ReviewJournal of personalized medicine2021
Towards a Responsible Transition to Learning Healthcare Systems in Precision Medicine: Ethical Points to Consider.
Review in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 10 citations in OpenAlex.
- Genomic Data Governance Challenges Between Research and Clinical Care: A Scoping Review.Health expectations : an international journal of public participation in health care and health policy · 2026Article
- Available guidance for ethical challenges in learning health systems: an integrative literature review.Health research policy and systems · 2026Review
- The ethical aspects of human organ-on-chip models: A mapping review.Stem cell reports · 2025Review
- Blueprint for clinical N-of-1 strategies with off-label precision treatments in monogenic epilepsies.Orphanet journal of rare diseases · 2025Review
- An ethics framework for the transition to an operational learning healthcare system.Learning health systems · 2024Article
- Evolving assessment pathways for precision oncology medicines to improve patient access: a tumor-agnostic lens.The oncologist · 2024Article
- Building a Sustainable Learning Health Care System for Pregnant and Lactating People: Interview Study Among Data Access Providers.JMIR pediatrics and parenting · 2024Article
- The Role of Genome Sequencing in Neonatal Intensive Care Units.Annual review of genomics and human genetics · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
Abstract
Learning healthcare systems have recently emerged as a strategy to continuously use experiences and outcomes of clinical care for research purposes in precision medicine. Although it is known that learning healthcare transitions in general raise important ethical challenges, the ethical ramifications of such transitions in the specific context of precision medicine have not extensively been discussed. Here, we describe three levers that institutions can pull to advance learning healthcare systems in precision medicine: (1) changing testing of individual variability (such as genes); (2) changing prescription of treatments on the basis of (genomic) test results; and/or (3) changing the handling of data that link variability and treatment to clinical outcomes. Subsequently, we evaluate how patients can be affected if one of these levers are pulled: (1) patients are tested for different or more factors than before the transformation, (2) patients receive different treatments than before the transformation and/or (3) patients' data obtained through clinical care are used, or used more extensively, for research purposes. Based on an analysis of the aforementioned mechanisms and how these potentially affect patients, we analyze why learning healthcare systems in precision medicine need a different ethical approach and discuss crucial points to consider regarding this approach.
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.