Value in Cancer Care: An Economist's Perspective

CMS and commercial insurers are increasingly paying for medical care through alternative payment models (APMs) that reward “value”.^1-3 These APMs include accountable care organizations, bundled payments, “pathway” programs with physician risk and reward, and advanced medical homes, as well as tying fee-for-service (FFS) payments to quality metrics.

Outpatient cancer care is an important target for these efforts: the 2015 Medicare Access and CHIP Reauthorization Act of 2015 legislation made the move to APMs in outpatient oncology care inevitable, tying FFS Medicare payments to the reporting and achievement of specific quality targets. In 2015, the Center for Medicare & Medicaid Innovation (CMMI) announced its oncology care model (OCM)^.4 The OCM incorporates bundled payment with a shared savings program based on spending for all care provided to cancer patients upon the initiation of chemotherapy, including chemotherapy and supportive care drugs, day surgeries, diagnostic tests, emergency department visits, and inpatient stays. In March 2016, CMMI announced its intention to pilot additional APMs in outpatient oncology. The interventions include reducing physician reimbursement for the use of expensive chemotherapy and providing tools for physicians to assess cancer drug selection based on measures of safety, efficacy, effectiveness, and price.⁵

Adoption of value-based outpatient oncology reimbursement by CMS is appealing. Under these reforms, services that used to generate revenue for physicians become costs they need to manage. In the more structured bundled or medical home models, payers reimburse defined payments for the care of each patient for a set period of time (an “episode”) and physicians have the freedom to treat patients as they choose. The payers benefit by moving away from existing policies that reward physicians for doing and billing more. In essence, APMs act to transfer some risks associated with high levels of cancer care spending from insurers to physicians or physician based organizations.

Yet, these policies also raise some challenges. In this perspective, I briefly review 2 vexing concerns with value-based outpatient cancer treatment.

Will High Drug Prices Be Tamed by Bundled or Pathway-based Payments?

One driving rationale for APMs in outpatient oncology care is the high and rising spending on prescription drugs used to treat cancer and its symptoms.^6,7 Stakeholders point to the fact that both the ever-growing prices of these drugs and the extent of their overuse likely account for a nontrivial amount of high spending levels and trends.⁸ Are bundled payments that include prescription drugs the answer to taming drug-related spending? The answer lies with whether one believes drug prices are a technical or probability risk to physicians or physician based organizations:

• Probability risk. This is the classic form of risk individuals buy insurance to mitigate. It is characterized by the occurrence of unpredictable events. In this context, probability risk is related to the spending required to treat a patient developing a particular cancer and seeking treatment from a specific physician. These are risks that lie outside a physician’s control.
• Technical risk. This risk is related to the treating physician’s clinical skill and efficient management of the patient’s cancer, including diagnosis and treatment. These risks lie under the physician’s control.

Basic insurance theory suggests APMs are a means by which insurers should seek to transfer the technical risks associated with spending to physicians while retaining the management of probability risks to ensure patient access to care. What components of spending risk can physicians control? Clearly, physicians have some control over how many lines of therapy they use, which regimens they choose, and how creative they get in applying drugs to treat cancers off-label. Consequently, the “use” aspect of drug spending should be considered a technical risk. The promise of APMs is that the use—eliminated by transferring spending risk to physicians—will be “waste” and thus its elimination will not entail any harm to patients.

Identifying which aspects of use are overuse and misuse is difficult, particularly when limited treatment options are available for deadly cancers or in periods of rapid technological innovation and diffusion. One worry is that APMs that transfer substantial risk to physicians to control use may entail significant risks to patients in the form of enticing physicians to skimp on care or shun specific types of patients altogether.⁹ For these reasons, many stakeholders believe the use of pathways for cancers exhibiting these characteristics are preferred APM models at this time.

With respect to drug prices being a technical or probability risk, the story of ziv-aflibercept’s (Zaltrap) US market launch in August 2012 is helpful to keep in mind.¹⁰ Soon after Sanofi Pharmaceuticals Inc launched Zaltrap, physicians from Memorial Sloan-Kettering Cancer Center wrote in a New York Times op-ed piece that they wouldn’t prescribe the drug because its list price ($11,407 per person per month of treatment in 2014) was twice as much as Genentech’s bevacizumab (Avastin), a drug with similar expected outcomes for colorectal cancer patients. In response, Sanofi said they would reduce the price of the drug by 50%.

