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

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.

Download Full-text

The association between hospitals’ risk-adjusted emergency department visits and survival and costs in kidney cancer patients.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.7_suppl.609 ◽

2019 ◽

Vol 37 (7_suppl) ◽

pp. 609-609

Author(s):

Joel E Segel ◽

Eric W. Schaefer ◽

Jay D. Raman ◽

Christopher S. Hollenbeak

Keyword(s):

Emergency Department ◽

Cancer Patients ◽

Kidney Cancer ◽

Mortality Rates ◽

Emergency Department Visits ◽

Medicare Data ◽

Initial Surgery ◽

Oncology Care ◽

Ed Visits ◽

The Cost

609 Background: As payers turn to alternative payment models, including the CMS Oncology Care Model, risk-adjusted emergency department (ED) visits are being incorporated as a quality. Yet little is know about this metric compares to existing metrics such as risk-adjusted mortality rates and costs. Methods: Using 2007-2012 SEER-Medicare data, we used logistic regression to model occurrence of an ED visit within 30 and 365 days for all kidney cancer patients receiving initial surgery. Our model controlled for demographics, stage, histology, systemic targeted therapy, and comorbidities. Based on model predictions, we created a ratio of actual versus predicted ED visits for hospitals to identify hospitals with higher and lower than predicted ED visit rates. We estimated the association between the hospitals’ ED visit ratio and hospitals’ risk-adjusted 365-day mortality rates, and 6- and 12-month total costs and total costs (less ED visits). Results: In our sample of 6,078 patients, 15.5% had an ED visit within 30 days of surgery and 43.5% within 365 days. For hospitals with ≥10 patients, we found no statistically significant association between 30-day or 365-day risk-adjusted ED visit rate and their 365-day risk-adjusted mortality rate. While hospitals’ 30-day ED visit rates were significantly associated with 6- and 12-month costs, the association was largely driven by the cost of the ED visit itself. Conversely, hospitals’ 365-day ED visit rates were significantly associated with 12-month costs after excluding the cost of the ED visit. Conclusions: Our results suggest hospitals’ risk-adjusted ED visit rates capture a qualitatively different measure of quality than the more commonly reported mortality rates and is significantly associated with patient cost.

Download Full-text

Frontline oncology care team primary palliative symptom guideline education, the oncology care model, and emergency department visits.

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.34_suppl.143 ◽

2018 ◽

Vol 36 (34_suppl) ◽

pp. 143-143 ◽

Cited By ~ 1

Author(s):

Susan McInnes ◽

Cheryl M Carrino ◽

Laura Shoemaker

Keyword(s):

Emergency Department ◽

Cancer Patients ◽

Cleveland Clinic ◽

Care Quality ◽

Emergency Department Visits ◽

Care Model ◽

Main Campus ◽

Palliative Care Teams ◽

Oncology Care ◽

Ed Visits

143 Background: The Oncology Care Model (OCM) is a novel 5-year quality-based Oncology payment and care delivery program established by the Centers for Medicare & Medicaid Service in 2016. OCM prioritizes high-quality, coordinated care for patients undergoing chemotherapy (chemo pts.) Participating centers provide augmented services to enhance care and meet quality goals. Challenging symptoms (sxs) are common among chemo pts and may lead to hospitalization and decreased quality of life. Specialist palliative care teams are not able to see all chemo pts with active sxs. Front line oncology care teams (FLC) need education on primary palliative sx management. Methods: Cleveland Clinic Taussig Cancer Institute is one of 181 practices voluntarily participating in OCM. Locations include main campus and 5 regional cancer offices with 100 oncologists caring for about 4,000 chemotherapy patients annually. Our OCM team engaged Oncology (Onc) and Palliative Medicine (PM) providers to standardize sx management. Education was provided to FLC of all disciplines. Electronic record analytics were used to determine emergency department (ED) utilization. Results: A multidisciplinary team of Onc and PM experts developed guidelines for 4 common sxs (chemotherapy-induced neuropathy, persistent cancer pain, nausea/vomiting and constipation. Guidelines were approved by key Onc and PM staff and made available to all providers online. There were 4 educational sessions for FLCs to all sites in 2017. Urgent sx outpatient appointment slots were created in oncology offices to address uncontrolled sx. From Dec 2017 to May 2018, ED visits for all cancer patients at main campus decreased from 500/month to 453/month (9.4%.) Reductions in ED visits were also seen at 2 hospitals adjacent to regional cancer centers (16% and 6%.) Conclusions: OCM participation provided an opportunity to improve care quality at our institution. Primary palliative sx guidelines were successfully developed by an interdisciplinary team and disseminated to FLC. Urgent sx management appointments were made available in oncology offices. These interventions coincided with a reduction in ED visits for all cancer patients.

