患者偏好系数与医疗卫生机构就诊率的关系研究

A Study on the Relationship between Patient Preference Coefficient and Treatment Rate of Medical and Health Institutions

中国正积极推动分级诊疗制度,实现患者的基层首诊和双向转诊,对基层医疗卫生机构的就诊率提出到2017年超过65%的新要求。然而,近10年来,基层医疗卫生机构就诊率总体处于下降的趋势,表明距离分级诊疗目标的差距依然存在且逐年增大。为了有针对性地研究不同医疗卫生机构的就诊率影响因素,以更有效地开展分级诊疗制度,以中国医疗卫生机构作为研究对象,针对医疗卫生机构的门诊部门进行研究,定义患者偏好系数为偏好医院就医的患者人次占患者总人次的比例。基于医疗卫生机构资源配置的限制,患者并不一定最终选择其所偏好的医疗卫生机构就诊。关于患者偏好系数和医疗卫生机构的就诊率提出假设,并基于马尔可夫过程对患者就医选择过程进行分析,得到理想状态下(即不考虑资源约束和患者偏好)医疗卫生机构就诊率的平稳状态。采用Anylogic仿真软件对中国国内不同患者偏好系数下的过程进行仿真模拟,在此基础上构建与患者偏好系数相关的医疗卫生机构就诊率的数学模型。研究结果表明,患者偏好系数与就诊率之间的关系受到资源的约束,当基层医疗卫生机构资源不足时,患者偏好系数存在一个临界值,患者偏好系数等于该临界值时,基层医疗卫生机构资源达到饱和,当患者偏好系数低于此临界值,基层医疗卫生机构就诊率不再发生变化,但医院就诊率也不再降低,反而保持在稳定水平。当医院资源达到饱和时也是同样的情况。在仿真基础上从定量角度进一步描述患者偏好系数与医疗卫生机构就诊率之间的关系,通过仿真结果分析患者流拥堵严重的位置。从患者就医选择的偏好角度出发,与医疗卫生机构就诊率构建关系,以患者需求反推医疗卫生机构的改进措施,提出人才培养与吸引、设备投入、医患关系和试点研究4个方面的建议,对提高基层医疗卫生机构就诊率进而实现分级诊疗的目标以及进一步开展相关研究具有积极意义。

China is actively promoting the hierarchical medical system to achieve primary diagnosis and two-way referral, and it puts forward new demands that there is a need for grassroots medical institutions to let its treatment rate beyond 65%. Neverthe- less, the treatment rate of grassroots medical institutions has continued to decline in the past ten years, which indicates that the gap between the targets of hierarchical medical system still exists and has increased year by year. In order to devise the research on the treatment rate of different medical and health institutions pertinently and more effec- tively carry on the study on hierarchical medical system without loss of generality, medical and health institutions are divided into two categories（hospitals and grassroots medical institutions） accordingly in China as our research object. The research aims at the outpatient department of the medical and health institutions, and due to limited medical resources, patients may not choose the institutions which they prefer , though the patient preference coefficient is defined as the ratio of the number of patients who prefer hospitals and the total number of patients attending the hospitals. This research hypothesizes the relationship between pa- tient preference coefficient and treatment rate of medical and health institutions, and analyzes patients＇ treatment process based on Markov process so as to achieve the equilibrium of treatment rate ideally （ without considering constraints of resources and pa- tient preference）. Anylogic software is used to simulate the process with different preference coefficients in China. The simulation results show that hypotheses of this study are approved. However, as the resources are insufficient, there is a critical value for patient preference coefficient, and the relationships on different sides of the critical value are also different. For example, when the resources of grassroots medical institutions are insufficient, there is a critical value for patient preference coefficient that the resources of grassroots medical institutions reach saturation. When the patient preference coefficient is below this critical value, the treatment rate of grassroots medical institutions and hospitals will both no longer change with patient prefer- ence coefficient changing. When the patient preference coefficient is higher than that of this critical value, the treatment rate of grassroots medical institutions decreased with the increase of patient preference coefficient, while the treatment rate of hospitals increased with the increase of patient preference coefficient. Additionally, through results of simulation, it also found some loca- tion with severe congestion because of patients＇ waitin.g. From the patient preference perspective, the study constructs the relationship between patient preference and treatment rate of medical and health institutions, and then puts forward improvements in view of the needs of patients. Furthermore, it is of pos- itive significance to put forward suggestions from four perspectives of talents cultivation, equipment investment , patient - physi- cian relationship and experimenis to improve the treatment rate of grassroots medical institutions so as to achieve the target of hi- erarchical medical system for further study.