Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2022
Automated planning stage tracking and analysis through an integrated whiteboard system.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
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Kalet Alan M, Kim Minsun, Hendrickson Kristi R G, Cao Ning, Young Lori, Fang Christine L, Kim Janice, Landers Angelia, Lavilla Myra A, Meyer Juergen
Аннотация
PURPOSE: One of the common challenges in delivering complex healthcare procedures such as radiation oncology is the organization and sharing of information in ways that facilitate workflow and prevent treatment delays. Within the major vendors of Oncology Information Systems (OIS) is a lack of tools and displays to assist in task timing and workflow processes. To address this issue, we developed an electronic whiteboard integrated with a local OIS to track, record, and evaluate time frames associated with clinical radiation oncology treatment planning processes.
METHODS: We developed software using an R environment hosted on a local web-server at Seattle Cancer Care Alliance (SCCA) in 2017. The planning process was divided into stages, and time-stamped moves between planning stages were recorded automatically via Mosaiq (Elekta, Sweden) Quality Check Lists (QCLs). Whiteboard logs were merged with Mosaiq-extracted diagnostic factors and evaluated for significance. Interventional changes to task time expectations were evaluated for 6 months in 2021 and compared with 6 month periods in 2018 and 2019.
RESULTS: Whiteboard/Mosaiq data from the SCCA show that treatment intent, number of prescriptions, and nodal involvement were main factors influencing overall time to plan completion. Contouring and Planning times were improved by 2.6 days (p<10-14) and 2.5 days (p<10-11), respectively. Overall time to plan completion was reduced by 33% (5.1 days; p<10-11).
CONCLUSIONS: This report establishes the utility of real-time task tracking tools in a radiotherapy planning process. The whiteboard results provide data-driven evidence to add justification for practice change implementations.
METHODS: We developed software using an R environment hosted on a local web-server at Seattle Cancer Care Alliance (SCCA) in 2017. The planning process was divided into stages, and time-stamped moves between planning stages were recorded automatically via Mosaiq (Elekta, Sweden) Quality Check Lists (QCLs). Whiteboard logs were merged with Mosaiq-extracted diagnostic factors and evaluated for significance. Interventional changes to task time expectations were evaluated for 6 months in 2021 and compared with 6 month periods in 2018 and 2019.
RESULTS: Whiteboard/Mosaiq data from the SCCA show that treatment intent, number of prescriptions, and nodal involvement were main factors influencing overall time to plan completion. Contouring and Planning times were improved by 2.6 days (p<10-14) and 2.5 days (p<10-11), respectively. Overall time to plan completion was reduced by 33% (5.1 days; p<10-11).
CONCLUSIONS: This report establishes the utility of real-time task tracking tools in a radiotherapy planning process. The whiteboard results provide data-driven evidence to add justification for practice change implementations.