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  • Development and application of a real-world-data-based indicator system to evaluate the use of diagnostic large medical equipment

    ObjectivesTo develop a real-world-data-based monitoring system for diagnostic large medical equipment, and to use PET/CT as a carrier for validation. MethodsWe used literature survey, site investigation, and two-rounds of modified Delphi methods to develop the indicator system, and used the analytic hierarchy process method to determine the weight of each indicator. We collected real-world PET/CT data from four tertiary hospitals from July to December 2022, and monitored the use of PET/CT in each hospital. ResultsQuestionnaire recovery rates of 2 rounds were 100% and 88%, respectively, the expert authority coefficient was greater than 0.70, and the coordination coefficients of experts in the total index were 0.307 and 0.471 (P<0.001). A three-level indicator system was established to monitor the use of large medical equipment, with three first-level indicators (clinical use, implementation, and other efficiencies), eight second-level indicators, and 15 third-level indicators. Empirical experiment found different hospitals vary in efficiency (of clinical use), staff status, and economic and research efficiency, while remained similar in other indicators. ConclusionWe developed a monitoring system for diagnostic large medical equipment based on real-world data, and used PET/CT as a carrier for validation. These findings provided theoretical and empirical foundations for the management of diagnostic large medical equipment in China.

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