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The American Journal of Managed Care December 2019
Clinical Characteristics and Treatment Patterns Among US Patients With HIV
Julie L. Priest, MSPH; Tanya Burton, PhD; Cori Blauer-Peterson, MPH; Kate Andrade, MPH; and Alan Oglesby, MPH
Partnering in Postacute Darkness? CMS Has Data That Will Help
Terry E. Hill, MD
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Anne K. Gauthier, MS
Preventive/Office Visit Patient Knowledge and Their Insurance Information Gathering Perceptions
Evan K. Perrault, PhD; Katie J. Schmitz, BA; Grace M. Hildenbrand, MA; and Seth P. McCullock, MA
Cost-Sharing Payments for Out-of-Network Care in Commercially Insured Adults
Wendy Yi Xu, PhD; Bryan E. Dowd, PhD; Macarius M. Donneyong, PhD; Yiting Li, PhD; and Sheldon M. Retchin, MD, MSPH
Benzodiazepine and Unhealthy Alcohol Use Among Adult Outpatients
Matthew E. Hirschtritt, MD, MPH; Vanessa A. Palzes, MPH; Andrea H. Kline-Simon, MS; Kurt Kroenke, MD; Cynthia I. Campbell, PhD, MPH; and Stacy A. Sterling, DrPH, MSW
Catheter Management After Benign Transurethral Prostate Surgery: RAND/UCLA Appropriateness Criteria
Ted A. Skolarus, MD, MPH; Casey A. Dauw, MD; Karen E. Fowler, MPH; Jason D. Mann, MSA; Steven J. Bernstein, MD, MPH; and Jennifer Meddings, MD, MS
A Claims-Based Algorithm to Reduce Relapse and Cost in Schizophrenia
Heidi C. Waters, PhD, MBA; Charles Ruetsch, PhD; and Joseph Tkacz, MS
Cost Burden of Hepatitis C Virus Treatment in Commercially Insured Patients
Christine Y. Lu, PhD; Dennis Ross-Degnan, ScD; Fang Zhang, PhD; Robert LeCates, MA; Caitlin Lupton, MSc; Michael Sherman, MD; and Anita Wagner, PharmD
Delivery System Performance as Financial Risk Varies
Joseph P. Newhouse, PhD; Mary Price, MA; John Hsu, MD, MBA; Bruce Landon, MD, MBA; and J. Michael McWilliams, MD, PhD
Association of Care Management Intensity With Healthcare Utilization in an All-Condition Care Management Program
Hussain S. Lalani, MD; Patti L. Ephraim, MPH; Arielle Apfel, MPH; Hsin-Chieh Yeh, PhD; Nowella Durkin; Lindsay Andon, MSPH; Linda Dunbar, PhD; Lawrence J. Appel, MD; and Felicia Hill-Briggs, PhD; for the Johns Hopkins Community Health Partnership
Currently Reading
Outcome Measures for Oncology Alternative Payment Models: Practical Considerations and Recommendations
Jakub P. Hlávka, PhD; Pei-Jung Lin, PhD; and Peter J. Neumann, ScD

Outcome Measures for Oncology Alternative Payment Models: Practical Considerations and Recommendations

Jakub P. Hlávka, PhD; Pei-Jung Lin, PhD; and Peter J. Neumann, ScD
This review presents a set of evidence-based outcome measures for oncology alternative payment models, drawing on evidence from existing and proposed quality measures.

Objectives: This paper aims to synthesize existing scholarship on quality measures in oncology, with a specific focus on outcome-based quality measures, which are often underutilized. We also present a set of “core outcome measures” that may be considered in future oncology alternative payment models (APMs).

Study Design: Our research consists of a focused literature review, content analysis, and quality measure synthesis and categorization.

Methods: We conducted a focused literature review to generate key evidence on quality measures in oncology. We studied 7 oncology quality assessment frameworks, encompassing 142 quality metrics, and synthesized recommendations using the Center for Medicare and Medicaid Innovation APM toolkit, focusing on outcome measures.

Results: We present 34 outcome-based oncology quality measures for consideration, which are classified into 5 domains: clinical care (eg, hospital and emergency department visits, treatment effectiveness, mortality), safety (eg, infections, hospital adverse events), care coordination (for hospital and hospice care), patient and caregiver experience, and population health and prevention. Both general and indication-specific outcome measures should be considered in oncology APMs, as appropriate. Utilizing outcome-based measures will require addressing multiple challenges, ranging from risk adjustment to data quality assurance.

Conclusions: Oncology care will benefit from a more rigorous approach to quality assessment. The success of oncology APMs will require a robust set of quality measures that are relevant to patients, providers, and payers.

