Observational studyClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2025
Quality of care assessment for non-small cell lung cancer patients: transforming routine care data into a continuous improvement system.
Observational study in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Lactate metabolism and protein lactylation in programmed cell death: From novel mechanism to therapeutic strategies in human diseases.Clinical and translational medicine · 2026Review
- Unexpected Long-Term Survival and Downstaging in Oligometastatic Non-Small Cell Lung Cancer Treated with Multimodal Therapy.Journal of clinical medicine · 2025Article
Corrections and comments
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Authors and funding
12 authors.
Funding
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Abstract
purposeThe 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.
resultsThrough 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.
conclusionsOur 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.
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