scholarly journals Design Challenges of an Episode-Based Payment Model in Oncology: The Centers for Medicare & Medicaid Services Oncology Care Model

2017 ◽  
Vol 13 (7) ◽  
pp. e632-e645 ◽  
Author(s):  
Ronald M. Kline ◽  
L. Daniel Muldoon ◽  
Heidi K. Schumacher ◽  
Larisa M. Strawbridge ◽  
Andrew W. York ◽  
...  
Keyword(s):  
Quality Measurement ◽  
New Drugs ◽  
Standards Of Care ◽  
Fee For Service ◽  
Medicare Beneficiaries ◽  
Coordinated Care ◽  
Care Model ◽  
Payment Model ◽  
Oncology Care ◽  
Payment Models

The Centers for Medicare & Medicaid Services developed the Oncology Care Model as an episode-based payment model to encourage participating practitioners to provide higher-quality, better-coordinated care at a lower cost to the nearly three-quarter million fee-for-service Medicare beneficiaries with cancer who receive chemotherapy each year. Episode payment models can be complex. They combine into a single benchmark price all payments for services during an episode of illness, many of which may be delivered at different times by different providers in different locations. Policy and technical decisions include the definition of the episode, including its initiation, duration, and included services; the identification of beneficiaries included in the model; and beneficiary attribution to practitioners with overall responsibility for managing their care. In addition, the calculation and risk adjustment of benchmark episode prices for the bundle of services must reflect geographic cost variations and diverse patient populations, including varying disease subtypes, medical comorbidities, changes in standards of care over time, the adoption of expensive new drugs (especially in oncology), as well as diverse practice patterns. Other steps include timely monitoring and intervention as needed to avoid shifting the attribution of beneficiaries on the basis of their expected episode expenditures as well as to ensure the provision of necessary medical services and the development of a meaningful link to quality measurement and improvement through the episode-based payment methodology. The complex and diverse nature of oncology business relationships and the specific rules and requirements of Medicare payment systems for different types of providers intensify these issues. The Centers for Medicare & Medicaid Services believes that by sharing its approach to addressing these decisions and challenges, it may facilitate greater understanding of the model within the oncology community and provide insight to others considering the development of episode-based payment models in the commercial or government sectors.

scholarly journals Where Are the Opportunities for Reducing Health Care Spending Within Alternative Payment Models?

2018 ◽  
Vol 14 (6) ◽  
pp. e375-e383 ◽  
Author(s):  
Gabrielle B. Rocque ◽  
Courtney P. Williams ◽  
Kelly M. Kenzik ◽  
Bradford E. Jackson ◽  
Karina I. Halilova ◽  
...  
Keyword(s):  
Health Care ◽  
Antineoplastic Therapy ◽  
First Episode ◽  
Health Care Spending ◽  
Administrative Claims ◽  
Antineoplastic Drugs ◽  
Fee For Service ◽  
Care Model ◽  
Episodes Of Care ◽  
Payment Models

Purpose: The Oncology Care Model (OCM) is a highly controversial specialty care model developed by the Centers for Medicare & Medicaid aimed to provide higher-quality care at lower cost. Because oncologists will be increasingly held accountable for spending as well as quality within new value-based health care models like the OCM, they need to understand the drivers of total spending for their patients. Methods: This retrospective cohort study included patients ≥ 65 years of age with primary fee-for-service Medicare insurance who received antineoplastic therapy at 12 cancer centers in the Southeast from 2012 to 2014. Medicare administrative claims data were used to identify health care spending during the prechemotherapy period (from cancer diagnosis to antineoplastic therapy initiation) and during the OCM episodes of care triggered by antineoplastic treatment. Total health care spending per episode includes all types of services received by a patient, including nononcology services. Spending was further characterized by type of service. Results: Average total health care spending in the three OCM episodes of care was $33,838 (n = 3,427), $23,811 (n = 1,207), and $19,241 (n = 678). Antineoplastic drugs accounted for 27%, 32%, and 36% of total health care spending in the first, second, and third episodes. Ten drugs, used by 31% of patients, contributed 61% to drug spending ($18.8 million) in the first episode. Inpatient spending also substantially contributed to total costs, representing 17% to 20% ($30.5 million) of total health care spending. Conclusion: Health care spending was heavily driven by both antineoplastic drugs and hospital use. Oncologists’ ability to affect these types of spending will determine their success under alternative payment models.

