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ANT Perspective of Healthcare Big Data for Service Delivery in South Africa

机译:南非服务交付的医疗保健大数据的蚂蚁透视

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摘要

In South Africa, there has been for many years challenges in how healthcare big data are accessed, used, and managed by facilities, particularly the small health facilities. The challenges arise from inaccuracy and inconsistency of patients' data and have impact on diagnoses, medications, and treatments, which consequently contributes to fatalities in South Africa, particularly in the rural areas of the country. The problem of inaccuracy and inconsistency of patients' data is often caused by lack of or poor analysis (or analytics) of data. Thus, the objective of this research was to understand the factors that influence the use and management of patients' big data for healthcare service delivery. The qualitative methods were applied, and a South African healthcare facility was used as a case in the study. Actor network theory (ANT) was employed as a lens to guide the analysis of the qualitative data. Based on the findings from the analysis, a model was developed, which is intended to guide analytics of big data for healthcare purposes, towards improving service delivery in the country.
机译:在南非,通过设施,特别是小型卫生设施,有多年的医疗保健大数据如何获得多年的挑战。患者数据的不准确性和不一致的挑战产生了影响,并对诊断,药物和治疗产生影响,因此导致南非的死亡,特别是在该国的农村地区。患者数据不准确和不一致的问题通常是由于数据的分析(或分析)缺乏或差的数据。因此,本研究的目的是了解影响患者大数据的使用和管理的医疗保健服务交付的因素。适用的定性方法,南非医疗保健设施被用作该研究的案例。演员网络理论(ANT)被用作指导定性数据分析的镜头。基于分析的发现,开发了一种模型,旨在指导医疗保健目的的大数据分析,从而改善该国的服务交付。

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