JANUARY 23, 2020

Welcome to the Pay for Performance Update eNewsletter
Editor: Philip L. Ronning
This issue is sponsored by the National ACO Summit, the National Bundled Payment Summit,
the National Medical Home Summit, National MACRA MIPS/APM Summit,
and the National Medicare Advantage Summit

Stop Penalizing Physicians with Pay-for-Performance
Throughout my career, I've contemplated what it means to be a good doctor. While I still cannot fully articulate it, I know a good doctor when I see one. She's the masterful diagnostician who can solve any medical mystery. He's the physician-scientist who spends countless hours on finding a cure for HIV. She's the colleague on my right, arguing on the phone with a patient's insurance company to get a life-saving medication approved. He's the colleague on my left who is running 45 minutes behind in clinic because he took extra time with a patient who was recently diagnosed with a terminal illness. Recently, there has been a push by health systems to define what it means to be a good doctor by measuring physicians' performance, value, and worth by "incentive quality metrics." These metrics are, in turn, tied to compensation. For example, each clinic within our health system chooses three metrics per year that physicians must meet; if they don't meet the metrics, they do not receive 20% of their salary. Despite being called "incentives," these are actually penalties that distract from improving patient care and promote physician burnout. There is little evidence that a pay-for-performance model, in which physicians are financially penalized, is effective. (KevinMD, January 10, 2020)

Effect of Financial Bonus Size, Loss Aversion, and Increased Social Pressure on Physician Pay-for-Performance


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.

(JAMA Network, February 8, 2019)

Examining Misaligned Incentives for Payers and Manufacturers in Value-Based Pharmaceutical Contracts


Value-based pharmaceutical contracts (VBPCs) are performance-based reimbursement agreements between health care payers and pharmaceutical manufacturers in which the price, quantity, or nature of reimbursement is tied to value-based outcomes. As value-based payment models have permeated through much of the health care payment landscape via reimbursement to payers and providers, VBPCs offer opportunities for manufacturers to similarly engage in performance-based models. This article compares 2 VBPC schemes: "pay-for-failure" schemes, in which manufacturers offer rebates or discounts to payers for treatment failure, and "pay-for-success" schemes, in which manufacturers offer rebates or discounts to payers for treatment success. Each method has its own short-term and long-term trade-offs, and both lead to some degree of misaligned incentives between payers and manufacturers. These incentive differences have important downstream effects, influencing patient selection, provision of wraparound services, and nature of reimbursements. This analysis contrasts potential benefits and disadvantages for each of these approaches and offers potential solutions to address misalignment. For example, although pay-for-success models may be more aligned between payers and manufacturers, pay-for-failure contracts can be innovative and effective in controlling costs and/or improving outcomes. To illustrate, VBPCs aimed to reduce costs could incorporate total cost of care reduction as a value-based outcome. The authors encourage payers and manufacturers to consider a blended alternative where pay-for-failure and pay-for-success outcomes could be incorporated as VBPC outcomes. Since little is known about the effect of each scheme on outcomes, further research on VBPCs is necessary to fully understand how differing incentives ultimately affect clinical outcomes and costs. DISCLOSURES: No outside funding supported the writing of this article. Good and Kelly are employed by the UPMC Centers for Value-Based Pharmacy Initiatives and High-Value Health Care, and Parekh was employed by the UPMC Centers for Value-Based Pharmacy Initiatives and High-Value Health Care at the time of this study. The authors have no other disclosures to report.

(Journal of Managed Care & Specialty Pharmacy, January 2020)

Value-Based Health Care Services Market Report - Key Players, Industry Overview and Forecasts to 2027
Value-based health care is a model, wherein providers such as hospitals are paid based on patient's health outcome, quality, efficiency, cost, and patient experience. Intense competition among providers and increase in pressure to lower cost and improve care have led to a shift from volume-based health care to value-based health care. Value-based health care benefits patients, providers, payers, suppliers, and society. It focuses on helping patients toward quick recovery and avoid chronic diseases to achieve better health at lower costs. Providers achieve high patient satisfaction with better care efficiencies. Payers achieve cost control and reduced risk by spreading it among large number of patients. Value-based health care helps to reduce overall health care spending for society. Commonly used value-based health care models are pay for performance, accountable care organization, bundled payments, and patient-centered medical home. (SB Wire, January 14, 2020)

Axes of a Revolution: Challenges and Promises of Big Data in Healthcare


Health data are increasingly being generated at a massive scale, at various levels of phenotyping and from different types of resources. Concurrent with recent technological advances in both data-generation infrastructure and data-analysis methodologies, there have been many claims that these events will revolutionize healthcare, but such claims are still a matter of debate. Addressing the potential and challenges of big data in healthcare requires an understanding of the characteristics of the data. Here we characterize various properties of medical data, which we refer to as ‘axes' of data, describe the considerations and tradeoffs taken when such data are generated, and the types of analyses that may achieve the tasks at hand. We then broadly describe the potential and challenges of using big data in healthcare resources, aiming to contribute to the ongoing discussion of the potential of big data resources to advance the understanding of health and disease.

(NatureHealth, January 13, 2020)

Health Workers Slam Bengoa's Performance-Related Pay Proposal for Northern Ireland NHS
Professor Rafael Bengoa, who authored a report in October 2016 which called for widespread reform of the NHS in Northern Ireland, has said nurses and doctors should be financially rewarded if they produce better outcomes than their colleagues. Mr. Bengoa made the controversial comments to the BBC's Nolan Show the week after thousands of nurses took to picket lines to protest over pay and staffing levels, which unions claim are unsafe. He said: "One needs to be thinking of a much more flexible system, this is not a privatisation, it is trying to make the public system much more flexible. We are all trying to do that with our different health services across Europe. "The important thing is that one can identify how to measure different teams doing different work according to the results they are getting. You can measure results. "I think the unions have to be thinking about this type of alternative and not try to standardise everyone on everything." (Belfast Telegraph, December 23, 2019)

How Do Value-Based Programs Work with Other CMSS Quality Efforts?

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CMMI's New Mandatory Downside-Risk Payment Models Presented by ECG

Ken Steele, MHA
Principal, ECG Management Consultants, Former Vice President Managed Care, Catholic Healthcare West (now Dignity Health), Former President, St. Mary's Medical Center, San Francisco, CA