Characteristics of medical oncologists participating in the Oncology Care Model.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18017-e18017
Author(s):  
Ravi Bharat Parikh ◽  
Justin E. Bekelman ◽  
Qian Huang ◽  
Joseph Martinez ◽  
Ezekiel J. Emanuel ◽  
...  
Keyword(s):  
Medical Training ◽  
Cross Sectional Study ◽  
Care Utilization ◽  
Care Model ◽  
Cross Sectional ◽  
Intensity Index ◽  
Physician Participation ◽  
Medical Oncologists ◽  
Oncology Care ◽  
Payment Models

e18017 Background: The Oncology Care Model (OCM) is Medicare’s first bundled payment program for patients with cancer. Because practices voluntarily enrolled in the OCM in 2016, there may be differences between OCM-participating and non-participating oncologists that impact the OCM’s generalizability. We examine baseline characteristics of OCM participants and markets with high OCM physician participation. Methods: In this cross-sectional study, we identified characteristics of US medical oncologists practicing in 2016 using a national telephone-verified physician database. We linked this data with Dartmouth Atlas and Medicare claims data to identify market characteristics of areas with high OCM participation. We used logistic regression to examine relationships between market characteristics and OCM participation. Results: Of 10428 US medical oncologists, 2605 (24.9%) were listed on an OCM-participating practice’s website. There were no differences in sex or medical training between OCM participants and non-participants, although OCM participants were younger. OCM participants were more likely to be affiliated with large, group, and urban practices that were not part of a health system (Table). Southwest, Southeast, and mid-Atlantic markets had higher OCM participation. Markets with high OCM physician participation had higher specialist density, Hospital Care Intensity Index, and acute care utilization at the end of life (all p < 0.001). Market penetration of Accountable Care Organizations (adjusted odds ratio [aOR] 4.65, 95% CI 3.31-6.56, p < 0.001) and Medicare Advantage (aOR 2.82, 95% CI 1.97-4.06, p < 0.001) were associated with higher OCM participation. Conclusions: We found differences in provider and practice demographics, care intensity, and prior exposure to alternative payment models between OCM-participants and non-participants. Differences in practice and market characteristics influence oncologists’ participation in alternative payment models and should be accounted for in Medicare’s OCM evaluation. [Table: see text]

The Oncology Care Model: A Critique

2016 ◽  
pp. e109-e114 ◽  
Author(s):  
Christian A. Thomas ◽  
Jeffrey C. Ward
Keyword(s):  
Health Care ◽  
Health Care Expenditures ◽  
Critical Discussion ◽  
Cost Of Care ◽  
Fee For Service ◽  
Care Model ◽  
Patient Admissions ◽  
Pilot Model ◽  
Oncology Care ◽  
The Cost

Rapidly increasing national health care expenditures are a major area of concern as threats to the integrity of the health care system. Significant increases in the cost of care for patients with cancer are driven by numerous factors, most importantly the cost of hospital care and escalating pharmaceutical costs. The current fee-for-service system (FFS) has been identified as a potential driver of the increasing cost of care, and multiple stakeholders are interested in replacing FFS with a system that improves the quality of care while at the same time reducing cost. Several models have been piloted, including a Center for Medicare & Medicaid Innovation (CMMI)–sponsored medical home model (COME HOME) for patients with solid tumors that was able to generate savings by integrating a phone triage system, pathways, and seamless patient care 7 days a week to reduce overall cost of care, mostly by decreasing patient admissions to hospitals and referrals to emergency departments. CMMI is now launching a new pilot model, the Oncology Care Model (OCM), which differs from COME HOME in several important ways. It does not abolish FFS but provides an additional payment in 6-month increments for each patient on active cancer treatment. It also allows practices to participate in savings if they can decrease the overall cost of care, to include all chemotherapy and supportive care drugs, and fulfill certain quality metrics. A critical discussion of the proposed model, which is scheduled to start in 2016, will be provided at the 2016 American Society of Clinical Oncology (ASCO) Annual Meeting with practicing oncologists and a Centers for Medicare & Medicaid Services (CMS) representative.

Baseline evaluation of the patient-centered oncology care model.

