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目的了解河南省疟疾患者诊治过程中的医疗费用情况,并探讨其影响因素。方法收集2013年11月-2014年10月河南省各级卫生机构诊断并网报的疟疾病例,对经镜检确诊的疟疾病例进行个案调查,收集病例的一般信息和诊治信息。运用SPSS17.0统计学软件,采用两(多)独立样本秩和检验及逐步回归分析法探讨疟疾患者医疗费用情况,及其相关影响因素。结果共调查了218例疟疾病例,其中73.4%来自乡村,其人均医疗费用为1 503元,来自城镇的患者人均医疗费用为4 833元;初诊选择乡村医院的患者人均医疗费用为2 600元,初诊选择省级综合医院的患者人均医疗费用为7 800元;在市、县级医院确诊患者的人均医疗费用为1 022.5元,在省级综合医院确诊患者的人均医疗费用为6 170元;经过1次就诊即确诊的患者人均医疗费用为0元(抗疟药免费),经过3次以上就诊确诊的患者人均医疗费用为5 621元。单因素分析结果显示,对医疗费用差异有统计学意义的变量为:疟疾患者的现居住地、初诊医院级别、确诊医院级别和就诊次数等因素(P<0.05)。逐步回归分析显示,初诊医院级别是疟疾患者医疗费用高低最主要的影响因素,其次为确诊医院级别、确诊前就诊次数。初诊医院、确诊医院级别越高,医疗费用越高,确诊前就诊次数越多,医疗费用越高。结论河南省疟疾患者的医疗费用与患者的就医行为存在着较明显的关联。
Objective To understand the medical expenses during the diagnosis and treatment of malaria patients in Henan Province and to explore the influencing factors. Methods The cases of malaria diagnosed and reported by the health institutions at all levels in Henan Province from November 2013 to October 2014 were collected. The malaria cases diagnosed by microscopic examination were collected and the general information and diagnosis and treatment information were collected. Using SPSS17.0 statistical software, using two (or more) independent sample rank sum test and stepwise regression analysis to explore the malaria patients medical costs, and its related factors. Results A total of 218 cases of malaria were investigated, of which 73.4% came from villages. The per capita medical cost was 1,503 yuan and the per capita medical expenses of urban residents was 4,833 yuan. The per capita medical cost of newly diagnosed rural hospitals was 2,600 yuan, The average per-capita medical expenses for patients newly diagnosed at the provincial general hospital was 7,800 yuan; the per capita medical expenses for patients diagnosed in cities and county-level hospitals were 1,022.5 yuan; the per capita medical expenses for patients diagnosed at provincial-level general hospitals were 6,170 yuan; The average per capita medical expenses for patients who were diagnosed at one visit was RMB0 (free of antimalarial drugs), and the per capita medical expenses of patients diagnosed more than three times were RMB5,621. The results of univariate analysis showed that the variables with statistically significant differences in medical expenses were the current residence of malaria patients, the level of newly diagnosed hospital, the level of hospital confirmed and the number of visits and so on (P <0.05). Stepwise regression analysis showed that the newly diagnosed hospital level was the most important factor affecting the level of medical costs in malaria patients, followed by the level of confirmed hospitals and the number of pre-diagnosis visits. Newly diagnosed hospitals, the higher the level of the hospital diagnosed, the higher the medical costs, the more the number of visits before the diagnosis, the higher the medical costs. Conclusion There is a clear correlation between the medical costs of malaria patients and the medical treatment of patients in Henan Province.