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Portable Health Clinic: A Pervasive Way to Serve the Unreached Community for Preventive Healthcare

机译:便携式医疗诊所:为未覆盖社区提供预防性医疗服务的普遍方法

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摘要

One billion people (15% of the world population) are unreached in terms of accessing to quality healthcare service. Insufficient healthcare facilities and unavailability of medical experts in rural areas are the two major reasons that kept the people unreached to healthcare services. Recent penetration of mobile phone and the unmet demand to basic healthcare services, remote health consultancy over mobile phone became popular in developing countries. In this paper, we introduce two such representative initiatives from Bangladesh and discuss the technical challenges they face to serve a remote patient. To solve these issues, we have prototyped a portable health clinic box with necessary diagnostic tools, we call it a "portable clinic" and a software tool, "GramHealth" for archiving and searching patients' past health records. We carried out experiments in three remote villages and in two commercial organizations in Bangladesh by collaborating with local organization to observe the local adoption of the technology. We also monitored the usability of the portable clinic and verified the functionality of "GramHealth". We display the qualitative analysis of the results obtained from the experiment. GramHealth DB has a unique combination of structured, semi-structured and un-structured data which can be considered as BigData. We have partly analyzed the data manually to find common set of rules to build a better clinical decision support. The model of analyzing the GramHealth BigData is also presented.
机译:10亿人(占世界人口的15%)无法获得优质的医疗服务。医疗保健设施不足和农村地区缺乏医疗专家是造成人们无法获得医疗保健服务的两个主要原因。最近手机的普及以及对基本医疗服务的需求未得到满足,通过手机进行远程医疗咨询在发展中国家变得很流行。在本文中,我们介绍了孟加拉国的两项具有代表性的倡议,并讨论了他们为远程患者提供服务时面临的技术挑战。为了解决这些问题,我们为便携式医疗诊所箱制作了原型,并配备了必要的诊断工具,我们将其称为“便携式诊所”和软件工具“ GramHealth”,用于存档和搜索患者过去的医疗记录。我们与孟加拉国的本地组织合作,在孟加拉国的三个偏远村庄和两个商业组织中进行了实验,以观察该技术在当地的应用。我们还监控了便携式诊所的可用性,并验证了“ GramHealth”的功能。我们展示了从实验中获得的结果的定性分析。 GramHealth DB具有结构化,半结构化和非结构化数据的独特组合,可以将其视为BigData。我们已经部分地手动分析了数据,以找到通用的规则集,以建立更好的临床决策支持。还介绍了分析GramHealth BigData的模型。

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