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]

Secret Sauce—How Diverse Practices Succeed in Centers for Medicare & Medicaid Services Oncology Care Model

2021 ◽  
pp. OP.21.00165
Author(s):  
Ronald M. Kline ◽  
Sibel Blau ◽  
Nikolas R. Buescher ◽  
Amy R. Ellis ◽  
J. Russell Hoverman ◽  
...  
Keyword(s):  
Business Models ◽  
Medical Center ◽  
Academic Medical Center ◽  
Emergency Department Visits ◽  
Care Model ◽  
Treatment Pathways ◽  
Payment Model ◽  
Community Oncology ◽  
Oncology Care ◽  
Oncology Practice

PURPOSE: CMS' Oncology Care Model (OCM) is an episode-based alternative payment model designed to incent high-value care through the use of monthly payments for enhanced services and performance-based payments on the basis of decreases in spending compared with risk-adjusted historical benchmarks. Transitioning from a fee-for-service model to a value-based, alternative payment model in oncology can be difficult; some practices will perform better than others. We present detailed experiences of four successful OCM practices, each operating under diverse business models and in different geographic areas. METHODS: Practices that achieved success in OCM, on the basis of financial metrics, describe pathways to success. The practices represent distinct business models: a medium-sized community oncology practice, a large statewide community oncology practice, a hospital-affiliated practice, and a large academic medical center. RESULTS: Practices describe effective changes in practice culture such as new administrative flexibilities, physician champions, improved communication, changes in physician compensation, and increased physician-level transparency. New or improved clinical services include acute care clinics, care coordination, phone triage, end-of-life care programs, and adoption of treatment pathways that identify high-value drug use, including better use of supportive care drugs. CONCLUSION: There is no one thing that will ensure success in OCM. Success requires whole practice transformation, encompassing both administrative and clinical changes. Communication between administrative and clinical teams is vital, along with improved data sharing and transparency. Clinical support services must expand to manage problems and symptoms in a timely way to prevent costly emergency department visits and hospitalizations, while constant attention must be paid to making high-value therapeutic choices in both oncolytic and supportive drug categories.

Pursuit of performance: An exploration of predictors associated with achieving performance based payments for breast cancer episodes under the Oncology Care Model.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18035-e18035
Author(s):  
Andrew Jehyun Song ◽  
Arianna Kee ◽  
Jared Minetola ◽  
Karen Walsh ◽  
Valerie P Csik ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Systemic Therapy ◽  
Medical Center ◽  
Academic Medical Center ◽  
Novel Therapies ◽  
Care Model ◽  
Logistic Regression Models ◽  
Multivariable Logistic Regression ◽  
Oncology Care

e18035 Background: The Oncology Care Model (OCM) captures patient costs in a 6-month episode triggered by administration of systemic therapy. Most breast cancer (BC) patients will receive systemic therapy, with variations depending on stage and hormonal status, which makes BC an ideal indication to study costs in the OCM. Practices earn performance based payments (PBP) if aggregate episodic expenditures are managed below set target prices. We investigated predictors for episodic expenditures exceeding target prices, thus reducing potential for PBP. Methods: We identified BC episodes with non-decedent beneficiaries attributable to our academic medical center from OCM Reconciliation Reports during 7/1/16-6/30/17. Cohorts were defined as episodes whose costs were above target (Cohort 1) and those below (Cohort 2). The Wilcoxon Rank-Sum test was used to compare actual and target episode expenditure between cohorts. Multivariable logistic regression models were used to assess association of maintaining costs below target due to various predictors. Results: A total of 369 episodes were included in the study, with 124 episodes in Cohort 1 and 245 in Cohort 2. Median actual and target episode expenditures were higher in Cohort 1 (actual: $23,466 vs. $2,691, p < 0.0001; target: $8,425 vs. $5,870, p < 0.0001). In multivariable logistic regression, episodes were more likely to be below target if novel therapies, Part B drugs, or inpatient admissions were not utilized, controlling for other predictors (see Table). Conclusions: Large disparities exist for both actual expenditures and target prices for BC episodes in the OCM. Novel therapies, Part B drugs, and inpatient admissions are negatively associated with maintaining episode expenditures below target. Risk-adjustments for these expenditures need to be overhauled in OCM to accurately capture costs associated with management of cancer patients, and provide practical target prices for institutions to continue delivery of value based care. [Table: see text]

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.

