ArticleYearbook of medical informatics2024
Primary Care EHR data on Social Determinants of Health: Quality and Fitness for Purpose in Precision/Personalised Medicine.
Article in Yearbook of medical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPrecision and personalised medicine requires comprehensive genetic, epigenetic, lifestyle, social, community and environmental knowledge of the patient. This approach highlights the importance of the social determinants of health (SDoH), described by the World Health Organization (WHO) as 'the non-medical factors that influence health outcomes, the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life such as economic policies and systems, development agendas, social norms, social policies and political systems'.
methodsThis study examined if countries collect SDoH indicators and, if they do, the quality of the data and whether they are fit for clinical and population health purposes. The sources of data were EHR networks and, where not available, national data collections.
resultsWhile demographic details (age, gender) and rurality were well documented in most countries, we found that data availability and quality for education, occupation, income, socio-economic status, and residential care varied considerably between countries. Data for smoking, obesity, alcohol use, mental health, and substance use were generally poorly recorded.
conclusionRecommendations include a universal set of indicators and taxonomy for SDoH; common data model and metadata standards for national and global harmonisation and monitoring; benchmarks for data quality and fitness-for-purpose; capacity building at national and subnational levels in data collection, data analysis, communication and dissemination of results; ethical and transparent data stewardship; and governance, leadership and diplomacy across multiple sectors to co-create an enabling policy and regulatory environment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.