Will physicians extend this bargaining power to other drugs’ prices under APMs? Yes, perhaps in selected cancers where innovation has created multiple branded and/or generic options that provide equivalent therapeutic benefits for patients. The cancers that have benefited from this type of recent treatment availability include some blood cancers, breast cancer, colorectal cancer, and lung cancer.^11,12 Here the application of bundled payments or medical home will likely empower physicians to seek more substantial discounts and rebates from manufacturers, mitigating price growth.

However, I have some reasons to be cautious about the net effect of this leverage, since spending risks associated with drug prices for truly novel drugs appear to entail probability risk. Despite public outcry,^13-15 manufacturers of novel cancer drugs have not pursued moderating pricing strategies. Indeed, physicians already have some leverage over the acquisition prices of generics and drugs with competitors in a therapeutic class. Their leverage comes from 340B drug discounts limited to the entities that qualify for the program and/or the volume of drug purchasing they are pursuing in a given period of time by their group purchasing organizations.¹⁶ Only some of these discounts are passed onto insurers or to patients under current payment policies. Nothing about the use of APMs will alter these arrangements, keeping such drug revenues locked in the coffers of physician groups, hospitals and other third parties. Furthermore, physicians have control over the prices paid for novel and existing oral drugs covered under cancer patients’ pharmacy benefits. These prices are negotiated by payers or increasingly by pharmacy benefit managers.¹⁷ Therefore, taming the prices of truly novel cancer drugs, particularly oral cancer drugs, will likely require other policy solutions.

How Best to Measure Quality?

The key tool to mitigating patient and physician concerns regarding APM-related stinting challenges and moving us toward innovative pricing policies for prescription drugs to treat cancer (such as risk-sharing agreements between insurers and pharmaceutical manufacturers) are valid, reliable, comparable, and time-sensitive outcomes data. Much-touted efforts are underway by the American Society of Clinical Oncology and US Oncology, among others, to expand metrics for assessing cancer treatment quality delivered in the outpatient setting across many more cancers and also for different outcome measures for comparative purposes. This flurry of activity belies a simple fact: in cancer, there is no settled-upon methodology for measuring outcomes and comparing outcomes between institutions, care settings, or physicians.

Quality measurement in this area is currently stymied for at least 3 reasons:

• First, modeling prognostic outcome correlates requires consensus on treatment for a given cancer patient, inclusive of state and possible line of therapy. However, the pace of technological change in both cancer diagnoses and treatment options hampers this consensus building.
• Second, like other areas of medicine, patient selection and treatment intensity bias outcome measurement. Risk adjustment of these measures as they relate to outpatient cancer care requires an analyst to observe patient cancer stage, line of therapy, and the presence and outcomes of diagnostic tests from claims data. FFS Medicare claims do not currently provide this information, inhibiting progress on risk-adjusted comparative outcome development.
• Finally, the construction of comparative outcome measures presumes identifiable and unique physicians. Yet, the task of defining unique physicians is increasingly problematic, particularly in the delivery of cancer care where merger and acquisition activities between physicians, community oncology groups, hospitals, and other arrangements have substantially increased. There is also a flurry of cancer care center “affiliations” occurring nationwide. These activities can cause a dramatic shift in the patterns of cancer care in a limited time frame, making it hard to assign treatment to a given physician.

Affiliation and consolidation activities among physicians, oncology groups and/or hospitals can also compound selection and treatment biases in the construction of comparative cancer measures. The extent of the potential biases that such activities introduce to these metrics is intimately related to the underlying economic and scientific rationales driving these activities. We can presume that these arrangements provide participants with several advantages, all impacting patient selection into treatment and/or the treatment patients receive, including the syndication of treatment pathways for the care of specific cancers, the creation of closer ties between institutions for patient referrals, access to shared physician time and expertise, improved bargaining power with insurers, and more control over intra-institutional prices.

EBO

I am unaware of any ongoing efforts by CMS to systematically track and characterize these relationships for quality measurement and reimbursement under the existing APM policies. New data collection efforts are likely required to systematically track consolidation and affiliation activity, and its impact on patient flow across settings. This is an important area for future research.

Rena M. Conti, PhD, is assistant professor of health policy and economics at The University of Chicago.

Address for correspondence:

Rena M Conti, PhD

Departments of Pediatrics Hematology/Oncology and Health Studies

The University of Chicago

5841 S Maryland Ave

Chicago, IL 60637

E-mail: rconti@uchicago.edu

Disclosures and Acknowledgements: The author has no relevant or material financial interests that relate to the research described herein.

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