基于多层神经网络算法的主诊医师岗位核定研究

目的探索主诊医师岗位核定的科学方法。方法多层神经网络算法。结果3个主诊医师岗位核定影响因素的标准化重要性排序从高到低依次为:床位数（100.0%）、年床均出院量（10.1%）、三四级手术占比（9.3%），并精准预测了各外科科室主诊医师岗位数，外科医师对主诊医师岗位核定方案满意，总体满意度得分为（4.40±0.31）分。结论运用多层神经网络算法科学设置主诊医师岗位数，能够充分调动医生主观能动性，有利于医疗资源合理配置。

Post Verification of Attending Physician Based on Multilayer Neural Network Algorithm

ObjectiveTo explore the scientific method of post verification of attending physician. MethodsThe multilayer neural network algorithm was used.ResultsThe standardized importance of the three factors,ranked from high to low: the number of beds (100.0%), the annual discharge per bed (10.1%), and the proportion of third-grade and fourth-grade operations (9.3%). The number of posts of attending physicians in each surgical department was accurately predicted. Surgeons were satisfied with the post verification scheme of attending physicians, and the overall satisfaction score was (4.40±0.31) points.Conclusion The use of multilayer neural network algorithm to scientifically set the number of attending physician can fully mobilize the subjective initiative of doctors, which is conducive to the rational allocation of medical resources.