Objective To develop and obtain expert consensus on a quality evaluation index system for waterless surgical hand antisepsis in operating rooms and to assign hierarchical weights to the finalized indicators. Methods Guided by the Donabedian structure-process-outcome model, candidate indicators were generated through a structured literature review and semi-structured interviews. A three-round expert consultation was conducted: Rounds 1 and 2 were used to screen and refine indicators, and Round 3 was used for AHP-based pairwise weighting. Twenty-two eligible experts received the Round-1 questionnaire; 20 returned valid questionnaires and constituted the panel retained for Rounds 2 and 3, in which all 20 responded. Expert authority was assessed using Cr = (Ca + Cs)/2. In Round 3, individual expert authority coefficients were normalized to obtain expert-specific weights, and pairwise judgments were aggregated using a weighted geometric mean before AHP weight calculation and consistency testing. Results The valid response rates were 90.9% (20/22), 100% (20/20), and 100% (20/20) in Rounds 1, 2, and 3, respectively. The panel mean expert authority coefficients (Cr) were 0.883, 0.895, and 0.900. Kendall's coefficients of concordance for the two indicator-screening rounds were 0.242 and 0.334, respectively (both P < 0.001), while coefficients of variation decreased from 0.07-0.20 to 0.05-0.18. The aggregated AHP group judgment matrices satisfied the predefined consistency criterion (CR < 0.10). The final system comprised three first-level, nine second-level, and 28 third-level indicators. The global weights of the first-level domains were structure 0.1762, process 0.4123, and outcome 0.4115. Conclusion This study produced a consensus-based and hierarchically weighted quality evaluation index system for waterless surgical hand antisepsis. The framework may support standardized quality assessment and future quality-improvement work; however, the present study establishes expert consensus and relative priorities rather than clinical effectiveness, psychometric reliability, or causal effects. Multicenter clinical validation is required before broad implementation.
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Yang et al. (2026) studied this question.
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