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机构地区:[1]河北北方学院附属第一医院信息管理处,河北张家口075000
出 处:《中国医药导报》2015年第25期141-143,159,共4页China Medical Herald
基 金:河北省张家口市科学技术和地震局科学技术研究与发展计划自筹经费项目(1421050I)
摘 要:目的研究HIS数据的挖掘统计对于医院管理决策的意义。方法运用问卷调查法,了解河北北方学院附属第一医院HIS数据的挖掘统计施行前(2012年4月~2013年4月)和实施后(2013年5月~2014年4月)医院管理人员(院领导3名、职能处室负责人4名、临床科室护士长4名以及主任5名)及一线工作人员(临床医师14名、临床护士20名)对医院管理情况的评价。比较HIS数据挖掘统计实施前后医院各方面管理情况及效果。结果挖掘统计实施后,各阶层管理人员对于医院管理的评分明显高于实施前,差异有统计学意义(P〈0.05)。实施后,医院各方面管理的评分明显高于实施前,差异有统计学意义(P〈0.05)。实施后,医院一线工作人员对于医院管理的评分明显高于实施前,差异有统计学意义(P〈0.05)。实施后优良率明显高于实施前,差异有统计学意义(P〈0.05)。结论HIS数据挖掘统计能够有效改善医院的管理决策,提升医院水平,值得推荐使用。Objective To study the significance of mining statistics of HIS data on decision making of hospital management. Methods Questionnaires were used to learn about the evaluation of hospital administrators (3 hospital leader- ships, 4 functional departments person in charge, 4 head nurses of clinical departments and 5 directors of clinical department) and the front line staffs (14 clinical doctors and 20 clinical nurses) on the hospital management before mining statistics of HIS data implementation (from April 2012 to April 2013) and after mining statistics of HIS data implementation (from May 2013 to April 2014) in the First Hospital Affiliated to Hebei North University. All aspects of the situation and effect of hospital management were compared before and after mining statistics of HIS data implementation. Results After mining statistics of HIS data implementation, the hospital management scores of all levels of managers were significantly higher than those of before implementation, the differences were statistically significant (P 〈 0.05). After implementation, the scores of all aspects of hospital management were significantly higher than those of before implementation, the differences were statistically significant (P 〈 0.05). After implementation, the hospital management scores of the front-line staffs were significantly higher than those of before implementation, the differences were statistically significant (P 〈 0.05). The excellent and good rate after implementation were significantly higher than those of before implementation, the differences were statistically significant (P 〈 0.05). Conclusion The mining statistics of HIS data can effectively improve the hospital management decision, also enhance the hospital level, which is worth using.
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