Engstrom Teyl, Kenny Danelle, Grimmett Wallace, Ramis Mary-Anne, Foley Chris, Sullivan Clair, Pole Jason D
The University of Queensland, Australia.
Mater Health, Australia.
Health Inf Manag. 2025 Sep;54(3):247-254. doi: 10.1177/18333583241299433. Epub 2024 Nov 23.
Advances in technology have increased the ease of reporting hospital incidents, resulting in large amounts of qualitative descriptive data. Health services have little experience analysing these data at scale to incorporate into routine reporting.
We aimed to explore the feasibility of applying a semi-automated content analysis (SACA) tool (Leximancer™) to qualitative descriptions of system-wide hospital incidents to provide insights into safety issues at all health service levels.
Data from 1245 incidents reported across a network of hospitals in Australia were analysed using the SACA tool. Summaries were generated using a variety of techniques, including inductive and deductive approaches to extract key concepts in the data.
The analysis was feasible and provided an actionable summary of the types of incidents reported in the data; the visual interface allowed users to explore the underlying text for a deeper understanding. Deductive analysis was utilised to explore specific areas of interest, and stratified analysis revealed more detailed concepts. The SACA tool was more efficient than manual processes; however, due to the context present in the incident descriptions, significant time, reading and subject matter expertise is still required to refine the analysis.
Semi-automated tools provide an opportunity for improving patient safety culture and practices by providing rapid content analysis of vast datasets that can be customised for specific organisational contexts and deployed at scale. Further research is required to assess usefulness with system users.
Qualitative data abound and system-wide analysis is essential to creating actionable insights.
技术进步提高了医院事件报告的便捷性，产生了大量定性描述数据。卫生服务机构在大规模分析这些数据以纳入常规报告方面经验甚少。
我们旨在探讨应用半自动内容分析（SACA）工具（Leximancer™）对全系统医院事件的定性描述进行分析的可行性，以深入了解各级卫生服务机构的安全问题。
使用SACA工具对澳大利亚一个医院网络报告的1245起事件的数据进行分析。采用多种技术生成摘要，包括归纳法和演绎法来提取数据中的关键概念。
该分析是可行的，并提供了数据中所报告事件类型的可操作摘要；可视化界面使用户能够探究基础文本以加深理解。利用演绎分析来探究特定感兴趣领域，分层分析揭示了更详细的概念。SACA工具比人工流程更高效；然而，由于事件描述中存在的背景信息，仍需要大量时间、阅读和专业知识来完善分析。
半自动工具通过对大量数据集进行快速内容分析提供了改善患者安全文化和实践的机会，这些分析可针对特定组织背景进行定制并大规模部署。需要进一步研究以评估其对系统用户的有用性。
定性数据丰富，全系统分析对于产生可操作的见解至关重要。