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 50-50
Author(s):  
Manasi A. Tirodkar ◽  
Sarah Hudson Scholle
Keyword(s):  
Patient Centered Care ◽  
Care Planning ◽  
Coordinated Care ◽  
Motivation To Change ◽  
Care Model ◽  
Patient Centered ◽  
Centered Care ◽  
Oncology Care ◽  
The Impact ◽  
The Way

50 Background: The patient-centered medical home (PCMH) model of care is being widely adopted as a way to provide accessible, proactive, coordinated care and self-care through primary care practices. During active treatment for cancer, the oncology practice is often the primary setting supporting the patient and coordinating cancer treatment. For this project, we are implementing a Patient-centered Oncology Care model in five oncology practices and evaluating the impact on cost, quality, and patient experiences. Methods: To determine the structures and processes present in the practices at baseline, we conducted a self-assessment on the standards, followed with an on-site “audit” for compliance with the standards. To get a sense for organizational culture and motivation to change, we conducted site visits which included interviews with providers, staff and patients and observation of clinical encounters and workflow. Results: Among the highest priority structures and processes, the most common were telephone triage, symptom management, advance care planning, and the use of evidence-based guidelines. The least common were patient/family orientation, availability of same day appointments, discussion and documentation of goals of therapy, symptom assessment, and tracking of appointments. All of the practices had made patient-centered care a priority and staff were motivated to change. There was variation in the way providers and the care team used health information technology during clinical workflow. There was also variation in which staff coordinated care for patients and whether or not financial counseling was offered. All of the practices stated that they needed to work on implementing survivorship care planning, shared decision-making, and patient engagement in quality improvement and practice transformation Conclusions: The pilot oncology practices have many structures and processes in common. However, there is little standardization within practices in the way these processes are established and documented. Practices vary in how they are implementing patient-centered care processes. However, with motivation to change, staff and providers are actively engaged in the transformation process.

Designing Payment Contracts for Healthcare Services to Induce Information Sharing: The Adoption and the Value of Health Information Exchanges (HIEs)

MIS Quarterly ◽  
2021 ◽  
Vol 45 (2) ◽  
pp. 637-692 ◽  
Author(s):  
Mehmet Ayvaci ◽  
Huseyin Cavusoglu ◽  
Yeongin Kim ◽  
Srinivasan Raghunathan
Keyword(s):  
Health Information ◽  
Healthcare Services ◽  
Care Quality ◽  
Switching Behavior ◽  
Fee For Service ◽  
Payment Model ◽  
Health Information Exchanges ◽  
Provider Payment ◽  
The Government ◽  
Payment Models

Recent initiatives to improve healthcare quality and reduce costs have centered around payment mechanisms and IT-enabled health information exchanges (HIEs). Such initiatives profoundly influence both providers’ choices in terms of healthcare effort levels and HIE adoption and patients’ choice of providers. Using a game-theoretical model of a healthcare setup, we examine the role of payment models in aligning providers’ and patients’ incentives for realizing socially optimal (i.e., first-best) choices. We show that the traditional fee-for-service (FFS) payment model does not necessarily induce the first-best solution. The pay-for-performance (P4P) model may induce the first-best solution under some conditions if provider switching by patients during a health episode is socially suboptimal, making provider coordination less of an issue. We identify an episode-based payment (EBP) model that can always induce the first-best solution. The proposed EBP model reduces to the P4P model if the P4P model induces the first-best solution. In other cases, the first-best inducing EBP model is multilateral in the sense that the payment to a provider depends not only on the provider’s own efforts and outcomes but also on those of other providers. Furthermore, the payment in this EBP model is sequence dependent in the sense that payment to a provider is contingent upon whether the patient visits a given provider first or second. We show that the proposed EBP model achieves the lowest healthcare cost, not necessarily at the expense of care quality or provider payment, relative to FFS and P4P. Although our proposed contract is complex, it sets an optimality baseline when evaluating simpler contracts and also characterizes aspects of payment that need to be captured for socially desirable actions. We further show that the value of HIEs depends critically on the payment model as well as on the social desirability of patient switching. Under all three payment models, the HIE value is higher when switching by at least some patients is desirable than when switching by any patient is undesirable. Moreover, the HIE value is highest under the FFS model and lowest under the P4P model. Hence, assessing the value of HIEs in isolation from the underlying payment mechanism and patient-switching behavior may result in under- or overestimation of the HIE value. Therefore, as payment models evolve over time, there is a real need to reevaluate the HIE value and the government subsidies that induce providers to adopt HIEs.

