders using financial incentives and social support delays subsequent vascular events in patients following AMI compared with usual care. Design, Setting, and Participants: Two-arm, randomized clinical trial with a 12-month intervention conducted from 2013 through 2016. Investigators were blinded to study group, but participants were not. Design was a health plan-intermediated intervention for members of several health plans. We recruited 1509 participants from 7179 contacted AMI survivors (insured with 5 large US insurers nationally or with Medicare fee-for-service at the University of Pennsylvania Health System). Patients aged 18 to 80 years were eligible if currently prescribed at least 2 of 4 study medications (statin, aspirin, ß-blocker, antiplatelet agent), and were hospital inpatients for 1 to 180 days and discharged home with a principal diagnosis of AMI. Interventions: Patients were randomized 2:1 to an intervention using electronic pill bottles combined with lottery incentives and social support for medication adherence (1003 patients), or to usual care (506 patients). Main Outcomes and Measures: Primary outcome was time to first vascular rehospitalization or death. Secondary outcomes were time to first all-cause rehospitalization, total number of repeated hospitalizations, medication adherence, and total medical costs. Results: A total of 35.5% of participants were female (n = 536); mean (SD) age was 61.0 (10.3) years. There were no statistically significant differences between study arms in time to first rehospitalization for a vascular event or death (hazard ratio, 1.04; 95% CI, 0.71 to 1.52; P = .84), time to first all-cause rehospitalization (hazard ratio, 0.89; 95% CI, 0.73 to 1.09; P = .27), or total number of repeated hospitalizations (hazard ratio, 0.94; 95% CI, 0.60 to 1.48; P = .79). Mean (SD) medication adherence did not differ between control (0.42 [0.39]) and intervention (0.46 [0.39]) (difference, 0.04; 95% CI, -0.01 to 0.09; P = .10). Mean (SD) medical costs in 12 months following enrollment did not differ between control ($29 811 [$74 850]) and intervention ($24 038 [$66 915]) (difference, -$5773; 95% CI, -$13 682 to $2137; P = .15). Conclusions and Relevance: A compound intervention integrating wireless pill bottles, lottery-based incentives, and social support did not significantly improve medication adherence or vascular readmission outcomes for AMI survivors. Trial Registration: clinicaltrials.gov Identifier: NCT01800201.