Development of a Nursing Quality Evaluation Indicator System for Lung Cancer in Traditional Chinese Medicine Based on...

Currently, no unified quality evaluation standard exists specifically for Traditional Chinese Medicine (TCM) nursing in lung cancer in China, and existing indicators do not capture TCM's unique features. To address this gap, we aimed to construct a preliminary scientific and disease specific quality evaluation framework for Traditional Chinese Medicine (TCM) nursing in lung cancer patients based on expert consensus, which can serve as a theoretical foundation for standardized management and future empirical validation.

Guided by Donabedian's structure process outcome model, we developed an initial indicator pool through a systematic literature review and semi structured interviews. A three round Delphi consultation was conducted with 17 national experts. Indicators were screened using importance/feasibility scores, coefficients of variation, and full-score rates. An analytic hierarchy process (AHP) was used to assign weights. No clinical validation has been performed at this stage.

All three rounds achieved a response rate of 100%. The expert authority coefficients increased from 0.853 to 0.894, and Kendall's W reached 0.304 (all P < 0.01). The final framework comprised three primary, 17 secondary, and 45 tertiary indicators, with coefficients of variation <0.25 and consistency ratios <0.10. The three primary domains were structure (focusing on staffing, training, and systems), process (emphasizing symptom management, TCM techniques, and safety), and outcome (covering symptom control and TCM syndrome improvement).

We developed a consensus‑based quality evaluation framework for TCM nursing in lung cancer that demonstrated good content validity and expert agreement. However, these findings are based solely on expert opinion; their predictive validity, clinical feasibility, and impact on patient outcomes require prospective multicenter validation before they can be recommended for routine practice. This framework provides a theoretical reference for future studies.