Association of Participation in the Oncology Care Model With Medicare Payments, Utilization, Care Delivery, and Quality Outcomes

JAMA ◽  
2021 ◽  
Vol 326 (18) ◽  
pp. 1829
Author(s):  
Nancy L. Keating ◽  
Shalini Jhatakia ◽  
Gabriel A. Brooks ◽  
Amanda S. Tripp ◽  
Inna Cintina ◽  
...  
Keyword(s):  
Care Delivery ◽  
Care Model ◽  
Quality Outcomes ◽  
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.

Building Sustainable Practice Transformation Through Payment Reform Initiatives

2022 ◽  
Author(s):  
Gabrielle B. Rocque ◽  
D'Ambra N. Dent ◽  
Nicole E. Caston ◽  
Terri Salter ◽  
Jordan DeMoss ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Care Delivery ◽  
Care Model ◽  
Payment Reform ◽  
Factors Affecting ◽  
Use Of Technology ◽  
Implementation Costs ◽  
Oncology Care ◽  
Negative Impacts ◽  
The Cost

PURPOSE: Novel value-based payment approaches provide an opportunity to deploy and sustain health care delivery interventions, such as treatment planning documentation. However, limited data are available on implementation costs. METHODS: We described key factors affecting the cost of implementing care improvements under value-based payments, using treatment planning and Medicare's Oncology Care Model as examples. We estimated expected costs of implementing treatment plans for years 1 and 2-6 under (1) different staffing models, (2) use of technology, and (3) differences in the patients engaged. We compared costs to the payment amounts under the Oncology Care Model. RESULTS: Team-based models where staffing is aligned with skills needed for key tasks (eg, a combination of lay navigator, nurse, and physician) are more financially feasible when compared with using physicians or nurses alone. When existing staff are at or near capacity, hiring new staff focused on practice transformation activities allows adequate time for new initiatives without negative impacts on existing services. Investments in information technology can enhance staff productivity, but initial costs may be high. Interventions may not be financially feasible if implemented for a small patient volume or only for patients insured by a particular payer. Finally, costs may be higher for disadvantaged populations, and equity in care delivery may require higher payments from payers. CONCLUSION: Estimating the cost of implementing an intervention in different types of practice settings with various types of patients is essential to ensure that a value-based payment system will adequately support desired improvements in quality of care for all patients.

scholarly journals Commentary: Quality nutrition care is integral to the Oncology Care Model

2021 ◽  
Author(s):  
Mary Beth Arensberg ◽  
Beth Besecker ◽  
Laura Weldishofer ◽  
Susan Drawert
Keyword(s):  
Best Practice ◽  
Treatment Guidelines ◽  
Nutrition Therapy ◽  
Care Model ◽  
Nutrition Care ◽  
Ambulatory Oncology ◽  
Oncology Care ◽  
Improvement Programs ◽  
And Performance ◽  
Registered Dietitian Nutritionists

AbstractThe Oncology Care Model (OCM) is a US Centers for Medicare & Medicaid Services (CMS) specialty model implemented in 2016, to provide higher quality, more highly coordinated oncology care at the same or lower costs. Under the OCM, oncology clinics enter into payment arrangements that include financial and performance accountability for patients receiving chemotherapy treatment. In addition, OCM clinics commit to providing enhanced services to Medicare beneficiaries, including care coordination, navigation, and following national treatment guidelines. Nutrition is a component of best-practice cancer care, yet it may not be addressed by OCM providers even though up to 80% of patients with cancer develop malnutrition and poor nutrition has a profound impact on cancer treatment and survivorship. Only about half of US ambulatory oncology settings screen for malnutrition, registered dietitian nutritionists (RDNs) are not routinely employed by oncology clinics, and the medical nutrition therapy they provide is often not reimbursed. Thus, adequate nutrition care in US oncology clinics remains a gap area. Some oncology clinics are addressing this gap through implementation of nutrition-focused quality improvement programs (QIPs) but many are not. What is needed is a change of perspective. This paper outlines how and why quality nutrition care is integral to the OCM and can benefit patient health and provider outcomes.

Impact of cancer- and patient-level factors on provider risk in the Oncology Care Model.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18852-e18852
Author(s):  
Basit Iqbal Chaudhry ◽  
Andrew Yue ◽  
Shuchita Kaila ◽  
Kay Sadik ◽  
Lisa Tran ◽  
...  
Keyword(s):  
Domain Knowledge ◽  
Research Literature ◽  
Risk Exposure ◽  
Progression Rate ◽  
Cell Transplant ◽  
Care Model ◽  
Data Set ◽  
Patient Level ◽  
Oncology Care ◽  
The Impact

