Gurjar Mruga, Lindberg Jesper, Björk-Eriksson Thomas, Olsson Caroline
Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sweden.
Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden.
Tech Innov Patient Support Radiat Oncol. 2022 Dec 20;25:100194. doi: 10.1016/j.tipsro.2022.12.001. eCollection 2023 Mar.
Oncological Information Systems (OIS) manage information in radiotherapy (RT) departments. Due to database structure limitations, stored information can rarely be directly used except for vendor-specific purposes. Our aim is to enable the use of such data in various external applications by creating a tool for automatic data extraction, cleaning and formatting.
We used OIS data from a nine-linac RT department in Sweden (70 weeks, 2015-16). Extracted data included patients' referrals and appointments with details for RT sub-tasks. The data extraction tool to prepare the data for external use was built in C# programming language. It used excel-automation queries to remove unassigned/duplicated values, substitute missing data and perform application-specific calculations. Descriptive statistics were used to verify the output with the manually prepared dataset from the corresponding time period.
From the initial raw data, 2030 (51 %)/907 (23 %) patients had known curative and palliative treatment intent for 84 different cancer diagnoses. After removal of incomplete entries, 373 (10 %) patients had unknown treatment intents which were substituted based on the known curative/palliative ratio. Automatically- and manuallyprepared datasets differed < 1 % for Mould, Treatment planning, Quality assurance and ± 5 % for Fractions and Magnetic resonance imaging with overestimations in 80/140 (57 %) entries by the tool.
We successfully implemented a software tool to prepare ready-to-use OIS datasets for external applications. Our evaluations showed overall results close to the manually-prepared dataset. The time taken to prepare the dataset using our automated strategy can reduce the time for manual preparation from weeks to seconds.
肿瘤学信息系统（OIS）管理放射治疗（RT）科室的信息。由于数据库结构的限制，除了特定供应商的用途外，存储的信息很少能直接使用。我们的目标是通过创建一个自动数据提取、清理和格式化工具，使这些数据能够在各种外部应用中使用。
我们使用了瑞典一个拥有九条直线加速器的RT科室在2015 - 2016年70周期间的OIS数据。提取的数据包括患者的转诊和预约以及RT子任务的详细信息。用于为外部使用准备数据的数据提取工具是用C#编程语言构建的。它使用Excel自动化查询来去除未分配/重复的值、替代缺失数据并进行特定应用的计算。使用描述性统计来将输出结果与相应时间段手动准备的数据集进行验证。
从初始原始数据来看，2030名（51%）/907名（23%）患者针对84种不同癌症诊断有已知的根治性和姑息性治疗意图。去除不完整记录后，373名（10%）患者的治疗意图不明，这些意图根据已知的根治性/姑息性比例进行了替代。对于模体、治疗计划、质量保证，自动准备和手动准备的数据集差异小于±1%，对于分次治疗和磁共振成像，差异为±5%，该工具在80/140（57%）的记录中存在高估。
我们成功实施了一个软件工具，为外部应用准备随时可用的OIS数据集。我们的评估显示总体结果与手动准备的数据集相近。使用我们的自动化策略准备数据集所花费的时间可以将手动准备时间从数周减少到数秒。
