2021
DOI: 10.1007/s11524-021-00558-7
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Data Sources for Understanding the Social Determinants of Health: Examples from Two Middle-Income Countries: the 3-D Commission

Abstract: The expansion in the scope, scale, and sources of data on the wider social determinants of health (SDH) in the last decades could bridge gaps in information available for decision-making. However, challenges remain in making data widely available, accessible, and useful towards improving population health. While traditional, government-supported data sources and comparable data are most often used to characterize social determinants, there are still capacity and management constraints on data availability and … Show more

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Cited by 4 publications
(3 citation statements)
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“…Data are often not harmonized nor interoperable across sectors, making data integration a challenge and subsequent analysis/modeling difficult. 29 The lack of standardized terminologies and definitions will also limit semantic interoperability, posing a challenge to the implementation of algorithms. This issue is not specific to LMICs.…”
Section: Challenges and Barriersmentioning
confidence: 99%
“…Data are often not harmonized nor interoperable across sectors, making data integration a challenge and subsequent analysis/modeling difficult. 29 The lack of standardized terminologies and definitions will also limit semantic interoperability, posing a challenge to the implementation of algorithms. This issue is not specific to LMICs.…”
Section: Challenges and Barriersmentioning
confidence: 99%
“…Thus, limited resources can significantly impact the ability to collect comprehensive data, especially in the context of data modeling. Data resource constraints can manifest in various ways, including limited access to essential data sources, 46 lack of communication with patients and other stakeholders regarding the measurements, 47 insufficient funding for data collection initiatives, 48 and inadequate technology infrastructure. 49 These constraints hinder the comprehensive data gathering needed to understand and address the upstream factors influencing health outcomes (Table 2 ).…”
Section: Understanding Data Challenges In the Context Of Whole Health...mentioning
confidence: 99%
“… 22 This framework argues that various factors influence health beyond biological factors. 23 , 24 This framework assists in presenting important information that can be used by policymakers, researchers and governments to assist in reducing inequities and promoting better health outcomes. 25 With this, the main objective of the study was to examine the determinants of self-reported chronic disease diagnoses among older persons in South Africa.…”
Section: Introductionmentioning
confidence: 99%