e18852 Background: Transferring financial risk from payers to providers to align incentives is central to value-based payment (VBP) reform, including Medicare’s Oncology Care Model (OCM). We simulated the impact of selected cancer- and patient-level factors on providers’ risk in OCM for multiple myeloma (MM), due to its clinical complexity. We hypothesize that risk exposure is sensitive to factors extrinsic to the OCM methodology, including clinical phenotype, disease state and progression rate. Methods: Simulation was used to address omitted variable bias in payer data. We developed 9 key clinical MM scenarios to examine provider risk, based on conceptual frameworks that included patient- and cancer-level factors. The model was parameterized using the Medicare limited data set, research literature and domain knowledge. Twenty factors were varied for each model, e.g. age, autologous stem cell transplant (ASCT). Results: Simulations results showed MM risk for providers depended highly on cancer and patient level factors (see table). For example, high-risk patients were on average $21.5K over target while undergoing ASCT (despite risk adjustment for ASCT) and $18-28K under target for follow on maintenance (maint.) episodes. Conclusions: Provider exposure to risk in OCM is highly sensitive to factors at the cancer and patient level. The distribution of clinical phenotypes, state of disease, and rate of disease progression can significantly impact risk exposure for providers in OCM. New methodologies that model risk in more clinically granular ways are needed to improve VBP in oncology. [Table: see text]

Potential Winners and Losers: Understanding How the Oncology Care Model May Differentially Affect Hospitals

2021 ◽  
pp. OP.21.00050
Author(s):  
Joel E. Segel ◽  
Eric W. Schaefer ◽  
Nicholas G. Zaorsky ◽  
Christopher S. Hollenbeak ◽  
Haleh Ramian ◽  
...  
Keyword(s):  
Medical School ◽  
Care Model ◽  
For Profit ◽  
Medicare Data ◽  
Higher Ed ◽  
Oncology Care ◽  
Ed Visits ◽  
Breast And Prostate Cancer ◽  
Expected Mortality ◽  
Rural Patients

PURPOSE: With the introduction of the Oncology Care Model and plans for the transition to Oncology Care First, alternative payment models (APMs) are an increasingly important piece of the oncology care landscape. Evidence is mixed on the Oncology Care Model's impact on utilization and costs, but as policymakers consider expansion of similar models, it is critical to understand the characteristics of hospitals that may be differentially affected. METHODS: We used 2007-2016 SEER-Medicare data to identify patients with breast and prostate cancer receiving chemotherapy, endocrine therapy (breast), or androgen deprivation therapy (prostate). For each hospital, we calculated 6-month expected mortality, emergency department (ED) visits, inpatient admissions, and costs, all commonly collected APM outcomes. After calculating observed-to-expected rates for each outcome by hospital, we estimated the association between observed-to-expected rates and characteristics of each hospital to understand hospital characteristics that might be associated with higher- or lower-than-expected rates of each outcome. RESULTS: Hospitals with > 15% rural patients had significantly higher-than-expected mortality (0.31 points higher, P < .001) and ED visit rates (0.10 points higher, P = .029) as well as significantly lower costs (0.06 points lower, P = .004). Hospitals unaffiliated with a medical school also experienced significantly higher-than-expected mortality and ED visits. Hospitals eligible for disproportionate share hospital payment experienced significantly higher ED visits but lower costs. For-profit hospitals experienced higher-than-expected mortality. CONCLUSION: Rural hospitals and those unaffiliated with a medical school may require special consideration as APMs expand in oncology care. Designated cancer centers and larger hospitals may be advantaged.

Centers for Medicare & Medicaid Services' Oncology Care Model: Delivering Higher Value Cancer Care

2017 ◽  
Vol 101 (5) ◽  
pp. 569-571 ◽  
Author(s):  
LK Mortimer ◽  
LM Strawbridge ◽  
EW Lukens ◽  
A Bassano ◽  
PH Conway ◽  
...  
Keyword(s):  
Cancer Care ◽  
Care Model ◽  
Oncology Care

Breast Cancer Stage Is Associated With Exceeding Target Price in the Oncology Care Model

2021 ◽  
Author(s):  
Ryan B. Thomas ◽  
Vittorio Maio ◽  
Anna Chen ◽  
Seojin Park ◽  
Dexter Waters ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Academic Medical Center ◽  
Stage Iv ◽  
Cost Of Care ◽  
Mean Difference ◽  
Cancer Stage ◽  
Care Model ◽  
Target Price ◽  
Old Patients ◽  
Oncology Care