Am J Manag Care. 2019;25(12):e403-e409
Takeaway Points

Evidence is scarce on what outcome measures are most suitable and feasible for future oncology payment models. This paper reviews 7 oncology quality assessment frameworks and existing literature on quality measurement in oncology and recommends that:
  • Outcome quality measures in future oncology payment models should include domains for clinical care, safety, care coordination, patient and caregiver experience, and population health and prevention.
  • Future oncology payment models should draw on the core outcome set but should be tailored to unique care delivery needs and context.
  • The inclusion of diverse outcome measures in oncology may help improve care delivery to all patients with cancer.
Several alternative payment models (APMs) are being piloted to address affordability, equity, and quality-of-care challenges in oncology care. Of these arrangements, the Oncology Care Model (OCM), developed by the Center for Medicare and Medicaid Innovation (CMMI), is among the most extensive, covering about 200,000 chemotherapy episodes annually. The OCM relies on multiple quality measures to determine the level of payment for each provider, with the goal of incentivizing higher-quality care in a cost-effective manner. The OCM’s payment design is described in eAppendix A (available at

Despite innovations in the payment landscape, limited consensus exists about what constitutes indispensable quality measures in oncology. The absence of such consensus may not only limit the development of better payment models, which increasingly link payment to quality of care, but also result in a lack of agreement on how value should be defined (and demonstrated) in an era of innovative, ever more expensive cancer therapies. In 2016, a roundtable of national experts in cancer care and oncology measurement recommended that policy makers “prioritize and develop effective cross-cutting measures that assess clinical and patient-reported outcomes, including shared decision making, care planning, and symptom control” and highlighted an “overreliance on condition-specific process measures.”1 Disease-specific quality measures have been developed, but there is a lack of consensus on what quality measures ought to be utilized across multiple cancers, especially when measuring clinical outcomes.2 As oncology APMs evolve, there are practical considerations in the design and implementation of outcome-based measures.

The development of new quality measures for oncology has been underway for many years. For example, CMS together with America’s Health Insurance Plans (AHIP) and others developed Core Quality Measures in 8 therapeutic areas, including medical oncology, to assess provider performance.3 This initiative included quality indicators focusing on breast cancer, colorectal cancer, prostate cancer, and, more generally, end-of-life care.4 It also identified areas for future measure development in oncology (eg, pain control, hospital admission, 5-year cure rates) and highlighted challenges related to data access and measurement as the standard of cancer care progresses, requiring frequent reassessments.4 In parallel, the American Society for Radiation Oncology has been working with the American Society of Clinical Oncology (ASCO) to develop measures “for utilization by both organizations in various quality programs and reporting environments.”5 However, no comprehensive set of core outcome-based quality measures in oncology has been published.

Research on healthcare quality measures typically differentiates between 2 key categories: process-based measures, which focus on proper reporting and procedure execution, and outcome-based measures, which involve clinical outcomes and patient-reported experience of care. This paper aims to synthesize existing scholarship on quality measures in oncology, with a specific focus on outcome-based quality measures, which are underutilized given their perceived benefits. We also present a set of “core outcome measures” that may be considered in future oncology APMs. Our study does not aim to provide a definitive list but, rather, to present a diverse set of outcome measures most commonly included in quality initiatives and payment models in oncology.


Our research consists of a focused literature review, content analysis, and measure categorization, similar to Macefield et al.6 First, our focused literature review summarizes key evidence related to quality measures in oncology, with an emphasis on classification, their unique advantages and disadvantages, and the challenges related to implementation in clinical practice. Second, our descriptive analysis of the most commonly used quality measures in oncology draws on a convenience sample of existing payment models and other quality assessment frameworks. Our sample includes 7 oncology quality assessment programs, frameworks, and payment models (also referenced as “oncology quality assessment frameworks”), which encompass 142 quality measures: the OCM by CMMI, the Quality Oncology Practice Initiative by ASCO, the Prospective Payment System–Exempt Cancer Hospital Quality Reporting Program by CMS, the Core Quality Measures Collaborative Core Sets by CMS and AHIP, the Oncology Medical Home program by the Community Oncology Alliance, the Osteoporosis Quality Improvement Registry by the National Osteoporosis Foundation and National Bone Health Alliance, and the Oncology Qualified Clinical Data Registry by the Oncology Nursing Society.

In this paper, we categorize these measures into process- versus outcome-based and analyze their frequency. Given our primary focus on outcome-based quality measures, we decided to expand our literature review to include the evidence base for each of the key outcome measure categories identified. These sources were identified by snowballing from quality measure summaries by CMS and reviewing other relevant literature. In addition, we review and summarize published reports on the impact of emerging oncology APMs on clinical outcomes and spending. We conclude with a synthesis of existing evidence on key outcome-based measures and their appropriateness in future oncology APMs. Finally, we discuss directions for customization and further validation of oncology core outcome measures.

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