Multimorbidity in South Africa: Is the health system ready?
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SUBMITTER: Roomaney RA
PROVIDER: S-EPMC10278409 | biostudies-literature | 2023 Jan-Dec
REPOSITORIES: biostudies-literature
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Multimorbidity in South Africa: Is the health system ready?
Roomaney Rifqah Abeeda RA van Wyk Brian B Pillay-van Wyk Victoria V
Journal of multimorbidity and comorbidity 20230101
<b>Background:</b> Multimorbidity is likely to be a significant contributor to ill health and inequality in South Africa and yet has been largely overlooked. <b>Purpose:</b> This paper focuses on the findings of a recent large study that highlighted emerging issues - namely (i) the high levels of multimorbidity among three key groups - older adults, women, and the wealthy; (ii) discordant and concordant disease clusters among the multimorbid. <b>Research Design:</b> Narrative. <b>Study Sample an ...[more]
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Project description:Implementation of a National Health Insurance (NHI) in South Africa requires a reliable, standardized health information system that supports Diagnosis-Related Groupers for reimbursements and resource management. We assessed the quality of inpatient health records, the availability of standard discharge summaries and coded clinical data and the congruence between inpatient health records and discharge summaries in public-sector hospitals to support the NHI implementation in terms of reimbursement and resource management. We undertook a cross-sectional health-records review from 45 representative public hospitals consisting of seven tertiary, 10 regional and 28 district hospitals in 10 NHI pilot districts representing all nine provinces. Data were abstracted from a randomly selected sample of 5795 inpatient health records from the surgical, medical, obstetrics and gynaecology, paediatrics and psychiatry departments. Quality was assessed for 10 pre-defined data elements relevant to NHI reimbursements, by comparing information in source registers, patient folders and discharge summaries for patients admitted in March and July 2015. Cohen's/Fleiss' kappa coefficients (κ) were used to measure agreements between the sources. While 3768 (65%) of the 5795 inpatient-level records contained a discharge summary, less than 835 (15%) of diagnoses were coded using ICD-10 codes. Despite most of the records having correct patient identifiers [κ: 0.92; 95% confidence interval (CI) 0.91-0.93], significant inconsistencies were observed between the registers, patient folders and discharge summaries for some data elements: attending physician's signature (κ: 0.71; 95% CI 0.67-0.75); results of the investigation (κ: 0.71; 95% CI 0.69-0.74); patient's age (κ: 0.72; 95% CI 0.70-0.74); and discharge diagnosis (κ: 0.92; 95% CI 0.90-0.94). The strength of agreement for all elements was statistically significant (P-value ≤ 0.001). The absence of coded inpatient diagnoses and identified data inaccuracies indicates that existing routine health information systems in public-sector hospitals in the NHI pilot districts are not yet able to sufficiently support reimbursements and resource management. Institutional capacity is needed to undertake diagnostic coding, improve data quality and ensure that a standard discharge summary is completed for every inpatient.
| S-EPMC8173599 | biostudies-literature
Project description:BackgroundVery little is known about socioeconomic related inequalities in multimorbidity, especially in developing countries. Traditionally, studies on health inequalities have mainly focused on a single disease condition or different conditions in isolation. This paper examines socioeconomic inequality in multimorbidity in illness and disability in South Africa between 2005 and 2008.MethodsData were drawn from the 2005, 2006, 2007, and 2008 rounds of the nationally representative annual South African General Household Surveys (GHS). Indirectly standardised concentration indices were used to assess socioeconomic inequality. A proxy index of socioeconomic status was constructed, for each year, using a selected set of variables that are available in all the GHS rounds. Multimorbidity in illness and disability were constructed using data on nine illnesses and six disabilities contained in the GHS.ResultsMultimorbidity affects a substantial number of South Africans. Most often, based on the nine illness conditions and six disability conditions considered, multimorbidity in illness and multimorbidity in disability are each found to involve only two conditions. In 2008 in South Africa, the multimorbidity that affected the greatest number of individuals (0.6% of the population) combined high blood pressure (BP) with at least one other illness. The combination of sexually transmitted diseases (STDs) and other condition or conditions is the least reported (i.e. 0.02% of the population). Between 2005 and 2008, multimorbidity in illness and disability is more prevalent among the poor; in disabilities this is yet more consistent. The concentration index of multiple illnesses in 2005 and 2008 are -0.0009 and -0.0006 respectively. The corresponding values for multiple disabilities are -0.0006 and -0.0006 respectively.ConclusionWhile there is a dearth of information on the socioeconomic distribution of multimorbidity in many developing countries, this paper has shown that its distribution in South Africa indicates that the poor bear a greater burden of multimorbidity. This is more so for disability than for illness. This paper argues that, given the high burden and skewed socioeconomic distribution of multimorbidity, there is a need to design policies to address this situation. Further, there is a need to design surveys that specifically assess multimorbidity.
