Value-Based Physician Payment in Oncology: Public and Private Insurer Initiatives

Assessing the Validity of the Centers for Medicare & Medicaid Services Measure in Identifying Potentially Preventable Emergency Department Visits by Patients With Cancer

PURPOSE

The Centers for Medicare & Medicaid Services (CMS) implemented chemotherapy measures (OP-35) to reduce potentially preventable emergency department visits (PPEDVs) and hospitalizations. This study evaluated the validity of the OP-35 measure in identifying PPEDVs among patients with cancer.

METHODS

This is a cross-sectional study, which used data from the 2012-2022 National Hospital Ambulatory Medical Care Survey. ED visits are assessed and compared on the basis of three measures: immediacy using Emergency Severity Index (ESI), disposition (discharge v hospitalization), and OP-35 criteria.

RESULTS

Between 2012 and 2022, a weighted sample of 46,723,524 ED visits were made by patients with cancer. Among reported ESI cases, 25.2% (8,346,443) was high urgency. In addition, 30.3% (14,135,496) of ED visits among patients with cancer led to hospitalizations. Using the OP-35 measure, it was found that 20.85% (9,743,977) was PPEDVs. A 21.9% (10,232,102) discrepancy between discharge diagnosis (CMS billing codes) and chief complaints was identified. Further analysis showed that 19.2% (1,872,556) of potentially preventable ED visits (CMS OP-35) were high urgency and 32.6% (3,181,280) resulted in hospitalization.

CONCLUSION

The CMS approach to identifying PPEDVs has limitations. First, it may overcount preventable visits by including high-urgency or hospitalization-requiring cases. Second, relying on final diagnoses for retrospective preventability judgment can be misleading as they may not reflect the initial reason for the visit. In addition, differentiating causes for ED visits in patients with cancer undergoing various treatments is challenging as the approach does not distinguish between chemotherapy-related complications and others. Identification inconsistencies arise because of varying coding practices and chosen preventable conditions, lacking consensus and alignment with specific hospital or patient needs. Finally, the model fails to consider crucial nonclinical factors like social support, economic barriers, and alternative care access, potentially unfairly penalizing hospitals serving underserved populations.

The economics of alternative payment models for pharmaceuticals

Pharmaceuticals are priced uniformly by convention, but vary in their degree of effectiveness for different disease indications. As more high-cost therapies have launched, the demand for alternative payment models (APMs) has been increasing in many advanced markets, despite their well-documented limitations and challenges to implementation. Among policy justifications for such contracts is the maximization of value given scarce resources. We show that while uniform pricing rules can handle variable effectiveness in efficient markets, market inefficiencies of other kinds create a role for different value-based pricing structures. We first present a stylized theoretical model of efficient interaction among drug manufacturers, payers, and beneficiaries. In this stylized setting, uniform pricing works well, even when treatment effects are variable. We then use this framework to define market failures that result in obstacles to uniform pricing. The market failures we identify include: (1) uncertainty of patient distribution, (2) asymmetric beliefs, (3) agency imperfection by payer, (4) agency imperfection by provider, and (5) patient behavior and treatment adherence. We then apply our insights to real-world examples of alternative payment models, and highlight challenges related to contract implementation.

Association Between a National Insurer's Pay-for-Performance Program for Oncology and Changes in Prescribing of Evidence-Based Cancer Drugs and Spending

PURPOSE

Cancer drug prescribing by medical oncologists accounts for the greatest variation in practice and the largest portion of spending on cancer care. We evaluated the association between a national commercial insurer's ongoing pay-for-performance (P4P) program for oncology and changes in the prescribing of evidence-based cancer drugs and spending.

METHODS

We conducted an observational difference-in-differences study using administrative claims data covering 6.7% of US adults. We leveraged the geographically staggered, time-varying rollout of the P4P program to simulate a stepped-wedge study design. We included patients age 18 years or older with breast, colon, or lung cancer who were prescribed cancer drug regimens by 1,867 participating oncologists between 2013 and 2017. The exposure was a time-varying dichotomous variable equal to 1 for patients who were prescribed a cancer drug regimen after the P4P program was offered. The primary outcome was whether a patient's drug regimen was a program-endorsed, evidence-based regimen. We also evaluated spending over a 6-month episode period.

RESULTS

The P4P program was associated with an increase in evidence-based regimen prescribing from 57.1% of patients in the preintervention period to 62.2% in the intervention period, for a difference of +5.1 percentage point (95% CI, 3.0 percentage points to 7.2 percentage points; P < .001). The P4P program was also associated with a differential $3,339 (95% CI, $1,121 to $5,557; P = .003) increase in cancer drug spending and a differential $253 (95% CI, $100 to $406; P = .001) increase in patient out-of-pocket spending, but no significant changes in total health care spending ($2,772; 95% CI, -$181 to $5,725; P = .07) over the 6-month episode period.

CONCLUSION

P4P programs may be effective in increasing evidence-based cancer drug prescribing, but may not yield cost savings.

