5 Background: The Oncology Care Model (OCM) is a Medicare value-based care program, that rewards practices for decreasing the total cost of care (TCOC) compared to a benchmark price. Enrolled patients are evaluated in 6-month episodes within a 1-year time window called Performance Periods (PP). The use of lower cost medication alternatives (LCA) is a critical strategy to bend the cost curve. Therapeutic interchange (TIC) with lower-cost generic/biosimilar/therapeutic alternative medications offer significant cost savings to payers and patients while maintaining equivalent quality of care. LCA for eight high-cost oncology therapeutic or supportive care medications became available during or just prior to OCM. The results of a clinically appropriate, physician-supported, pharmacist-led interchange of high-cost medications to LCA in The US Oncology Network (The Network) during OCM PP 7 (PP7), 8 (PP8), and 9 (PP9) is described here. Methods: Medicare Part B & D claims for 14 OCM practices in The Network were used to evaluate the impact of eight TIC opportunities during PP 7-9. TIC opportunities included changing therapy from reference products to biosimilars (bevacizumab, trastuzumab, rituximab, pegfilgrastim and filgrastim), from brand to generics (abiraterone, imatinib, fosaprepitant) and from high cost to LCA (aprepitant to fosaprepitant, denosumab to zoledronic acid). TCOC impact was measured by comparing the cost of each dose of the LCA vs the estimated cost if the more expensive alternative had been used instead. Results: The shift from high cost to LCAs in PP7, PP8 and PP9 is shown in Table as percentage of total doses dispensed or administered. Transitions from aprepitant to fosaprepitant, and from denosumab to zoledronic acid was done when clinically appropriate (as determined by the treating physician). The cumulative savings from TIC was $26.0M in PP7, $32.3M in PP8 and $32.9M in PP9. TIC to biosimilars contributed $6.6M in PP8 and $12.2M in PP9 of the cumulative savings. TIC reduced TCOC by 2.78% in PP7, 4.13% in PP8, 5.25% in PP9 within the OCM. Conclusions: TIC to biosimilars, generics and clinically appropriate LCA is an effective way to reduce TCOC while maintaining quality care in the OCM. Even small shifts in utilization towards LCA can generate a significant reduction in TCOC. Physician-supported, pharmacist-led TIC initiatives are critical to bending the cost curve within Oncology.[Table: see text]

e18747 Background: The COVID-19 pandemic had a profound impact on cancer care delivery throughout the nation. Data regarding the outcomes of patients on cancer therapy who had COVID-19 is lacking. The US Oncology Network had 14 practices participating in the Oncology Care Model (OCM) during performance period 8 (PP8) which enrolled patients from 1/2/2020 to 7/1/2020. OCM enrolls patients with Medicare undergoing treatment for a cancer diagnosis. Utilizing OCM claims files, we evaluated the impact of COVID-19 on outcomes and costs for patients enrolled in the OCM during the first stages of the pandemic. Methods: Utilizing claims and episode data from the OCM, we were able to identify episodes with patients who had a positive COVID-19 diagnosis. Episodes were flagged with COVID-19 based on the ICD-10 code U07.1 on claims files. We were then able to compare the total cost of care (TCOC), inpatient costs and death rate to those patients in the OCM that did not have a COVID-19 ICD-10 claim. Results: 2.5% of patient episodes in PP8 had a positive COVID-19 ICD-10 claim. TCOC per episode increased 36% per patient from $34,340 for those without COVID-19 to $53,605 for those with COVID-19, a difference of $19,265 per patient. Inpatient costs increased from $3,276 for those without COVID-19 to $12,226 for those with a COVID-19 diagnosis. 8.9% of patients without a COVID-19 diagnosis died during the episode vs 20.0% of those with a COVID-19 diagnosis. Other costs including the cost of drugs did not significantly differ between the two groups. Conclusions: A diagnosis of COVID-19 for patients in the OCM receiving cancer treatment during PP8 led to a significant increase in costs, especially the costs of hospitalization. The death rate more than doubled for patients with COVID-19 during an OCM episode. Patients with Medicare and cancer undergoing treatment were at high-risk for complications and death from COVID-19 during OCM performance period 8.