Healthcare resource utilization, quality metrics, and costs of bladder cancer within the oncology care model.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 54-54
Author(s):  
L. Johnetta Blakely ◽  
Zsolt Hepp ◽  
Rupali Fuldeore ◽  
Samantha Tomicki ◽  
Jared Hirsch ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
High Risk ◽  
Healthcare Resource ◽  
Healthcare Resource Utilization ◽  
Quality Metrics ◽  
Low Risk ◽  
Novel Therapies ◽  
Medicare Beneficiaries ◽  
Care Model ◽  
Oncology Care

54 Background: The Oncology Care Model (OCM) incentivizes practices to provide higher quality, lower cost care for Medicare beneficiaries through payment arrangements that include financial and performance accountability for 6-month care episodes. We sought to describe the existing experience with bladder cancer (BC) for OCM practices, in the context of all OCM cancer types, given the dynamic treatment landscape in which new and emerging therapies will impact spending and patient care in this payment model. Objective: To estimate healthcare resource utilization (HRU), OCM quality metrics, and costs for OCM episodes among Medicare beneficiaries with BC. Methods: OCM episodes triggered by receipt of cancer therapy (index event) were identified among Medicare beneficiaries (100% Research Identifiable Files) from 2016-18. Other inclusion criteria were enrollment in Parts A & B for the entire OCM episode (6 months or until death) and 6 months pre-index date, Medicare as primary payer, and ≥1 qualifying Evaluation & Management visit during the episode. A cancer type was assigned to each episode. BC episodes were stratified as low- (defined by receipt of BCG and/or mitomycin without other systemic therapy) or high-risk (receipt of systemic therapy other than BCG or mitomycin) based on OCM definitions. Results: Of the 2.2 million OCM cancer episodes identified among 1 million beneficiaries, 60,099 (̃3%) were BC episodes. Our analytic cohort consisted of 43,621 BC episodes (69% low-risk and 31% high-risk) among 33,497 beneficiaries. Across BC episodes, average patient age was 76.6 years and 77% were male. Relative to low-risk episodes, high-risk episodes included higher metastatic cases (40 vs 2%), and more comorbidity burden (7.4 vs 4.3 Charlson comorbidity score). High-risk episodes had more hospital admissions (0.7 vs 0.2) and intensive care unit use (17 vs 5%), longer length of stay (5.9 vs 4.9 days), and higher rates of surgery (7 vs 1%) and mortality (17 vs 2%). Among OCM quality metrics, high-risk episodes had higher inpatient admissions (42 vs 15%) and emergency department visits (37 vs 20%) relative to low-risk episodes. Average spending per high-risk BC episode was ̃$38,000 (vs $9,204 for low-risk), with ̃$11,000 spent on systemic therapies and ̃$7,000 on inpatient services. Conclusions: High-risk OCM episodes of BC, which included 40% metastatic BC, had higher HRU and costs, and lower quality performance, than low-risk episodes. Novel therapies offer a significant opportunity to optimize BC management and improve quality of care, particularly for high-risk episodes. Further, as < 3% of OCM episodes were attributed to BC, and only one-third of BC episodes were classified as high-risk, controlling expenditure on novel therapies in BC episodes is unlikely to impact overall performance for practices participating in OCM.

scholarly journals MP86-04 INITIAL EXPERIENCE OF A UROLOGY PRACTICE PARTICIPATING IN AN EPISODE-BASED PAYMENT MODEL FOR CANCER CARE, THE ONCOLOGY CARE MODEL (OCM)

2018 ◽  
Vol 199 (4S) ◽  
Author(s):  
Jeremy Shelton ◽  
Richard David ◽  
Shirley Lee ◽  
Melanie Reed ◽  
Kambiz Dardashti ◽  
...  
Keyword(s):  
Cancer Care ◽  
Initial Experience ◽  
Care Model ◽  
Payment Model ◽  
Oncology Care

The Oncology Care Model: Perspectives From the Centers for Medicare & Medicaid Services and Participating Oncology Practices in Academia and the Community

