| 李雪梅,张 薇,孟晓晶,张志毅.基于灰熵关联的平均住院日影响因素研究[J].,2017,17(22):4273-4276 |
| 基于灰熵关联的平均住院日影响因素研究 |
| Research on Influence Factors of Average Length of Stay Based on Degree of Grey Entropy |
| 投稿时间：2016-11-25 修订日期：2016-12-20 |
| DOI：10.13241/j.cnki.pmb.2017.22.016 |
| 中文关键词: 灰熵 平均住院日 影响因素 |
| 英文关键词: Grey entropy Average length of stay Influence factors |
| 基金项目:黑龙江省教育厅2014年度人文社会科学（面上）项目（12542149） |
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| 中文摘要: |
| 摘要 目的：分析医疗指标与平均住院日的关联程度，为医院有效缩短平均住院日提供参考依据。方法：建立基于灰熵优化的加权灰色关联度模型，对影响平均住院日的医疗指标进行重要程度的分析。结果：根据关联程度分析，可知影响平均住院日的医疗指标重要程度依次为开放床位数、床位周转次数、治疗有效率、床位使用率、年门诊量、住院手术人次和出院人数。结论：基于灰熵优化的加权灰色关联分析方法可以有效分析医疗指标对平均住院日的影响程度，提高医疗服务质量。 |
| 英文摘要: |
| ABSTRACT Objective: Providing reference basis for effective shorten the average length of stay, this article analyses degree of the medical treatment index and the average length of stay. Methods: This article establishes a model of the weighted grey incidence of optimized grey entropy, and analyzes the influence of the medical treatment index for the average length of stay. Results: According to analyze correlation degree, the influence of the medical treatment index for the average length of stay in order of importance is open berths to count,bunk down times, treatment effectiveness, beds rate of utilization of hospital beds, annual outpatient service quantity, hospital surgery people number and discharge. Conclusion: Weighted grey incidence analysis method based on optimized grey entropy can effectively analyze influence degree of the medical treatment index for the average length of stay, and improving the quality of medical services. |
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