An Insurer's Program To Incentivize Generic Oncology Drugs Did Not Alter Treatment Patterns Or Spending On Care

The high and rising costs of anticancer drugs have received national attention. The prices of brand-name anticancer drugs often dwarf those of established generic drugs with similar efficacy. In 2007-16 UnitedHealthcare sought to encourage the use of several common low-cost generic anticancer drugs by offering providers a voluntary incentivized fee schedule with substantially higher generic drug payments (and profit margins), thereby increasing financial equivalence for providers in the choice between generic and brand-name drugs and regimens. We evaluated how this voluntary payment intervention affected treatment patterns and health care spending among enrollees with breast, lung, or colorectal cancer. We found that the incentivized fee schedule had neither significant nor meaningful effects on the use of incentivized generic drugs or on spending. Practices that adopted the incentivized fee schedule already had higher rates of generic anticancer drug use before switching, which demonstrates selection bias in take-up. Our study provides cautionary evidence of the limitations of voluntary payment reform initiatives in meaningfully affecting health care practice and spending.

Impact of Pharmacy Benefit Managers on Oncology Practices and Patients

Pharmacy benefit managers (PBMs) are thoroughly integrated into the drug supply chain as administrators of prescription drug benefits for private insurers, self-insuring business, and government health plans. As the role of PBMs has expanded, their opaque business practices and impact on drug prices have come under increasing scrutiny. PBMs are particularly influential in oncology care because prescription drugs play a major role in the treatment of most cancers and an increasing number of patients with cancer are treated with oral oncology agents managed by PBMs. There is concern that some PBM practices may threaten access to high-quality cancer care and may increase the financial and administrative burden on patients and practices. In this article, we review the role of PBMs in prescription drug coverage and reimbursement, discuss the impact of PBMs on oncology care, and present data from the 2018 ASCO Practice Survey assessing the knowledge and attitude of oncology practices toward PBMs.

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.

Minimizing the burden of cancer in the United States: Goals for a high-performing health care system

Between 1991 and 2015, the cancer mortality rate declined dramatically in the United States, reflecting improvements in cancer prevention, screening, treatment, and survivorship care. However, cancer outcomes in the United States vary substantially between populations defined by race/ethnicity, socioeconomic status, health insurance coverage, and geographic area of residence. Many potentially preventable cancer deaths occur in individuals who did not receive effective cancer prevention, screening, treatment, or survivorship care. At the same time, cancer care spending is large and growing, straining national, state, health insurance plans, and family budgets. Indeed, one of the most pressing issues in American medicine is how to ensure that all populations, in every community, derive the benefit from scientific research that has already been completed. Addressing these questions from the perspective of health care delivery is necessary to accelerate the decline in cancer mortality that began in the early 1990s. This article, part of the Cancer Control Blueprint series, describes challenges with the provision of care across the cancer control continuum in the United States. It also identifies goals for a high-performing health system that could reduce disparities and the burden of cancer by promoting the adoption of healthy lifestyles; access to a regular source of primary care; timely access to evidence-based care; patient-centeredness, including effective patient-provider communication; enhanced coordination and communication between providers, including primary care and specialty care providers; and affordability for patients, payers, and society.

Using claims data to attribute patients with breast, lung, or colorectal cancer to prescribing oncologists

Background

Alternative payment models frequently require attribution of patients to individual physicians to assign cost and quality outcomes. Our objective was to examine the performance of three methods for attributing a patient with cancer to the likeliest physician prescriber of anticancer drugs for that patient using administrative claims data.

Methods

We used the HealthCore Integrated Research Environment to identify patients who had claims for anticancer medication along with diagnosis codes for breast, lung, or colorectal lung cancer between July 2013 and September 2017. The index date was the first date with a record for anticancer medication and cancer diagnosis code. Included patients had continuous medical coverage from 6 months before index to at least 7 days after index. Patients who received anticancer drugs during the 6 months prior to index were excluded. The three methods attributed each patient to the physician with whom the patient had the most evaluation and management (E&M) visits within a 90-day window around the index date (Method 1); the most E&M visits with no time window (Method 2); or the E&M visit nearest in time to the index date (Method 3). We assessed the performance of the methods using the percentage of the study cohort successfully attributed to a physician, and the positive predictive value (PPV) relative to available physician-reported data on patient(s) they treat.

Results

In total, 70,641 patients were available for attribution to physicians. Percentages of the study cohort attributed to a physician were: Method 1, 92.6%; Method 2, 96.9%; and Method 3, 96.9%. PPVs for each method were 84.4%, 80.6%, and 75.8%, respectively.

Conclusion

We found that a claims-based algorithm - specifically, a plurality method with a 90-day time window - correctly attributed nearly 85% of patients to a prescribing physician. Claims data can reliably identify prescribing physicians in oncology.

Current and Future Oncology Management in the United States

BACKGROUND

The cost of treating cancer patients is high and rising in the United States. Payers are exposed to cost through doctor visits, laboratory tests, imaging tests, radiation treatment, drugs, hospital stays, surgery, home care, transportation and travel, and caregiving. This study focuses on the cost of medication from the viewpoint of U.S. payers. Although new tools for managing these costs have been gaining attention, prices continue to rise, and challenges to managing costs remain high. Innovative tools are necessary for controlling the cost of care in oncology, but their effectiveness is still unclear.

