Assessing the geographical distribution of comorbidity among commercially insured individuals in South Africa

Mannie, Cristina; Kharrazi, Hadi

doi:10.1186/s12889-020-09771-6

Cited by 3 publications

(9 citation statements)

References 21 publications

(29 reference statements)

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“…However, these studies provide an important source of information that is highly relevant to the management and planning for multimorbidities. For example, a recent study by Mannie and Kharrazi 48 assessed the geographical distribution of comorbidities among 2.6 million commercially insured individuals in South Africa using a comorbidity index that highlighted healthcare utilisation. Using this score, they were able to identify areas of high utilisation and underserved individuals; although they did not provide detail on the types of services needed.…”

Section: Discussionmentioning

confidence: 99%

Multimorbidity in South Africa: a systematic review of prevalence studies

et al. 2021

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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.

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Section: Discussionmentioning

confidence: 99%

Multimorbidity in South Africa: a systematic review of prevalence studies

et al. 2021

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“…Since health status is dynamic and expected to change from time to time, the average morbidity and average healthcare costs of individuals with membership across both years were used to provide a better indication of the health status and healthcare resource needs of each individual as opposed to using only a single year. Details of the inclusion criteria applied in this study are published elsewhere [10].…”

Section: Study Populationmentioning

confidence: 99%

“…Incorporating comorbidities in disparities research provides a useful approach to assessing the total burden of disease in underprivileged populations [6]. Nonetheless, measuring comorbidities in a population is challenging and requires calculating validated comorbidity indices [8,9] across a large number of individuals using data collected across health providers [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…Morbidity studies in South Africa (SA) have traditionally focused on individual diseases [12] or a combination of few, select, commonly occurring chronic diseases [13][14][15], have been based on small and often geographically limited samples [15], and have involved time-consuming, non-routine data collection processes [12,14]. To address these limitations, in a past study, we leveraged insurance claims data and used a validated comorbidity index to measure the total burden of disease across 2.6 million commercially insured individuals residing in different SA geographies [10]. The study served to highlight how a measure of comorbidity can be used to provide a more in-depth understanding of the current and future healthcare needs through its determination of individuallevel health status.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, the aggregated comorbidity data described the impact of geographic regions on potential health inequities. The study concluded that comorbidity indexes should be further investigated as a means to detect geographical areas of increased and potential unmet healthcare needs [10].…”

Section: Introductionmentioning

confidence: 99%

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Measuring the geographic disparity of comorbidity in commercially insured individuals compared to the distribution of physicians in South Africa

Mannie

Strydom²,

Kharrazi

2022

BMC Prim. Care

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Background Measuring and addressing the disparity between access to healthcare resources and underlying health needs of populations is a prominent focus in health policy development. More recently, the fair distribution of healthcare resources among population subgroups have become an important indication of health inequities. Single disease outcomes are commonly used for healthcare resource allocations; however, leveraging population-level comorbidity measures for health disparity research has been limited. This study compares the geographical distribution of comorbidity and associated healthcare utilization among commercially insured individuals in South Africa (SA) relative to the distribution of physicians. Methods A retrospective, cross-sectional analysis was performed comparing the geographical distribution of comorbidity and physicians for 2.6 million commercially insured individuals over 2016–2017, stratified by geographical districts and population groups in SA. We applied the Johns Hopkins ACG® System across the claims data of a large health plan administrator to measure a comorbidity risk score for each individual. By aggregating individual scores, we determined the average healthcare resource need of individuals per district, known as the comorbidity index (CMI), to describe the disease burden per district. Linear regression models were constructed to test the relationship between CMI, age, gender, population group, and population density against physician density. Results Our results showed a tendency for physicians to practice in geographic areas with more insurance enrollees and not necessarily where disease burden may be highest. This was confirmed by a negative relationship between physician density and CMI for the overall population and for three of the four major population groups. Among the population groups, the Black African population had, on average, access to fewer physicians per capita than other population groups, before and after adjusting for confounding factors. Conclusion CMI is a novel measure for healthcare disparities research that considers both acute and chronic conditions contributing to current and future healthcare costs. Our study linked and compared the population-level geographical distribution of CMI to the distribution of physicians using routinely collected data. Our results could provide vital information towards the more equitable distribution of healthcare providers across population groups in SA, and to meet the healthcare needs of disadvantaged communities.

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Geospatial assessment of the convergence of communicable and non-communicable diseases in South Africa

Cuadros,

Moreno,

Tomita

et al. 2023

Journal of Multimorbidity and Comorbidity

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Introduction Several low-and middle-income countries are undergoing rapid epidemiological transition with a rising burden of non-communicable diseases (NCDs). South Africa (SA) is a country with one of the largest HIV epidemics worldwide and a growing burden of NCDs where the collision of these epidemics poses a major public health challenge. Methods Using data from a large nationally representative survey, the South Africa Demographic and Health Survey (SADHS 2016), we conducted a geospatial analysis of several diseases including HIV, tuberculosis (TB), cardiovascular, respiratory, and metabolic diseases to identify areas with a high burden of co-morbidity within the country. We explored the spatial structure of each disease and associations between diseases using different spatial and visual data methodologies. We also assessed the individual level co-occurrence of HIV and the other diseases included in the analysis. Results The spatial distribution for HIV prevalence showed that this epidemic is most intense in the eastern region of the country, mostly within the Gauteng, Mpumalanga, and Kwazulu-Natal provinces. In contrast, chronic diseases had their highest prevalence rates the southern region of the country, particularly in the Eastern and Western Cape provinces. Individual-level analyses were consistent with the spatial correlations and found no statistically significant associations between HIV infection and the presence of any NCDs. Conclusions We found no evidence of geospatial overlap between the HIV epidemic and NCDs in SA. These results evidence the complex epidemiological landscape of the country, characterized by geographically distinct areas exhibiting different health burdens. The detailed description of the heterogenous prevalence of HIV and NCDs in SA reported in this study could be a useful tool to inform and direct policies to enhance targeted health service delivery according to the local health needs of each community.

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Assessing the geographical distribution of comorbidity among commercially insured individuals in South Africa

Cited by 3 publications

References 21 publications

Multimorbidity in South Africa: a systematic review of prevalence studies

Multimorbidity in South Africa: a systematic review of prevalence studies

Measuring the geographic disparity of comorbidity in commercially insured individuals compared to the distribution of physicians in South Africa

Geospatial assessment of the convergence of communicable and non-communicable diseases in South Africa

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