Download Full-text

Sustaining the gains in cancer care from the oncology care model.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.6632 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. 6632-6632

Author(s):

Valerie P Csik ◽

Jared Minetola ◽

Andrew E. Chapman ◽

Neal Flomenberg

Keyword(s):

Cancer Care ◽

Clinical Pathways ◽

The United States ◽

Demonstration Project ◽

Cancer Center ◽

Care Model ◽

Drug Expenditures ◽

Oncology Care ◽

Ed Visits ◽

Feedback Data

6632 Background: The Oncology Care Model (OCM) is a 5-year demonstration project led by the Centers for Medicare and Medicaid Services (CMS) to create a framework for the future of oncology care in the United States. More than half way through the project, our large, urban NCI-designated cancer center chose to focus on and invest in resources and personnel for patient navigation and the development of clinical pathways. Although navigation has shown to reduce emergency department (ED) visits by as much as 6% per quarter compared to non-navigated patients, sustaining it is a challenge because it is a nonbillable service. Clinical pathways are a tool to reduce care variation by addressing drug expenditures, and represent an opportunity to reduce outpatient costs by as much as 35% when patients are treated on pathway.3 Many OCM practices made similar investments and all are facing the question: How will the infrastructure and efforts developed during OCM be sustainable after the demonstration project ends? Methods: An analysis of average ED cost and utilization as well as drug expenditures was conducted using OCM feedback data (Q1-Q8). Total utilization of ED visits and ED admits were used to determine a projected annualized cost which was compared to a budgeted navigation team. Similarly, projected annualized drug expenditures were compared to the annual cost of the pathways tool. Results: We found that ED visits and ED admits would need to be reduced by 11% to cover navigation costs. Similarly, a 0.7% reduction in total drug expenditures would cover the cost of clinical pathways. The OCM data represents a timeframe prior to implementation of these programs and an average increase of 1.6% per quarter for ED admits, a 0.6% decrease in ED visits and 2.7% increase in drug expenditures. This will serve as a baseline to measure progress towards our sustainability targets. Conclusions: Long term sustainability of the infrastructure developed during OCM to support cancer care transformation will be dependent on reducing high cost and highly utilized services. Aligning impact areas with resources/tools to ensure sustainability is an approach that can help define targets for OCM practices.

Download Full-text

Variations in hospitalization and emergency department/observation stays using the oncology care model methodology in Medicare data

Current Medical Research and Opinion ◽

10.1080/03007995.2020.1801403 ◽

2020 ◽

Vol 36 (9) ◽

pp. 1519-1527

Author(s):

Shuling Li ◽

Yi Peng ◽

Jiannong Liu ◽

Suying Li ◽

Leon Raskin ◽

...

Keyword(s):

Emergency Department ◽

Care Model ◽

Medicare Data ◽

Oncology Care

Download Full-text

Association between Spending in Oncology Care Model-Defined Episodes and Overall Survival in Multiple Myeloma Using 2012-2017 Medicare Data

Blood ◽

10.1182/blood-2020-136284 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 22-23

Author(s):

Ruben Niesvizky ◽

Zoe Clancy ◽

Ronda Copher ◽

Ryan B. Thomas ◽

Cynthia Z. Qi ◽

...

Keyword(s):

