부산대학교 도서관

Purpose/objective(s): Access to radiation treatment is inequitable, limited by shortages in technology and training in low-to-middle income countries (LMIC). Automated treatment planning software may ease this inequity. The Radiation Planning Assistant (RPA) is an automated treatment-planning tool designed for limited resource environments. In anticipation of deployment, understanding barriers and facilitators of implementing RPA in LMIC is critical to optimizing its value. We conducted a survey to elucidate radiation oncology provider attitudes, needs, barriers, and facilitators of RPA deployment and uptake in LMIC clinical settings.Materials/methods: Providers in three countries expressing interest in piloting RPA were approached for survey participation, with 100% response. Providers received an initial 1-hour remote, live videoconference learning session supported by interactive learning using breast and head and neck cancer dummy radiation plans. Providers were surveyed using a validated measure of acceptability (score range from 0, least, to 60, most acceptable) and yes/no questions to assess barriers to and facilitators of implementation of RPA, and user experience. Acceptability scores were compared using one-way ANOVA test. Facilitators and barriers to RPA uptake were analyzed by Fisher's exact test.Results: Across 25 providers in five institutions in South Africa (n = 13), Tanzania (n = 1), Guatemala (n = 12), respondents were most frequently between 31-50 years old (72%) and in practice > 5 years (68%). Respondent roles included physician (32%), dosimetry (24%), physicist (32%), resident/registrar (4%), radiation therapist (4%), and administrator (4%). Most respondents agreed that RPA could be used in their practice either now (64% agree or completely agree) or in 2 years (64%), and indicated a high interest level in RPA (88% agree or completely agree). There was no significant difference in mean acceptability score by role (P = 0.21). However, among the subset of respondents in South Africa, dosimetrists rated RPA as significantly less acceptable (P = 0.0112, mean score 33.5) as compared to physicians (mean 48), physicists (mean 51.8), and resident/registrar (mean 60). The most frequently anticipated benefits of RPA were decreased workload (80%), decreased planning time (72%), and the ability to treat more patients (64%). Many respondents also anticipated RPA would help transition from 2D to 3D treatment planning (44%) or 3D to IMRT (48%). Barriers to implementation were lack of reliable internet (80%), potential subscription fees (60%), and need for functionality in additional disease sites (48%).Conclusion: This survey of international respondents indicated considerable interest in the RPA in LMIC settings. Implementation must be tailored to variations in perceived benefits and barriers may vary by provider role, practice location, and infrastructural resources.