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脑梗死患者住院费用影响因素分析及预付费用模型构建 被引量:2

Cerebral infarction patients hospitalized costs influence factor analysis and prepaid expenses model building
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摘要 目的通过对2014年晋中市某医院脑梗死患者病例信息进行调查,研究影响这一病种住院费用的主要因素,同时对其中稳定的影响因素进行单病种预付费用模型构建,预测脑梗死疾病医保预付费的费用级别,从而为相关卫生行政部门制定单病种付费额度提供参考。方法采用回顾性调查方法对患者的住院费用进行研究,采集患者病历基本信息及有关住院费用资料,并运用统计软件SPSS对数据进行处理。结果根据多重线性回归分析得出:年龄、入院时情况、住院天数、护理方式、NIHSS评分等级及伴随病个数为住院费用的主要影响因素;并运用Logistic回归建立了Logit概率预测模型。结论年龄、入院时情况、住院天数、护理方式、NIHSS评分及伴随病个数六个影响因素为影响患者住院费用的主要因素;运用Logistic回归建立的脑梗死患者住院费用预测模型整体拟合良好。 Objective Through patients with cerebral infarction case information investigation of jinzhong hospital in 2014 years, study the main influencing factors of this disease hospitalization expenses, at the same time, using the stability influence factors to build a prepaid expenses of single diseases model, to provide the reference for the relevant administrative department of public health to formulate control cost and predict cerebral infarction disease health level of single macro-reforms lines. Methods Using retrospective survey research methods to study inpatient hospitalization expense, then collected patients' basic information and medical records about the hospitalization expense, simultaneously use the SPSS statistical software for data analysis. ResultsThrough multiple linear regression analysis: age, the situation on admission, hospitalization days, nursing way, NIHSS score level and the number of accompanying disease are the main factors influencing of hospitalization expenses. Using Logistic regression Logit probability prediction model is established. Conclusion Age, the situation on admission, hospitalization days, nursing way, NIHSS score and the number of accompanying disease six factors associated with disease as the main factors influencing the patients' hospitalization expenses;Using Logistic regression to establish cerebral infarction patients in hospital cost prediction model and the whole fitting is good.
出处 《中国处方药》 2016年第6期1-3,共3页 Journal of China Prescription Drug
关键词 脑梗死 住院费用 影响因素 模型构建 Cerebral infarction Hospitalization expenses Factors influencing Model building
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