Drug Costs ◽

Specific Drug ◽

Care Model ◽

Analysis Group ◽

Medicare Data ◽

Primary Driver ◽

Oncology Care ◽

Comorbidity Index ◽

The Cost ◽

Over Time

Introduction: The Oncology Care Model (OCM) is an innovative payment model introduced by the Centers for Medicare & Medicaid Services in 2016, which aims to improve quality and reduce the cost of cancer care. Under this framework, practices are incentivized to reduce spending in chemotherapy-centered episodes. Previous studies using data from pre-OCM periods (i.e. before July 1, 2016) suggested that reducing OCM episode costs, particularly disease-specific drug costs, may adversely affect overall survival (OS) in patients with multiple myeloma (MM). Using more recent data that covers 1.5 years after OCM implementation, the current study aimed to evaluate trends in OCM-defined episode costs and OS over time. Additionally, the association between OCM-defined MM episode costs and OS in MM, as well as changes in the association between the pre- and post-OCM periods, were evaluated. Methods: Patients with newly diagnosed MM (NDMM) and ≥ 1 qualifying OCM-defined MM episode between 2012 and 2017 were selected from the 100% Medicare data. OCM episodes were defined as the 6-month period following a triggering MM treatment claim. Each episode was linked to a practice and classified based on participation in the OCM and occurrence of pre- versus post-OCM implementation. Regression models were developed, based on the OCM algorithm, to adjust for case severity mix at the practice level. The models evaluated the impact of patient and episode characteristics on total episode costs, and episode subcomponents (e.g. MM-specific drugs, other medical treatment). Based on the regression outputs, standardized costs were calculated for each practice, adjusting for differences in patient and episode characteristics. All costs were inflated to 2017 US dollars (USD). From initial MM diagnosis, mean unadjusted episode costs, mean standardized episode costs, and 1-year OS rate were described over time by the year of first episode initiation. Two Cox proportional hazards models were constructed for OS with adjustment for key patient covariates (i.e. age, gender, comorbidity index, race, number of OCM episodes, and disability entitlement). Model 1 evaluated the association between OS and standardized total episode costs and the proportion of episode costs attributed to MM-specific drugs. Model 2 evaluated the effect on OS of the interaction between the time period (i.e. pre-OCM vs post-OCM) and total standardized episode costs. The analyses were repeated for key patient subgroups stratified by comorbidity status (i.e. low Charlson Comorbidity Index [CCI] vs high CCI) and practice type (i.e. OCM vs non-OCM). Results: A total of 17,363 patients with NDMM (51.0% male) were included in the analysis. Mean age at diagnosis was 74.8 years (30.0-102.0). Patient characteristics were comparable between pre-OCM and post-OCM periods. There were a total of 41,972 OCM episodes during the mean 2.2 years (standard deviation [SD] 1.4) of follow-up. Average (SD) MM-drug costs, other medical and drug costs, and total costs per OCM episode were USD 51,482 (USD 31,752), USD 22,625 (USD 28,452), and USD 74,107 (USD 38,606), respectively. From 2012 to 2017, average total episode costs, MM-drug costs, and survival all increased (Table). Model 1 indicated that a USD 10,000 increase in standardized total costs was associated with a 27.5% lower risk of death (hazard ratio [HR] 0.725; P < 0.05) and that MM-drug costs were the primary driver for the improved OS. The hazard of death decreased by 21.3% (HR 0.787; P < 0.05) for every 10% increase in the proportion of costs attributed to MM-drug costs versus other medical costs. Model 2 showed the association was similar during pre-OCM and post-OCM periods. Consistent results were observed between subgroups of high versus low CCI and OCM versus non-OCM practices. Conclusions: The analysis identified a positive correlation between average spending within OCM-defined episodes and OS among patients with NDMM, demonstrating observable clinical value for patients. This correlation remained consistent across pre-OCM and post-OCM periods. A closer evaluation of the cost subcomponents suggested that MM-specific drug costs are a primary driver for the observed OS benefit. Patient benefit from the innovative, albeit higher cost, therapies is noteworthy given the improved survival of MM. Careful evaluation is warranted for healthcare providers when attempting to reduce spending in response to new payment models. Disclosures Niesvizky: BMS: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Clancy:BMS: Current Employment, Current equity holder in publicly-traded company. Copher:Bristol Myers Squibb: Current Employment. Thomas:BMS: Current Employment. Qi:BMS: Other: Employee of Analysis Group Inc., which received consulting fees; Astellas Pharma, Inc.: Research Funding. Zhou:BMS: Other: Employee of Analysis Group Inc., which received consulting fees. Zichlin:BMS: Other: Employee of Analysis Group Inc., which received consulting fees. Koenigsberg:BMS: Other: Employee of Analysis Group Inc., which received consulting fees. Signorovitch:BMS: Other: Employee of Analysis Group Inc., which received consulting fees.

Download Full-text

Oncology practice changes during a multistep Oncology Care Model practice transformation project.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.31_suppl.88 ◽

2019 ◽

Vol 37 (31_suppl) ◽

pp. 88-88

Author(s):

Debra Wujcik ◽

Susan T. Owenby ◽

Moh'd M. Khushman ◽

Daniel Cameron ◽

Thomas Wayne Butler ◽

...

