Sánchez Juan C, Nuñez-García Beatriz, Garitaonaindia Yago, Calvo Virginia, Blanco Mariola, Ramos Martín-Vegue Arturo, Royuela Ana, Manso Marta, Cantos Blanca, Méndez Miriam, Collazo-Lorduy Ana, Provencio Mariano
Medical Oncology Department, Puerta de Hierro-Majadahonda University Hospital, C. Joaquín Rodrigo, 1, Majadahonda, 28222, Madrid, Spain.
Admission and Clinical Documentation Department, Puerta de Hierro-Majadahonda University Hospital, Madrid, Spain.
Clin Transl Oncol. 2025 Mar;27(3):1047-1061. doi: 10.1007/s12094-024-03658-3. Epub 2024 Aug 16.
The complexity of cancer care requires planning and analysis to achieve the highest level of quality. We aim to measure the quality of care provided to patients with non-small cell lung cancer (NSCLC) using the data contained in the hospital's information systems, in order to establish a system of continuous quality improvement.
METHODS/PATIENTS: Retrospective observational cohort study conducted in a university hospital in Spain, consecutively including all patients with NSCLC treated between 2016 and 2020. A total of 34 quality indicators were selected based on a literature review and clinical practice guideline recommendations, covering care processes, timeliness, and outcomes. Applying data science methods, an analysis algorithm, based on clinical guideline recommendations, was set up to integrate activity and administrative data extracted from the Electronic Patient Record along with clinical data from a lung cancer registry.
Through data generated in routine practice, it has been feasible to reconstruct the therapeutic trajectory and automatically calculate quality indicators using an algorithm based on clinical practice guidelines. Process indicators revealed high adherence to guideline recommendations, and outcome indicators showed favorable survival rates compared to previous data.
Our study proposes a methodology to take advantage of the data contained in hospital information sources, allowing feedback and repeated measurement over time, developing a tool to understand quality metrics in accordance with evidence-based recommendations, ultimately seeking a system of continuous improvement of the quality of health care.
癌症护理的复杂性需要进行规划和分析，以实现最高水平的质量。我们旨在利用医院信息系统中包含的数据来衡量为非小细胞肺癌（NSCLC）患者提供的护理质量，以便建立一个持续质量改进系统。
方法/患者：在西班牙一家大学医院进行的回顾性观察队列研究，连续纳入2016年至2020年间接受治疗的所有NSCLC患者。基于文献综述和临床实践指南建议，共选择了34个质量指标，涵盖护理流程、及时性和结果。应用数据科学方法，建立了一种基于临床指南建议的分析算法，以整合从电子病历中提取的活动和管理数据以及来自肺癌登记处的临床数据。
通过常规实践中产生的数据，利用基于临床实践指南的算法重建治疗轨迹并自动计算质量指标是可行的。流程指标显示对指南建议的高度依从性，结果指标显示与先前数据相比生存率良好。
我们的研究提出了一种利用医院信息源中包含的数据的方法，允许随着时间的推移进行反馈和重复测量，开发一种根据循证建议理解质量指标的工具，最终寻求一个医疗保健质量持续改进的系统。