6636 Background: Febrile neutropenia (FN) resulting from myelosuppressive chemotherapy can lead to increased hospitalizations and mortality. Pegfilgrastim can be used to reduce the risk of FN; however, few studies address pegfilgrastim’s value in patients with metastatic solid tumors. This observational study compared outcomes for pegfilgrastim-treated (peg-tx) and peg-untreated (no peg) patients with metastatic colorectal (CRC) at US Oncology practices (USO) participating in the Oncology Care Model. Methods: Patients with metastatic CRC treated at USO from July 1, 2013 – December 31, 2014 and a qualifying baseline OCM episode were included. Propensity scoring was used to match (1:2) peg-tx and no peg cohorts based on line of therapy, number of comorbidities, age, gender, ECOG performance status, chemotherapy neutropenic fever risk, and dose reduction. Outcomes assessed included all-cause and infection-related hospitalization rates; total cost of care per 6-month OCM episode; and overall survival (OS). Results: Matched peg-tx and no peg samples were 149:298. The all-cause hospitalization rate was higher in the peg-tx vs. no peg population, 45% vs. 32% (OR 1.7, (1.1, 2.5), p = 0.011). Infection-related hospitalization rates were no different in peg-tx vs. no peg cohorts, p = 0.367. Cost of care was significantly higher for peg-tx patients vs. no peg ($58,787 ± $20,490 vs. $37,811 ± $19,593 respectively, p < .001). OS was 19.5 months (peg-tx) vs. 19.7 months (no peg), p = 0.882. Conclusions: While peg use in curative treatment settings for high risk patients is standard of care, in our Medicare population use in metastatic CRC did not result in a lower all-cause or infection-related hospitalization rate or impact in OS. There was a higher 6-month total cost of care associated with those patients who received peg during chemotherapy.

66 Background: The Oncology Care Model (OCM) is a 6-month, episode-based, Medicare value-based care program, which rewards practices for decreasing the total cost of care (TCOC) compared to a trend adjusted predicted baseline called the benchmark price. The predicted baseline and trend factor are a function of 14 covariates in a generalized linear model with a log link and gamma distribution. Select non-cancer comorbidities, represented by a subset of Hierarchical Condition Category (HCC) flags assigned to the episode in the calendar year when the episode initiates, is a major covariate of the linear model. Patient episodes with one or more HCC flags are expected to have higher episode expenditures and receive a higher adjustment to the benchmark. Here, we seek to describe the seasonality of HCC flags and its impact on the benchmark for OCM episodes in The US Oncology Network (The Network). Methods: All eligible OCM episodes data from 14 practices in The Network participating in the OCM for performance periods (PP) 3-9 were analyzed to measure the average number of HCC flags per episode. The relative contribution of HCC flags to the benchmark was calculated by unraveling the linear model. The difference of the average HCC flags, benchmark, and relative contribution of HCC flags to the benchmark for episodes starting in different quarters of the calendar year were evaluated. Results: Average HCC flags for episodes showed a seasonal decline during each calendar year, with episodes initiating during the first quarter of a calendar year having 16.25% higher HCC flags, compared to those in the last quarter (1.93 vs 1.66 flags). The benchmark and the relative contribution of the HCC flags to the episode benchmark were lower in the last quarter of the year (4% and 16.5% respectively) compared to the first quarter. Episode expenditures did not show a similar seasonality pattern. Conclusions: The assignment of HCC flags based on the episode initiation date, leads to a seasonality effect on the average HCC flags and benchmark for episodes initiating in different parts of the calendar year. The seasonality results from a progressively abbreviated period available to assign HCC flags for episodes initiating later in the calendar year. We also hypothesize that the annual reporting requirement for HCC flags, and risk adjustment coding by professionals at the start of each new calendar year, contributes to this seasonality. The financial impact of seasonality on episodic value-based care model benchmarks necessitates a modified, non-seasonal approach to comorbidity-based risk adjustment.

e17019 Background: Therapeutic interchange (TIC) to lower-cost generic products offers significant cost savings to payers and patients while maintaining equivalent quality of care. The Oncology Care Model (OCM) is a value-based care program from Medicare that rewards practices for decreasing the total cost of care (TCOC) compared to historical baseline prices that are adjusted by a trend factor to account for rising cost trends in oncology. One strategy for bending the cost curve is to utilize lower cost medications. A generic version of abiraterone acetate (FDA approved for treatment of Prostate Cancer) was first introduced into the market in late 2018. This led to a concerted approach to interchange the brand product with the generic equivalent in The US Oncology Network (The Network) as an opportunity to reduce TCOC. Here we describe utilization and the financial impact of abiraterone TIC in The Network during OCM performance period 8 (PP8) which enrolled patients from 1/2/2020 to 7/1/2020. Methods: Prescription drugs dispense data for the 14 US Oncology Network practices participating in the OCM were used to determine brand and generic abiraterone utilization. The impact of TIC on TCOC was measured by comparing the cost of the generic product vs. the estimated cost of the brand agents. Results: TIC resulted in an increase in generic abiraterone use from prior performance periods. Generic abiraterone increased from 0% in PP4 to 24% in PP5, 55% in PP6, 67% in PP7 and 80% in PP8 within the Network. We compared the actual cost of all abiraterone dispenses in PP8 vs. the calculated cost (based on Average Wholesale Price less 17.5%) of the brand product if the more expensive brand drugs were used instead. The difference in the actual cost vs estimated cost led to a savings of $4.37 million in PP6, $6.34 million in PP7 and $9.37 million in PP8 (about 1% of TCOC) by using generic versus brand abiraterone alone. Conclusions: TIC from brand to generic abiraterone in The Network generated significant savings for OCM. Continued shift towards lower cost generics will increase savings to CMS in the Oncology Care Model. We estimate that 100% Network adoption of the generic abiraterone could save nearly 1.25% of the TCOC compared to continued use of brand product.