ArticleDigital health
The environmental sustainability of data-driven health research: A scoping review.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 33 citations in OpenAlex.
- The Environmental and Global Impact of Pharmacogenomics: Advancing Green Pharmacy Toward Sustainable and Inclusive Precision Medicine.Journal of personalized medicine · 2026Review
- Policy options on a sustainable path for clinical trials.Bulletin of the World Health Organization · 2026Article
- Greening public health: embedding environmental sustainability in research and practice.Frontiers in public health · 2026Article
- Artificial intelligence in medicine: a position paper by the Italian Society of Internal Medicine.Internal and emergency medicine · 2026Article
- Beyond techno-optimism: four critical limitations in the UK's AI policy for health care.The British journal of general practice : the journal of the Royal College of General Practitioners · 2025Article
- Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024).JMIR public health and surveillance · 2025Article
- Evaluating the environmental sustainability of AI in radiology: a systematic review of current practice.BMJ digital health & AI · 2025Article
- The relevance of sustainable laboratory practices.RSC sustainability · 2024Review
- May Artificial Intelligence take health and sustainability on a honeymoon? Towards green technologies for multidimensional health and environmental justice.Global bioethics = Problemi di bioetica · 2024Article
- Artificial intelligence for optimizing benefits and minimizing risks of pharmacological therapies: challenges and opportunities.Frontiers in drug safety and regulation · 2024Review
- Article
- Systems thinking and efficiency under emissions constraints: Addressing rebound effects in digital innovation and policy.Patterns (New York, N.Y.) · 2023Review
- The environmental impact of data-driven precision medicine initiatives.Cambridge prisms. Precision medicine · 2023Review
- Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Data-Driven and Artificial Intelligence technologies are rapidly changing the way that health research is conducted, including offering new opportunities. This will inevitably have adverse environmental impacts. These include carbon dioxide emissions linked to the energy required to generate and process large amounts of data; the impact on the material environment (in the form of data centres); the unsustainable extraction of minerals for technological components; and e-waste (discarded electronic appliances) disposal. The growth of Data-Driven and Artificial Intelligence technologies means there is now a compelling need to consider these environmental impacts and develop means to mitigate them. Here, we offer a scoping review of how the environmental impacts of data storage and processing during Data-Driven and Artificial Intelligence health-related research are being discussed in the academic literature. Using the UK as a case study, we also offer a review of policies and initiatives that consider the environmental impacts of data storage and processing during Data-Driven and Artificial Intelligence health-related research in the UK. Our findings suggest little engagement with these issues to date. We discuss the implications of this and suggest ways that the Data-Driven and Artificial Intelligence health research sector needs to move to become more environmentally sustainable.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.