夸祖鲁-纳塔尔省公共卫生部门糖尿病护理的进展:十年分析

IF 0.6 Q4 ENDOCRINOLOGY & METABOLISM
N. Sahadew, V. Singaram
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引用次数: 3

摘要

目的:本研究分析了夸祖鲁-纳塔尔省(KZN)卫生部(DOH)常规收集的糖尿病相关信息。方法:通过区卫生信息系统(DHIS)获取2006-2016年(含11年)所有公共卫生机构的原始数据。从南非统计局获得了关于人口估计的其他开放来源数据。在使用ThinkCell软件生成图形表示之前,使用Microsoft Excel对DHIS数据进行定量分析。结果:2006年至2015年10年间,KZN糖尿病患者的临床就诊次数增加了305%。根据卫生部收集的数据,绝大多数被诊断患有糖尿病的患者都在人口较多的埃德克温尼区寻求医疗服务。自2012年开始记录以来,未按时返回治疗的患者(违约者)数量有所减少。数据显示,KZN地区糖尿病发病率呈波动趋势;然而,发病率与患者筛查之间存在很强的相关性。结论:糖尿病患者以德班市高度城市化地区最多。对高危患者的筛查频率有所增加,并与发病率密切相关,这进一步支持了筛查的有效性,并将其纳入新的初级卫生保健方案。2016年,违约患者的数量急剧减少,这可能表明依从性有所改善。数据输入的不一致性是本研究的一个局限性。然而,在这些限制条件下,这项研究强调了“大数据”对医疗保健政策和更有效的医疗保健在KZN的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Progress in diabetes care in the KwaZulu-Natal public health sector: a decade of analysis
Aims: This study analysed diabetes-related information routinely collected by the KwaZulu-Natal (KZN) Department of Health (DOH). Methods: Primary data were obtained for all public health facilities through the District Health Information System (DHIS) for the period 2006–2016 inclusive (11 years). Additional open source data on population estimates were obtained from Statistics South Africa. Quantitative analysis of DHIS data was performed using Microsoft Excel before graphical representations were generated using the ThinkCell software. Results: The number of clinical visits by diabetic patients in KZN increased by 305% in the 10 years between 2006 and 2015. According to the data collected by the Department of Health, a large majority of patients diagnosed with diabetes are seeking medical care in the more populated district of eThekwini. The number of patients not returning for scheduled treatment (defaulters) has reduced since recording began in 2012. According to the data, the incidence of diabetes in KZN is oscillating; however, a strong correlation is found between incidence and patient screening. Conclusion: The largest number of diabetic patients were seen in the highly urbanised district of eThekwini. The screening of high-risk patients has increased in frequency and exhibits strong correlations with incidence, further supporting the effectiveness of screening and its inclusion in a new primary healthcare protocol. There was a sharp reduction in number of defaulting patients in 2016, probably indicating improved compliance. The inconsistency of data input is a limitation of the study. However, this study within these constraints highlights the importance of ‘big data’ for healthcare policy and more effective health care in KZN.
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