利用亲和力分析诊断患者在电子医疗方面的需求。

IF 1.2
Agnieszka Strzelecka, Michał Stachura, Tomasz Wójcik, Anna Beata Pacian, Teresa Kulik, Jolanta Pacian, Monika Kaczoruk, Elżbieta Monika Galińska, Ewa Kawiak-Jawor, Grażyna Nowak-Starz
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引用次数: 2

摘要

简介:电子保健工具允许医疗机构使用信息通信技术对特定患者的数据进行排序,并且患者在与特定组织联系时使用这些技术。材料与方法:采用二次统计资料。该研究是在初级卫生保健患者中进行的。亲和力规则的挖掘是在R程序中完成的。使用规则包中的apriori和inspect函数。此外,从使用上述方法获得的规则中删除了任何冗余规则。将亲和分析方法的一般描述应用到本文描述的调查中,应该强调的是,使用亲和分析的目的是发现包含子事务B={V_6=1}作为结果的规则。这是由发现关于研究患者可能拥有的统一信息系统知识的关联的意图决定的。结果:在发现的规则中,先行词通常包含需要引入远程医疗统一解决方案的指示。此外,根据“有意识的”患者的意见,统一的IT系统应该改善初级卫生保健机构的工作,引入在线预约就诊系统应该提高医生的工作效率和舒适度,并且IT系统应该提供明确的患者身份识别。结论:在电子卫生系统中应用亲和分析是有潜力的。在他的研究中所描述的亲和分析的例子导致发现(从医疗机构的角度来看)关于患者关于电子保健的知识和期望的有趣和重要的规律。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using affinity analysis in diagnosing the needs of patients as regards e-Health.

Introduction: E-Health tools allow a medical facility to set a given patient's data in order using ICT techniques, and the patient to use those techniques when contacting a given organisation.

Material and methods: Secondary statistical data was used in the research. The study was carried out among primary health care patients. Mining for affinity rules was done in the R programme. The apriori and inspect functions from the arules package were used. Moreover, any redundant rules were removed from thoseobtained using the afero-mentioned method. Applying the general description of the affinity analysis method onto the survey described herein, it should be stressed that the aim of using affinity analysis was to discover the rules which contain the sub-transaction B={V_6=1} as a consequent. This was determined by the intention to discover associations regarding the knowledge about a uniform information system that the patients under study might have.

Results: In the discovered rules, the antecedent most often contained an indication of the need for introducing a uniform solution as regards telemedicine. Moreover, according to the opinions of 'conscious'patients, a uniform IT system should improve the work at primary health care institutions, introducing an on-line booking system for visits should improve the productivity and comfort of doctors, and an IT system should provide unambiguous identification of a patient.

Conclusions: There is potential in using affinity analysis within e-Health. The example of affinity analysis described in his study led to the discovery of interesting and important (from the point of view of a medical facility) regularities regarding the knowledge and expectations of patients as regards e-Health.

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