南非四个省公共医疗保健部门的糖尿病:比较分析。

IF 1.2
N Sahadew, S Pillay, V S Singaram
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引用次数: 0

摘要

背景:在南非(SA)等发展中国家,糖尿病日益加重的负担一直未得到重视。近年来,有记录的和未确诊的糖尿病(DM)病例呈前所未有的指数级增长。事实证明,不可靠的数据收集、负担过重的卫生系统和落后的基础设施都是实现最佳疾病管理的障碍。地区卫生信息系统(DHIS)是南非公共卫生保健部门的数据收集工具。它在南非所有九个省都被用于收集数据,而不需要单独的患者标识符。目的:分析和比较DHIS在西开普省(WC)、东开普省(EC)、夸祖鲁-纳塔尔省(KZN)和南非豪登省收集的糖尿病数据。方法:对2016年DHIS的糖尿病相关数据进行审计。然后使用Excel对数据进行分析。使用数据透视表可以进行时间序列和横断面分析。图形设计使用Thinkcell软件。结果:在所调查的四个省份中,豪登省的糖尿病发病率最高,比报告的全球糖尿病发病率估计高67%,而WC的发病率最低。结论:大都市地区被强调为目标区域,进一步加强了目前在南南非城市化与糖尿病之间观察到的联系。筛查工作的存在和记录是南非公共医疗保健部门和DHIS朝着正确方向迈出的重要一步。随着在数据收集领域的标准和规范标准化方面加强省际协调,以及加强对数据官员和主要收集代理人的培训,高质量和丰富的数据是非常可能的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diabetes in the public healthcare sector of four South African provinces: A comparative analysis.

Background: The growing burden of diabetes has long been under the radar in developing countries such as South Africa (SA). In recent years, there has been an unprecedented and exponential increase in recorded and undiagnosed diabetes mellitus (DM) cases. Unreliable data collection, overburdened health systems and poor infrastructure have all proved to be barriers to achieving optimum disease management. The District Health Information System (DHIS) serves as the data collection tool for the SA public healthcare sector. It is used in all nine SA provinces to gather data without individual patient identifiers.

Objective: To analyse and compare the DM data collected by the DHIS in the Western Cape (WC), Eastern Cape (EC), KwaZulu-Natal (KZN) and Gauteng provinces of SA.

Methods: An audit of diabetes-related data from the DHIS for 2016 was conducted. The data were then analysed using Excel. Time-series and cross-sectional analyses were made possible using pivot tables. Graphics were designed using Thinkcell software.

Results: Of the four provinces surveyed, Gauteng recorded the highest incidence of DM, 67% higher than the reported global DM incidence estimate, while the WC had the lowest incidence. A similar pattern was also noted regarding the incidence of DM in people aged <18 years, with Gauteng having the highest and WC the lowest prevalence results. When comparing the number of DM-related consultations conducted in each province, the metropolitan districts were highlighted as hotspots of activity for DM care. This study found a moderate inversely proportional relationship between the incidence of DM in all provinces and education deprivation (p<0.05). Among the provinces that collected data on screening (excluding EC), KZN recorded the highest number of diabetic screenings.

Conclusion: Metropolitan areas were highlighted as areas to be targeted, further reinforcing the current connection observed between urbanisation and DM in SA. The presence and recording of screening efforts is an excellent step in the right direction for the SA public healthcare sector and the DHIS. With improved interprovincial co-ordination regarding standardisation of the criteria and specifications of data collection fields, and enhanced training for data officers and primary collection agents, good quality and rich data is a very close possibility.

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