Background The use of drug utilization management techniques such as formulary exclusions, prior authorizations, and step edits has risen sharply during the last decade, contributing to growing administrative costs for physician practices. However, limited data exist on the extent of these administrative costs, with previous studies relying on data from over a decade ago. Objective The aim of this study was to assess physician and practice administrator experiences with drug utilization management. Methods A national survey was conducted between 9 February and 30 March 2021, targeting 925 physicians and administrators working at medical practices in the US. Time spent by physicians and their staff on tasks related to drug utilization management for prescription medications was collected and used to calculate the dollar value of that time. Results We estimated that physicians spent a median of 4.0 h per week on drug utilization management, while nurses spent 15.0 h and other staff spent between 3.6 and 10.0 h on drug utilization management per physician per week. This time was associated with a calculated median dollar value of $75,927 per physician per year. Extrapolating this estimate to a national scale suggests that time spent annually by physician practices on drug utilization management could be valued at more than $43 billion. Conclusions Drug utilization management results in significant time spent by US physician practices, which in turn, results in meaningful costs to these practices. As the prevalence of drug utilization management continues to grow, the impact on physician practices will remain an important topic. Supplementary Information The online version contains supplementary material available at 10.1007/s41669-022-00351-5.

416 Background: Patients with cancer can experience disease- and treatment-related symptoms that are underreported and underestimated by physicians. This observational, non-interventional study evaluated the use of ePROs and their impact on duration of treatment (DoT) in patients with solid tumors receiving IO therapy in community practice. Methods: Patients initiating index IO therapy immediately prior to (Jan-2017 to Dec-2018) and after (Sep-2019 to Dec-2020) implementation of Noona, the ePRO platform at Tennessee Oncology clinics, were included in a retrospective historical control (HC) and ePRO cohort, respectively, and followed for up to 6 months. The ePRO cohort was further divided into ePRO users (platform enrollment ≤45 days from index) and non-users. ePRO questionnaires, based on Common Terminology Criteria for Adverse Events (CTCAE), were sent within a week after each IO infusion and could be completed using an internet browser or smartphone app. Patient characteristics and DoT were described and compared between the HC and ePRO cohorts and between the HC cohort and ePRO users subgroup. Use of ePROs was evaluated within the ePRO cohort. Differences in baseline characteristics between cohorts were adjusted using Cox proportional hazards models. Results: Data were collected for 538 HC and 1014 ePRO patients (319 ePRO users and 695 non-users). Patient characteristics were generally similar between cohorts, but more HC patients were diagnosed with Stage IV disease (54% vs 47%; p < 0.01) and initiated IO as monotherapy (82% vs 52%), while more ePRO patients initiated IO as combination therapy (48% vs 18%). ePRO users were more likely than non-users to be female, white, married, living with a spouse, and have higher education (college or graduate degree) (all p < 0.05). Use of ePROs was durable over follow-up, with a consistent number of questionnaires sent over Months 1-3 and Months 4-6 (median: 6 questionnaires in each period) and a slight decrease in the number answered (median: 4 vs 3 questionnaires). ePRO patients had a longer DoT than HC patients (median time to end of first IO regimen: not estimable vs 5.1 months). Significantly more ePRO than HC patients remained on their first IO regimen at 6 months (54% vs 46%; p < 0.05). Multivariate Cox regression showed the risk of ending first IO therapy was lower for ePRO versus HC patients (p < 0.05). Conclusions: The increased DoT observed in the ePRO versus HC cohort in this study suggests that use of ePROs may facilitate improved care coordination and enable patients to remain on IO therapy longer. However, ePRO uptake was only 31% in the ePRO cohort, with several social determinants appearing to influence use. Overcoming barriers in ePRO uptake is an area for future study.

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Hospitalized spineinfection patients with a DM diagnosis increased 6%, while discharges with other associated comorbidities decreased. In the group of patients with spine infection and those with DM, the ratio of male/female patients, patient-age distribution, and payer mixes were similar. This was not present for the other comorbidity groups. Conclusions: The frequency of U.S. hospitalizations for spine infection increased between 2006 and 2014. The associated volume of Medicare and Medicaid patients increased and fewer patients were commercially insured, with consistent corresponding changes in aggregate HCUPnet calculated payer costs. The increase in spine infections appeared to parallel the increase in hospitalization for diabetes mellitus, a recognized comorbidity associated with infection. Assessing correlations between spine infection and comorbidities requires further study, along with estimating the economic burden of these patients.

Introduction: The evolving treatment landscape for non-small-cell lung cancer (NSCLC) and complexities of regulations and reimbursement present challenges to community oncologists. Clinical pathways are tools to optimize care, but information on their value in the real world is limited. This retrospective study assessed treatment patterns and clinical outcomes in patients with Stage I–III NSCLC pre- and post-pathways implementation at Tennessee Oncology, a large, community-based oncology practice in the USA. Methods & Materials: Chart data were abstracted for adults diagnosed with Stage I–III NSCLC who received systemic treatment. Patients were divided into pre-pathways (treatment initiation 2014–2015) and post-pathways (treatment initiation 2016–2018) cohorts. Patient characteristics, treatment patterns and outcomes were summarized descriptively. Kaplan–Meier curves were used to assess time-dependent outcomes, and log-rank test was used to compare the cohorts. Results: 291 patients were included (Stage I–II: 38 pre-pathways, 55 post-pathways; Stage III: 105 pre-pathways, 93 post-pathways). Duration on first-line (1L) therapy was similar for Stage I–II patients pre- and post-pathways (median 1.9 months vs 2.1 months; p = 0.75), but increased for Stage III patients post-pathways (2.1 months vs 1.4 months pre-pathways; p < 0.01). Achievement of a complete or partial response with 1L therapy was similar post-pathways among Stage I–Stage –IIII patients (60.0% vs 55.2% pre-pathways), but increased for Stage III patients (56.0% vs 35.2% pre-pathways). Conclusion: Given that improvements in rates of treatment response post-pathways occurred only for patients diagnosed with Stage III NSCLC, among whom immunotherapy uptake increased post-pathways, such improvements may be attributable to evolving practices in cancer care, including advances in treatment and care delivery, rather than clinical pathways implementation. Further research is warranted to assess the impact of clinical pathways in the current treatment era, given that immunotherapy has now become the standard of care in NSCLC.