OBJECTIVES

To (a) gauge payer perceptions of current and future cost management of innovative oncology drugs and (b) predict which management tools will increase in prevalence by 2020-2022.

METHODS

A literature search of cost and management of oncology created the foundation for developing a survey for U.S. payers. The mobile survey was completed on devices such as smart phones or tablets. Payers were asked about general oncology product management, use of specific management tools today, management challenges, and expected use of specific management tools in 2020-2022. Management tools were segmented into traditional (used across many therapeutic categories), oncology-specific (used in oncology but not routinely used in other disease areas), and systemic (not product-specific but that affect the way services are provided and funded). Specific questions for managing the cost of care in non-small cell lung cancer (NSCLC) and chronic lymphocytic leukemia (CLL) were included in the survey. NSCLC and CLL were chosen because of their diverse clinical characteristics and the level of innovation in these disease areas. The survey was fielded from May 31, 2017, to June 15, 2017. Results consisted of simple descriptive statistical analysis weighted by the payer's reported organizational covered lives.

RESULTS

Payers were concerned with the high cost and budget impact of oncology drugs and considered these a high priority for management. However, they continue to use traditional management tools such as manage to FDA label, quantity limits, step edits, and reauthorizations, which are ineffective in controlling cost. More innovative management tools such as pathways of care are available but are not yet widely adopted. Payers hope to better control oncology cost in the future; however, specific questions pertaining to the management of NSCLC and CLL indicate that minimal changes in cost management will occur by 2020-2022.

CONCLUSIONS

Despite an increasing number of innovative cost management tools, challenges remain for managing oncology medication costs. New incentives are being generated, but barriers to their implementation will continue to restrict use through 2020-2022.

DISCLOSURES

No outside funding supported this study. The authors are employed by MKO Global Partners, which is a consulting firm that focuses on payer strategy and market access in the pharmaceutical and biotech markets. Some initial results from this research were published as part of a comparative poster at ISPOR European Conference; November 4-8, 2017; Glasgow, Scotland, UK.

What drives variation in spending for breast cancer patients within geographic regions?

OBJECTIVE

To estimate and describe factors driving variation in spending for breast cancer patients within geographic region.

DATA SOURCE

Surveillance, Epidemiology, and End Results (SEER)-Medicare database from 2009-2013.

STUDY DESIGN

The proportion of variation in monthly medical spending within geographic region attributed to patient and physician factors was estimated using multilevel regression models with individual patient and physician random effects. Using sequential models, we estimated the contribution of differences in patient and disease characteristics or use of cancer treatment modalities to patient-level and physician-level variance in spending. Services associated with high spending physicians were estimated using linear regression.

DATA EXTRACTION METHOD

A total of 20 818 women with a breast cancer diagnosis in 2010-2011.

PRINCIPAL FINDINGS

We observed substantial between-patient and between-provider variation in spending following diagnosis and at the end-of-life. Immediately following diagnosis, 48% of between-patient and 31% of between-physician variation were driven by differences in delivery of cancer treatment modalities to similar patients. At the end-of-life, patients of high spending physicians had twice as many inpatient days, double the chemotherapy spending, and slightly more hospice days.

CONCLUSIONS

Similar patients receive very different treatments, which yield significant differences in spending. Efforts to reduce unwanted variation may need to target treatment choices within patient-doctor discussions.

Transformation of the Health Care Industry: Curb Your Enthusiasm?

Policy Points: Policymakers seek to transform the US health care system along two dimensions simultaneously: alternative payment models and new models of provider organization. This transformation is supposed to transfer risk to providers and make them more accountable for health care costs and quality. The transformation in payment and provider organization is neither happening quickly nor shifting risk to providers. The impact on health care cost and quality is also weak or nonexistent. In the longer run, decision makers should be prepared to accept the limits on transformation and carefully consider whether to advocate solutions not yet supported by evidence.

CONTEXT

There is a widespread belief that the US health care system needs to move "from volume to value." This transformation to value (eg, quality divided by cost) is conceptualized as a two-fold movement: (1) from fee-for-service to alternative payment models; and (2) from solo practice and freestanding hospitals to medical homes, accountable care organizations, large hospital systems, and organized clinics like Kaiser Permanente.

METHODS

We evaluate whether this transformation is happening quickly, shifting risk to providers, lowering costs, and improving quality. We draw on recent evidence on provider payment and organization and their effects on cost and quality.

FINDINGS

Data suggest a low prevalence of provider risk payment models and slow movement toward new payment and organizational models. Evidence suggests the impact of both on cost and quality is weak.

CONCLUSIONS

We need to be patient in expecting system improvements from ongoing changes in provider payment and organization. We also may need to look for improvements in other areas of the economy or to accept and accommodate prospects of modest improvements over time.