Keyword(s):

Lung Cancer ◽

Nurse Practitioners ◽

Organizational Support ◽

Statistical Significance ◽

Performance Status ◽

Cost Of Care ◽

Care Model ◽

Oncology Care ◽

Ed Visits

88 Background: Treatment of lung cancer has seen a paradigm shift in recent years. While the availability of newer treatment options such as targeted therapy and immunotherapy have provided new hope for better outcomes, this has added to the cost of care. Participation in the Center for Medicare Services’ Oncology Care Model (OCM) provides opportunities for oncology practices to identify practice transformation (PT) change strategies that result in improved quality of care (QOL) and cost savings. Methods: A lung cancer PT team convened to facilitate changes that improve patient outcomes and decrease costs at an OCM organization. The year-long project included clinical treatment updates, quantitative and qualitative assessments, and data sharing. Practice changes focused on biomarker driven treatment selection, nurse navigation to better manage symptoms and decrease emergency department (ED) visits and hospitalizations, and earlier advanced care planning (ACP) discussions. Surveys were completed by oncology physicians and nurse practitioners at baseline (n = 9) and end of the project (n = 7). Results: After education, there were more correct responses in 3 of 6 knowledge questions and providers noted less concern about performance status or co-morbidities when prescribing immunotherapy. Providers noted fewer barriers with biomarker documentation; self-reported confidence in 4 questions of biomarker selection was unchanged. Providers reported increased participation of nurse navigators to impact ED visits and hospitalizations over time. Documentation of ACP discussions increased, 42% (8/19) to 56% (13/23), but did not reach statistical significance due to sample size. Although providers reported changes toward earlier ACP discussions, 1 in 3 still wait until performance status declines to initiate discussion. Conclusions: Systematic PT can improve quality of patients care and measures used in value-based care reimbursement models. Providers need ongoing education, practice feedback, and organizational support to effect positive practice changes. In addition, new strategies to increase provider ability to initiate end of life discussions need to be explored.

Download Full-text

Handling coarsened age information in the analysis of emergency department presentations

BMC Medical Research Methodology ◽

10.1186/s12874-020-01181-x ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Rhonda J. Rosychuk ◽

Jeff W.N. Bachman ◽

Anqi Chen ◽

X. Joan Hu

Keyword(s):

Emergency Department ◽

Sample Size ◽

Uniform Distribution ◽

Empirical Distribution ◽

Data Access ◽

Recurrent Event ◽

Fiscal Year ◽

Recurrent Event Data ◽

Higher Ed ◽

Ed Visits

Abstract Background Administrative databases offer vast amounts of data that provide opportunities for cost-effective insights. They simultaneously pose significant challenges to statistical analysis such as the redaction of data because of privacy policies and the provision of data that may not be at the level of detail required. For example, ages in years rather than birthdates available at event dates can pose challenges to the analysis of recurrent event data. Methods Hu and Rosychuk provided a strategy for estimating age-varying effects in a marginal regression analysis of recurrent event times when birthdates are all missing. They analyzed emergency department (ED) visits made by children and youth and privacy rules prevented all birthdates to be released, and justified their approach via a simulation and asymptotic study. With recent changes in data access rules, we requested a new extract of data for April 2010 to March 2017 that includes patient birthdates. This allows us to compare the estimates using the Hu and Rosychuk (HR) approach for coarsened ages with estimates under the true, known ages to further examine their approach numerically. The performance of the HR approach under five scenarios is considered: uniform distribution for missing birthdates, uniform distribution for missing birthdates with supplementary data on age, empirical distribution for missing birthdates, smaller sample size, and an additional year of data. Results Data from 33,299 subjects provided 58,166 ED visits. About 67% of subjects had one ED visit and less than 9% of subjects made over three visits during the study period. Most visits (84.0%) were made by teenagers between 13 and 17 years old. The uniform distribution and the HR modeling approach capture the main trends over age of the estimates when compared to the known birthdates. Boys had higher ED visit frequencies than girls in the younger ages whereas girls had higher ED visit frequencies than boys for the older ages. Including additional age data based on age at end of fiscal year did not sufficiently narrow the widths of potential birthdate intervals to influence estimates. The empirical distribution of the known birthdates was close to a uniform distribution and therefore, use of the empirical distribution did not change the estimates provided by assuming a uniform distribution for the missing birthdates. The HR approach performed well for a smaller sample size, although estimates were less smooth when there were very few ED visits at some younger ages. When an additional year of data is added, the estimates become better at these younger ages. Conclusions Overall the Hu and Rosychuk approach for coarsened ages performed well and captured the key features of the relationships between ED visit frequency and covariates.

Download Full-text

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

Supportive Care in Cancer ◽

10.1007/s00520-021-06436-x ◽

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.

Download Full-text

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

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e18852 ◽

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]

Download Full-text