Cancer inpatient malnutrition risk, documentation, and ICD-10 coding in an academic medical center.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 12107-12107
Author(s):  
Aynur Aktas ◽  
Lenna Finch ◽  
Danielle Boselli ◽  
Declan Walsh ◽  
Kunal C. Kadakia ◽  
...  
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Stage Iv ◽  
Academic Community ◽  
Primary Site ◽  
Disease Stage ◽  
Cancer Site ◽  
Black Race ◽  
Stage Iv Disease ◽  
Icd 10

12107 Background: Malnutrition (MN) is common in hospitalized cancer patients but often underdiagnosed. We evaluated the prevalence of MN risk, dietitian documented MN (DDMN), and physician coded malnutrition (PCMN) in a consecutive cohort of cancer inpatients in an academic, community-based medical center. Methods: Electronic medical records (EMR) were reviewed for inpatients with a solid tumor diagnosis staged I-IV and admitted to Atrium Health Carolinas Medical Center at least once between 1/1/2016 to 5/21/2019. All data were collected from the first admission EMR encounter closest to the cancer diagnosis date. High MN risk was a score ≥2 on the Malnutrition Screening Tool (MST) completed by an RN at admission. Registered Dietitian (RD) assessments were reviewed for DDMN and grade (mild, moderate, severe). PCMN diagnosis was based on MN ICD-10 codes extracted from the medical coder’s discharge summary. Multivariate logistic regression models identified associations between clinic-demographic factors and the prevalence of DDMN and PCMN with stepwise selection. Results: N=5,143; 48% females. Median age 63 (range 18-102) years. 70% White; 24% Black, 3% Latino. Most common cancers: thoracic 19% and digestive system (14% other, 11% colorectal). 28% had known stage IV disease. The MST was completed in 79%. Among those with MST ≥2 (N=1,005; 25%), DDMN and PCMN prevalence was 30% and 22%, respectively. In the entire cohort, 8% had DDMN; 7% PCMN; 4% both. Prevalence of MN risk, DDMN, and PCMN by cancer site are in the Table. DDMN (N=420) was mild 2%, moderate 16%; severe 66%; unspecified 16%. On discharge, PCMN (N=360) was mild 10%; moderate 0%; severe 69%; unspecified 21%. Male gender (OR 1.27 [1.01, 1.59]), Black race (OR 1.57 [1.25, 1.98]), stage IV disease (v. I-III) (OR 3.08 [2.49, 3.82]), and primary site were all independent predictors of DDMN (all p<0.05); Black race (OR 1.46 [1.14, 1.87]), stage IV disease (OR 2.70 [2.15, 3.39]), and primary site were independent predictors of PCMN (all p<0.05). Conclusions: 25% of cancer inpatients were at high risk for MN. Primary site, disease stage, and race were independent predictors of a greater risk. MN appears to be under-diagnosed compared to population studies. This is the first study to report the prevalence of MN in a large cancer inpatient database with a representative population.[Table: see text]

Oral chemotherapy education: Hitting the mark?

2020 ◽  
Vol 38 (29_suppl) ◽  
pp. 221-221
Author(s):  
Jonathan L Berry ◽  
Jim W Doolin ◽  
Garrett Diltz ◽  
Tenzin Dechen ◽  
Natalia Forbath ◽  
...  
Keyword(s):  
Formal Education ◽  
Medical Center ◽  
Academic Medical Center ◽  
Hematologic Malignancies ◽  
Oral Chemotherapy ◽  
Community Practice ◽  
Medication Persistence ◽  
Process Measures ◽  
Education Group ◽  
Oncology Practice

221 Background: ASCO’s Quality Oncology Practice Initiative (QOPI) includes process measures on oral chemotherapy education. Whether achievement of these measures has an impact on clinical outcomes and if an intervention to improve these measures can improve outcomes is not yet known. Methods: A retrospective analysis was conducted of patients initiated on oral chemotherapy in an academic medical center site and a community oncology practice between January 2016 and October 2019. The primary aim was to compare the time to emergency department (ED) within 90 days from initiation of oral chemotherapy of patients who met the QOPI process measure through an intervention of pharmacist-driven education with a comparison group of patients who had not received formal education. A secondary aim was to assess for a difference in oral chemotherapy medication persistence. Data were also analyzed by demographics, concurrent parenteral therapy, intent of therapy, and disease group. Results: 285 patients in the education group and 284 patients in the non-education group were analyzed. The education group had a higher proportion of patients with gastrointestinal and gynecologic cancers, and a lower proportion of patients with hematologic malignancies, compared to the non-education group. The education group also had a higher proportion of patients treated at the community practice compared to the non-education group. There was no statistical difference in median time-to-ED, with 49 days (IQR 37-74) in the education group and 59 days (IQR 41-60) in the non-education group (p=0.15). Conclusions: In patients receiving oral chemotherapy, pharmacist-driven education with improvement in QOPI process measures did not result in an improvement in time to ED. One factor contributing to this result may be that only 20% of patients required ED-level care within 90 days of starting oral We continue to collect data regarding medication persistence, which may be a more sensitive outcome measure. At this point, further work is needed to determine if achievement or modification of the QOPI oral chemotherapy process measures results in a clinically significant change in outcome. [Table: see text]