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Project description:IntroductionSouth Africa has the largest burden of HIV worldwide and has a growing burden of non-communicable diseases; the combination of which may lead to diseases clustering in ways that are not seen in other regions. This study sought to identify common disease classes and sociodemographic and lifestyle factors associated with each disease class.MethodsData were analyzed from the South African Demographic and Health Survey 2016. A latent class analysis (LCA) was conducted using nine disease conditions. Sociodemographic and behavioral factors associated with each disease cluster were explored. All analysis was conducted in Stata 15 and the LCA Stata plugin was used to conduct the latent class and regression analysis.ResultsMultimorbid participants were included (n = 2 368). Four disease classes were identified: (1) HIV, Hypertension and Anemia (comprising 39.4% of the multimorbid population), (2) Anemia and Hypertension (23.7%), (3) Cardiovascular-related (19.9%) and (4) Diabetes and Hypertension (17.0%). Age, sex, and lifestyle risk factors were associated with class membership. In terms of age, with older adults were less likely to belong to the first class (HIV, Hypertension and Anemia). Males were more likely to belong to Class 2 (Anemia and Hypertension) and Class 4 (Diabetes and Hypertension). In terms of alcohol consumption, those that consumed alcohol were less likely to belong to Class 4 (Diabetes and Hypertension). Current smokers were more likely to belong to Class 3 (Cardiovascular-related). People with a higher body mass index tended to belong to Class 3 (Cardiovascular-related) or the Class 4 (Diabetes and Hypertension).ConclusionThis study affirmed that integrated care is urgently needed, evidenced by the largest disease class being an overlap of chronic infectious diseases and non-communicable diseases. This study also highlighted the need for hypertension to be addressed. Tackling the risk factors associated with hypertension could avert an epidemic of multimorbidity.
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Project description:The aim of this study was to compare the transcriptional response to TB in regions of different incidence / prevalence.
2010-08-11 | GSE19442 | GEO
Project description:ObjectivesTo review prevalence studies of multimorbidity in South Africa to identify prevalence estimates, common disease clusters and factors associated with multimorbidity.DesignSystematic review.SettingSouth Africa (general community and healthcare facilities).Data sourcesArticles were retrieved from electronic databases (PubMed, Web of Science, Scopus, CINAHL, Science Direct and JSTOR).Eligibility criteriaStudies addressing the prevalence of multimorbidity in South Africa were eligible for inclusion. A systematic search was done in various databases up to December 2020. A risk of bias assessment was conducted for each article using a modified checklist.Study selectionTwo researchers independently screened titles and abstracts; assessed the risk of bias of each study and extracted data. Included studies were described using a narrative synthesis.ResultsIn total, 1407 titles were retrieved; of which 10 articles were included in the narrative synthesis. Six studies had a low risk of bias and three had a moderate risk of bias. One study was not assessed for risk of bias, because there was no criteria that apply to routine health information systems. Three of the included studies were population-based surveys, four were community-based cohorts and three cross-sectional studies of health facility data. The prevalence of multimorbidity was low to moderate (3%-23%) in studies that included younger people or had a wide range of selected age groups; and moderate to high (30%-87%) in studies of older adults. The common disease clusters were hypertension and diabetes, hypertension and HIV, and TB and HIV.ConclusionAll studies indicated that multimorbidity is a norm in South Africa, especially among older adults. Hypertension is the main driver of multimorbidity. Research on multimorbidity in South Africa needs to be strengthened with high-quality study designs.Prospero registration numberCRD42020196895.
| S-EPMC8496399 | biostudies-literature
Project description:IntroductionMultimorbidity has increased globally over the past two decades, due to ageing populations and increased burden of non-communicable diseases (NCDs). In a country like South Africa, with a growing burden of NCDs and a high prevalence of HIV, information on multimorbidity can improve planning for healthcare delivery and utilisation, and reduce costs in the context of constrained health resources. This review aims to synthesise prevalence studies on multimorbidity, and identify dominant clusters and trends of multimorbidity in South Africa.Methods and analysisWe will search electronic bibliographic databases (PubMed, Scopus, JSTOR, POPLINE, PsycINFO, ScienceDirect, Web of Science and CINAHL), and the reference lists of included articles. Two researchers will independently screen title and abstracts, and then full text to identify studies published before and in 2020 that report on prevalence of multimorbidity in South Africa. Risk of bias assessments will be done for each study. Information on the prevalence of multimorbidity and disease clusters will be extracted from each study. Where possible, prevalence of specific clusters of multimorbidity will be pooled using a random effects meta-analysis to account for variability between studies. The I2 statistic will be used to establish the extent of heterogeneity due to variation in prevalence estimates rather than due to chance. The systematic review will be reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses.Ethics and disseminationOnly published journal articles will be included in the systematic review. This review received ethics approval as part of a larger project by the University of the Western Cape Biomedical Science Research Ethics Committee (BM20/5/8). The findings from this research will be used to estimate the prevalence of multimorbidity in South Africa and will contribute to the design of future research projects. The findings will be disseminated in a peer-reviewed journal article.Prospero registration numberCRD42020196895.
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Project description:Metagenomics analysis of sewage for surveillance of antimicrobial resistance in South Africa
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