{"title":"Progress in diabetes care in the KwaZulu-Natal public health sector: a decade of analysis","authors":"N. Sahadew, V. Singaram","doi":"10.1080/16089677.2019.1629080","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":43919,"journal":{"name":"Journal of Endocrinology Metabolism and Diabetes of South Africa","volume":"39 1","pages":"83 - 91"},"PeriodicalIF":0.6000,"publicationDate":"2019-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Endocrinology Metabolism and Diabetes of South Africa","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/16089677.2019.1629080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 3
Abstract
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.