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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
From the Editorial Board: Anne K. Gauthier, MS
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.
Mortality. Mortality is a common outcome indicator used in both clinical practice and clinical trials, and it may be reported in different ways (eg, patient mortality over a specific period, overall survival, progression-free survival, by the setting of a patient’s death). Additionally, the setting of death (in a hospital vs at home or in a hospice) may play an important role in patients’ quality of life18,24 and is sometimes used as part of mortality-related quality measures.

PROs. Ranging from pain to social function evaluation, PROs are increasingly used to evaluate appropriateness of care given their ability to reflect patient needs and preferences, which may vary significantly. The FDA issued a PRO-specific guidance in 2009,25 defining PROs as “any report of the status of a patient’s health condition that comes directly from the patient, without interpretation of the patient’s response by a clinician or anyone else,” and stating that in general, “findings measured by a well-defined and reliable PRO instrument in appropriately designed investigations can be used to support a claim in medical product labeling if the claim is consistent with the instrument’s documented measurement capability.”25

PROs are relevant in both early and late disease stages, complementing other measures that address outcomes in a hospital setting. In 2016, a multistakeholder roundtable on improving oncology measurement recommended that PROs be collected “before, during, and after treatment.”26 Although more evidence is needed, PROMs have been studied for use during an initial consultation and during shared decision making regarding patient care, aside from tracking treatment progress and patient satisfaction.27 A 2013 report on PROs by the National Quality Forum indicates that several guiding principles for selecting PROMs should be followed: psychometric soundness, person-centricity, meaningfulness, amenability to change, and implementability.28 Progress in drawing on electronic PROs may catalyze the ability of plans to systematically and reliably collect patient- and caregiver-reported outcomes, especially if they impose minimal burden on staff and patients.29

Nonetheless, the use of PROs has been associated with multiple challenges, including representativeness, inclusion of PROs in medication labels, necessity for both standardized and customizable PROs, and operational and organizational barriers to collecting and analyzing them.30 In addition, PRO collection is often resource-intensive, the validity of disease-specific PROs may be limited, and many PROs lack predictive value.30 Despite these challenges, PROs can be useful tools to obtain insight into patient needs and preferences in order to make better patient-level, as well as policy, decisions and to support further research and development.

AEs. Quality measures based on reporting of AEs aim to lower the number of avoidable incidents, potentially shortening hospitalization length and reducing costs as well as mortality. Initial guidance on the reporting of AEs in oncology trials was published by the Consolidated Standards of Reporting Trials in 2003, and AEs related to oncology care are now understood better.31 However, AEs in clinical settings are thought to be significantly underreported, partly driven by voluntary reporting and the use of instruments that may be prone to lower sensitivity.32 Improvements in documentation and electronic reporting are expected to improve the reliability of data about AEs observed in clinical practice (most hospitals do not use electronic health records [EHRs] to “directly measure [or record] patient harm”).33

If implemented broadly, the magnitude of potential improvements may be significant: Studies have shown that AEs can extend the length of hospitalizations, increase costs of care, and increase mortality up to 2-fold.34


Evidence From Early Quality Initiatives in Oncology

Although no comprehensive evaluation of OCM has taken place, limited evidence suggests that previous quality initiatives with outcome-based components have improved care while reducing costs. For instance, during a 2-year pilot in Texas involving 221 oncology patients (Innovent Oncology program by McKesson Specialty Health, Texas Oncology, and Aetna), savings of more than $500,000 were achieved.35,36 The program has also been shown to improve adherence to clinical pathways and clinical outcomes: Pathway adherence has increased from 63% to 76%; reductions in ED visits, hospital admissions, and hospital days of 48%, 34%, and 44%, respectively, were observed; and average inpatient days decreased from 2.1 to 1.2 days.32,33 Innovent Oncology based its value-based reimbursement on 3 pillars: (1) Level I Pathways Program (aiming to increase the use of evidence-based treatment guidelines), (2) clinical benchmarking (based on a number of quality indicators), and (3) contract negotiation services.37 Among the quality measures included have been gastrointestinal toxicities, infection, thromboembolic events, pain, and depression.23

Similarly, an oncology pilot by UnitedHealthcare that drew on episode payments for more than 800 patients with breast, colon, and lung cancer in 5 oncology practices achieved net savings of more than $33 million (a 34% reduction of the predicted total medical cost).38 Some of the key quality measures used by this pilot included ED and hospitalization rates, admissions for cancer symptoms, febrile neutropenia occurrence rate, admissions for treatment-related symptoms, days from last chemotherapy to death, and hospice days for patients who died.38

However, a lack of a counterfactual (via a matched control group, for example) undermines a direct causal link between quality measurement and observed outcomes in these pilots, and more comprehensive evaluations are still needed.

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