Estimating the Practice-Level and National Cost Burden of Treatment-Related Prior Authorization for Academic Radiation Oncology Practices.

PURPOSE: Prior authorization (PA) imposes significant time burdens on radiation oncology practices, but its financial impact has not been characterized. We used time-driven activity-based costing (TDABC) to assess the cost burden of treatment-related PA events at an academic radiation oncology practice. We then estimated annual costs for an academic practice and academic practices nationally. METHODS AND MATERIALS: Using internal analyses, we created TDABC process maps for treatment-related PA events at an academic radiation oncology practice. Using published compensation data, internal workhour estimates, and supervisory requirements, we calculated the cost of each PA event and annual costs. Using data from the 2017 American Society for Radiation Oncology Workforce Survey and the 2018 American Society for Radiation Oncology Prior Authorization Survey, we estimated annual PA costs for academic medical centers nationally. RESULTS: We successfully created TDABC process maps for treatment-related PA events at an academic radiation oncology practice. There were significant time and cost burdens for all events (range: 51-95 minutes, $28-$101 US dollars [USD]), with significant increases when peer-to-peer discussion was required (range: 92-95 minutes, $75-$101 USD). Annual treatment-related PA departmental costs were estimated to be $491,989 USD, with approved treatments accounting for the majority (94%; $463,027 USD). Nationally, annual treatment-related PA costs were estimated to be $40,125,848 USD, with approved treatments accounting for the majority (86%; $34,632,620 USD). CONCLUSION: TDABC can be used to estimate the cost burden of PA events. These burdens are significant and translate into massive organizational costs. Our national estimates highlight the tremendous cost of PA for academic radiation oncology practices, with the majority of costs related to approved treatments.

Health Information Technologies in the Support Systems of Pregnant Women and Their Caregivers: Mixed-Methods Study.

BACKGROUND: The quality and quantity of families' support systems during pregnancy can affect maternal and fetal outcomes. The support systems of expecting families can include many elements, such as family members, friends, and work or community groups. Emerging health information technologies (eg, social media, internet websites, and mobile apps) provide new resources for pregnant families to augment their support systems and to fill information gaps. OBJECTIVE: This study sought to determine the number and nature of the components of the support systems of pregnant women and their caregivers (eg, family members) and the role of health information technologies in these support systems. We examined the differences between pregnant women's support systems and those of their caregivers and the associations between support system composition and stress levels. METHODS: We enrolled pregnant women and caregivers from advanced maternal-fetal and group prenatal care clinics. Participants completed surveys assessing sociodemographic characteristics, health literacy, numeracy, and stress levels and were asked to draw a picture of their support system. Support system elements were extracted from drawings, categorized by type (ie, individual persons, groups, technologies, and other) and summarized for pregnant women and caregivers. Participant characteristics and support system elements were compared using the Pearson chi-square test for categorical variables and Wilcoxon ranked sum test for continuous variables. Associations between support system characteristics and stress levels were measured with Spearman correlation coefficient. RESULTS: The study enrolled 100 participants: 71 pregnant women and 29 caregivers. The support systems of pregnant women were significantly larger than those of caregivers-an average of 7.4 components for pregnant women and 5.4 components for caregivers (P=.003). For all participants, the most commonly reported support system elements were individual persons (408/680, 60.0%), followed by people groups (132/680, 19.4%), technologies (112/680, 16.5%), and other resources (28/680, 4.1%). Pregnant women's and caregivers' technology preferences within their support systems differed-pregnant women more often identified informational websites, apps, and social media as parts of their support systems, whereas caregivers more frequently reported general internet search engines. The size and components of these support systems were not associated with levels of stress. CONCLUSIONS: This study is one of the first demonstrating that technologies comprise a substantial portion of the support systems of pregnant women and their caregivers. Pregnant women more frequently reported specific medical information websites as part of their support system, whereas caregivers more often reported general internet search engines. Although social support is important for maternal and fetal health outcomes, no associations among stress, support system size, and support system components were found in this study. As health information technologies continue to evolve and their adoption increases, their role in patient and caregiver support systems and their effects should be further explored.