PURPOSE: To explore mean difference between Oncology Care Model (OCM) total costs and target price among breast cancer episodes by stage under the Centers for Medicare and Medicaid Services OCM payment methodology. METHODS: Breast cancer episodes from OCM performance period 1-4 reconciliation reports (July 1, 2016-July 1, 2018) were linked with health record data from a large, academic medical center. Demographics, total cost of care (TCOC), and target price were measured by stage. Adjusted differences between TCOC and target price were compared across cancer stage using multivariable linear regression. RESULTS: A total of 539 episodes were evaluated from 252 unique patients with breast cancer, of which 235 (44%) were stage I, 124 (23%) stage II, 33 (6%) stage III, and 147 (27%) stage IV. About 37% of episodes exceeded target price. Mean differences from target price were –$1,782, $2,246, –$6,032, and $11,379 all in US dollars (USD) for stages I through IV, respectively. Stage IV episodes had highest mean TCOC ($44,210 USD) and mean target price ($32,831 USD) but also had higher rates of chemotherapy, inpatient admission, and novel therapy use. After adjusting for covariates, stage IV and ≥ 65-year-old patients had the highest mean difference from target price ($17,175 USD; 95% CI, $12,452 to $21,898 USD). CONCLUSION: Breast cancer episodes in older women with distant metastases most frequently exceeded target price, suggesting that target price did not adequately account for complexity of metastatic cancers. A metastatic adjustment introduced in PP7 represents a promising advancement in the target price methodology and an impact evaluation will be needed.

scholarly journals Managers Shaping the Service Triangle: Navigating Resident and Worker Interests Through Work Design in Nursing Homes

2020 ◽  
pp. 073088842093077
Author(s):  
Lander Vermeerbergen ◽  
Aoife M. McDermott ◽  
Jos Benders
Keyword(s):  
Health Care ◽  
Nursing Home ◽  
Nursing Homes ◽  
Care Delivery ◽  
Work Design ◽  
Service Users ◽  
Care Model ◽  
Golden Mean ◽  
Stakeholder Interests ◽  
Centered Care

Managers play a key role in shaping the service triangle and navigating stakeholder interests within this. In health care, labor shortages are prompting consideration of the consequences of care delivery for service users and staff. Here, the authors consider how senior nursing home managers tasked with balancing resident and worker interests manage tensions using work design. The findings identify a five-cluster typology, reflecting variations in how managers from 20 Flemish nursing homes operationalize the same resident-centered care model. Managers purposively shape a different service triangle in each operationalization, variously prioritizing benefits for residents, seeking the golden mean, or attempting to suppress tensions.

scholarly journals Hospice or Hospital: The Costs of Dying of Cancer in the Oncology Care Model

2020 ◽  
Vol 1 (1) ◽  
pp. 92-96 ◽  
Author(s):  
J. Russell Hoverman ◽  
B. Brooke Mann ◽  
Sara Phu ◽  
Philip Nelson ◽  
Jad E. Hayes ◽  
...  
Keyword(s):  
Care Model ◽  
Oncology Care

scholarly journals Characteristics of Physicians Participating in Medicare’s Oncology Care Model Bundled Payment Program

2019 ◽  
Vol 15 (10) ◽  
pp. e897-e905 ◽  
Author(s):  
Ravi B. Parikh ◽  
Justin E. Bekelman ◽  
Qian Huang ◽  
Joseph R. Martinez ◽  
Ezekiel J. Emanuel ◽  
...  
Keyword(s):  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Medical Training ◽  
Care Model ◽  
Cross Sectional ◽  
Bundled Payment ◽  
Practice Level ◽  
Physician Participation ◽  
Medical Oncologists ◽  
Oncology Care

PURPOSE: The Oncology Care Model (OCM) is Medicare’s first bundled payment program for patients with cancer. We examined baseline characteristics of OCM physician participants and markets with high OCM physician participation to inform generalizability and complement the ongoing practice-level evaluation of the OCM. 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 these data with Dartmouth Atlas and Medicare claims data from 2011 through 2016 to identify characteristics of markets with high OCM participation. We used logistic regression to examine relationships between market characteristics and OCM participation. RESULTS: Of 10,428 US medical oncologists, 2,605 (24.9%) were listed in an OCM practice. There were no differences in sex or medical training between OCM participants and nonparticipants, although OCM participants were slightly younger. OCM participants practiced in larger (median daily patient volume, 80 v 55 patients) and urban practices (95.2% v 90.7%) and were less likely to be part of a health system (41.0% v 60.4%) or solo practice (45.5% v 67.4%; all P < .001). Participation was higher in southern and mid-Atlantic markets. Markets with high OCM physician participation had higher specialist density, hospital care intensity, and acute care use at the end of life (all P < .001). Market-level penetration of Accountable Care Organizations (adjusted odds ratio, 4.65; 95% CI 3.31 to 6.56; P < .001) and Medicare Advantage (adjusted odds ratio 2.82; 95% CI, 1.97 to 4.06; P < .001) were associated with higher OCM participation. CONCLUSION: In the first description of oncologists participating in the OCM, we found differences in practice demographics, care intensity, and exposure to nontraditional payment models between OCM-participating and nonparticipating physicians. Such provider-level differences may not be captured in Medicare’s practice-level analysis.

Sign in / Sign up

Export Citation Format

Share Document