Application of mathematical models on efficiency evaluation and intervention of medical institutions in China

Abstract

Abstract Background The efficiency of medical services directly impacts the economic burden of healthcare, making it crucial to analyze the input-output efficiency of various types of medical institutions. However, while hospitals had been extensively analyzed for their efficiency, other types of medical institutions had received limited attention in this regard. Methods In this study, we employed data envelopment analysis (DEA) methods based on time series and internal benchmarks to autonomously assess the efficiency of 18 distinct categories of healthcare facilities in China over the past decade. The verification was conducted through the utilization of the critical incident technique (CIT). Additionally, we utilized the Delphi process (AHP) method to evaluate suppliers of medical consumables, implemented a multi-population genetic algorithm for managing these consumethod and analytic hierarchymables efficiently, and applied stakeholder theory to manage medical personnel efficiency. Results Our findings indicated that medical institutions capable of providing clinical services exhibited higher levels of efficiency compared to those unable to do so. Multiple indicators suggested redundancy within these institutions. Notably, comprehensive benefit evaluation revealed that clinical laboratory had performed poorly over the past decade. We selected an inefficient medical institution for intervention in reagent management and the work efficiency of medical staff. After implementing the Delphi method and multi-population genetic algorithm for consumable replenishment, the reagent cost was reduced by 40%, 39% and 31% respectively in each of the three experimental groups, compared to the control group. By applying stakeholder theory and process reengineering methods, we were able to shorten quality control management time for medical staff in the experimental group by 41 min per day, reduce clinical service time by 25 min per day, and extend rest time by 70 min per day, while the quality indicators were all meeting the targets. Conclusion By employing various mathematical models as described above, we were able to reduce costs associated with medical consumables and enhance medical personnel work efficiency without compromising quality objectives.

Keywords

• DEA
• CIT
• Delphi
• AHP
• Multi-population genetic algorithm
• Stakeholder