A chemotherapy privileging process for advanced practice providers at an academic medical center

2019 ◽  
Vol 26 (1) ◽  
pp. 116-123
Author(s):  
Michelle A Carrasquillo ◽  
Tyler A Vest ◽  
Jill S Bates ◽  
Aimee Faso ◽  
Jessica Auten ◽  
...  
Keyword(s):  
Supportive Care ◽  
Nurse Practitioners ◽  
Medical Center ◽  
Academic Medical Center ◽  
Physician Assistants ◽  
Advanced Practice ◽  
Training Process ◽  
Academic Medical ◽  
The Creation ◽  
Oncology Practice

Purpose Nurse practitioners, physician assistants, and pharmacists are advanced practice providers who are highly trained and qualified healthcare professionals that can help support traditional demands on oncologists' increased time in direct patient care. The purpose of this study was to detail and assess the creation of a privileging process for this group of medical professionals within an academic medical center. Obtaining the designation of limited oncology practice provider (LOPP) gives the right to modify chemotherapy orders and to order supportive care medications. Methods An interdisciplinary team developed a comprehensive training process inclusive of required educational domains, knowledge goals, and educational activities to become an LOPP. In 2018, five years after the implementation of the privileging process, a survey was distributed to assess perceptions of the training process and integration of LOPPs within oncology practice. Results Most oncologists noted that working with LOPPs is beneficial to oncology practice (94%) and that they make modifying chemotherapy orders more efficient (87%). Greater than 82% of LOPPs also reported that their privileges streamline the chemotherapy process and make them feel valuable. Conclusion The creation of the LOPP designation is an effective way to integrate nurse practitioners, physician assistants, and pharmacists within oncology practice. The inclusion of a focused privileging process ensures the safety of cancer care provided and has created a streamlined process for chemotherapy modifications and supportive care.

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.

scholarly journals Collaborative Comanagement Between Neurohospitalists and Internal Medicine Hospitalists Decreases Provider Costs and Enhances Satisfaction With Neurology Care at an Academic Medical Center

2017 ◽  
Vol 8 (2) ◽  
pp. 74-81
Author(s):  
James G. Greene
Keyword(s):  
Positive Impact ◽  
Medical Center ◽  
Academic Medical Center ◽  
Hospital Medicine ◽  
Professional Services ◽  
Care Model ◽  
Future Health ◽  
Medical Centers ◽  
Academic Medical ◽  
Potential Benefits

Background and Purpose: The majority of academic medical centers are moving to a neurohospitalist model of care for hospital neurology coverage. Potential benefits over a more traditional academic model of patient care include greater expertise in acute neurologic disease, increased efficiency, and improved availability to patients, providers, and learners. Despite these perceived advantages, switching to a neurohospitalist model can come at substantial financial cost, so finding ways to maximize the positive impact of a limited number of neurohospitalists is very important to the future health of academic neurology departments. Over the past 7 years, we have implemented a model for inpatient neurological care based on an intimate collaborative relationship between the neurology and hospital medicine services at our main academic hospital. Our goal was to optimize the value of care by decreasing cost while improving quality. Methods: Cost and revenue associated with professional services was evaluated on a yearly basis. As part of ongoing quality improvement efforts, yearly surveys were administered to referring providers during the transition to a collaborative care model in which NHs and medicine hospitalists comanage neurology inpatients. Results: Net operating loss was dramatically decreased upon transition to the new care model. Concomitantly, there was a robust positive impact on perception of overall quality, timeliness, and communication skills of neurology services. Conclusions: Collaborative comanagement is an effective strategy to improve overall satisfaction with neurology services at a tertiary academic medical center while maintaining financial viability.

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.

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