2017 ◽  
pp. 460-466 ◽  
Author(s):  
Ron Kline ◽  
Kerin Adelson ◽  
Jeffrey J. Kirshner ◽  
Larissa M. Strawbridge ◽  
Marsha Devita ◽  
...  
Keyword(s):  
New York ◽  
Cancer Care ◽  
Care Delivery ◽  
The United States ◽  
Cancer Center ◽  
Fee For Service ◽  
Community Practice ◽  
Care Model ◽  
Practice Redesign ◽  
Oncology Care

Cancer care delivery in the United States is often fragmented and inefficient, imposing substantial burdens on patients. Costs of cancer care are rising more rapidly than other specialties, with substantial regional differences in quality and cost. The Centers for Medicare & Medicaid Services (CMS) Innovation Center (CMMIS) recently launched the Oncology Care Model (OCM), which uses payment incentives and practice redesign requirements toward the goal of improving quality while controlling costs. As of March 2017, 190 practices were participating, with approximately 3,200 oncologists providing care for approximately 150,000 unique beneficiaries per year (approximately 20% of the Medicare Fee-for-Service population receiving chemotherapy for cancer). This article provides an overview of the program from the CMS perspective, as well as perspectives from two practices implementing OCM: an academic health system (Yale Cancer Center) and a community practice (Hematology Oncology Associates of Central New York). Requirements of OCM, as well as implementation successes, challenges, financial implications, impact on quality, and future visions, are provided from each perspective.

The oncology care model and the future of alternative payment models: A gynecologic oncology perspective

2021 ◽  
Author(s):  
Emeline M. Aviki ◽  
Stephen M. Schleicher ◽  
Leslie Boyd ◽  
Margaret Liang ◽  
Emily M. Ko ◽  
...  
Keyword(s):  
Gynecologic Oncology ◽  
Care Model ◽  
The Future ◽  
Oncology Care ◽  
Payment Models

Bundling cancer subtypes in value-based care: A pilot analysis of lymphoma episodes in the Oncology Care Model.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18850-e18850
Author(s):  
Andrew Yue ◽  
Basit Iqbal Chaudhry ◽  
Stephen Matthew Schleicher ◽  
Scott F. Huntington ◽  
Aaron J. Lyss ◽  
...  
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Fee For Service ◽  
Care Model ◽  
Cancer Subtypes ◽  
Cost Variance ◽  
Icd 10 ◽  
Intensity Of Care ◽  
Oncology Care ◽  
Oncology Practice

e18850 Background: Value based models (VBMs) in which cancers are bundled are a growing alternative to fee for service, as in the Oncology Care Model (OCM). However, bundles in OCM may not capture the clinical granularity needed to predict resource utilization for cancer subtypes. One such bundle is lymphoma, which groups highly heterogeneous diseases with distinct treatments and differing intensity of care. Here, we compare OCM predicted episode costs (targets) to actual episode costs by lymphoma subtype. Methods: Our cohort study used OCM data from a large academic medical center (AMC) and large community oncology practice (COP). Six-month episodes of lymphoma beginning between July 2016 and June 2019 were categorized based on ICD-10 diagnoses on antineoplastic infusions and E&M visits, as well as disease and data modeling. Episodes were subdivided into follicular (FL), diffuse large B (DLBCL), small B (SBCL), mantle (MCL), Hodgkin (HL), Waldenstrom macroglobulinemia (WM), mature T/NK (T/NK), and Other. The distributional consistency of episode costs and targets for each subtype relative to the rest of the episodes was evaluated by Kolmogorov-Smirnov tests. We also compared the proportion of subtypes contributing to episodes in the AMC vs. COP. Results: A total of 1801 lymphoma episodes were identified (44% in AMC, 56% in COP). The most common subtypes (DLBCL and FL) contributed a larger proportion of episodes in the COP, while less frequent subtypes (T/NK, WM) were more prevalent at the AMC. Further, episode costs are significantly different across individual subtypes. Target variance was significantly lower than cost variance across subtypes. For example, the average target for WM was $50.4K, average costs were $40.2K, with 26% of episodes over target. In contrast, the average target for T/NK was $55.9K, average costs were $72.7K, with 64% of episodes over target. Conclusions: VBMs such as OCM currently aggregate cancer types and lack clinical granularity. Our evaluation of OCM episodes at an AMC and COP found considerable differences in lymphoma populations and in costs by subtype. Failure to account for clinical features (i.e. lymphoma history) could lead to inappropriate shifts of risk from payers to providers in VBMs.[Table: see text]

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