Hematologic Malignancy Episodes Exceed Target Price in Oncology Care Model.

The current study evaluated whether total cost of care (TCOC) and target price were aligned in Oncology Care Model (OCM) hematologic malignancy episodes and identified factors associated with episodes exceeding target price. Hematologic malignancy episodes from OCM performance period 1-4 reconciliation reports were identified from a large academic medical center. Of the 516 hematologic malignancies episodes included in the analysis, 283 (54.8%) exceeded the target price. Episode characteristics found to be statistically significantly associated with exceeding target price were Medicare Part B drug use and Part D drug use, novel therapy use, home health agency, and >730 days from last chemotherapy. The mean TCOC was $85 374 (± $26 342) for the episodes that exceeded target price while the mean target price was $56 106 (±$16 309). The results found a substantial misalignment between the TCOC and target price for hematologic malignancy episodes, adding to the existing evidence on the lack of adequate adjustment to the OCM target price.

COVID-19 Pandemic Influence on Medical Oncology Provider Perceptions of Telehealth Video Visits.

PURPOSE: The COVID-19 pandemic necessitated a rapid expansion of telehealth use in oncology, a specialty in which prior utilization was low in part because of barriers perceived by providers. Understanding the changing perceptions of medical oncology providers during the pandemic is critical for continued expansion and improvement of telehealth in cancer care. This study was designed to identify medical oncology providers' perceptions of telehealth video visits as influenced by the COVID-19 pandemic. METHODS: We conducted semi-structured interviews with medical oncology providers from November 20, 2020, to January 27, 2021, at the Sidney Kimmel Cancer Center at Thomas Jefferson University, a National Cancer Institute-designated cancer center in an urban, academic health system in Philadelphia, PA. We assessed provider perceptions of the impact of the COVID-19 pandemic on (1) provider-level comfort and willingness for telehealth, (2) provider-perceived patient comfort and willingness to engage in telehealth, and (3) continued barriers to successful telehealth use. RESULTS: Volunteer and convenience sampling resulted in the participation of 25 medical oncology providers, including 18 physicians and seven advanced practice providers, in semi-structured interviews. Of the 25 participants, 13 (52%) were female and 19 (76%) were White, with an average age of 48.5 years (standard deviation = 12.6). Respondents largely stated an increased comfort level and willingness for use of video visits. In addition, respondents perceived a positive change in patient comfort and willingness, mostly driven by convenience, accessibility, and reduced risk of COVID-19 exposure. However, several reported technologic issues and limited physical examination capability as remaining barriers to telehealth adoption. CONCLUSION: The rapid adoption of telehealth necessitated by the COVID-19 pandemic has increased provider-level and provider-perceived patient comfort and willingness to engage in video visits for cancer care. As both providers and patients increasingly accept telehealth across many use cases, future work should focus on further addressing technology and physical examination barriers and ensuring continued reimbursement for telehealth as a routine part of covered care.

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

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.

Development of an Oncology Acute Care Risk Prediction Model.

PURPOSE: Acute care utilization (ACU), including emergency department (ED) visits or hospital admissions, is common in patients with cancer and may be preventable. The Center for Medicare & Medicaid Services recently implemented OP-35, a measure in the Hospital Outpatient Quality Reporting Program focused on ED visits and inpatient admissions for 10 potentially preventable conditions that arise within 30 days of chemotherapy. This new measure exemplifies a growing focus on preventing unnecessary ACU. However, identifying patients at high risk of ACU remains a challenge. We developed a real-time clinical prediction model using a discrete point allocation system to assess risk for ACU in patients with active cancer. METHODS: We performed a retrospective cohort analysis of patients with active cancer from a large urban academic medical center. The primary outcome, ACU, was evaluated using a multivariate logistic regression model with backward variable selection. We used estimates from the multivariate logistic model to construct a risk index using a discrete point allocation system. RESULTS: Eight thousand two hundred forty-six patients were included in the analysis. ED utilization in the last 90 days, history of chronic obstructive pulmonary disease, congestive heart failure or renal failure, and low hemoglobin and low neutrophil count significantly increased risk for ACU. The model produced an overall C-statistic of 0.726. Patients defined as high risk (achieving a score of 2 or higher on the risk index) represented 10% of total patients and 46% of ACU. CONCLUSION: We developed an oncology acute care risk prediction model using a risk index-based scoring system, the REDUCE (Reducing ED Utilization in the Cancer Experience) score. Further efforts to evaluate the effectiveness of our model in predicting ACU are ongoing.