ArticleLearning health systems2018
Transparency and choice in learning healthcare systems.
Article in Learning health systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Building a Sustainable Learning Health Care System for Pregnant and Lactating People: Interview Study Among Data Access Providers.JMIR pediatrics and parenting · 2024Article
- Ethics of AI in Pathology: Current Paradigms and Emerging Issues.The American journal of pathology · 2021Review
- Exploring public concerns for sharing and governance of personal health information: a focus group study.JAMIA open · 2021Article
- Towards a Responsible Transition to Learning Healthcare Systems in Precision Medicine: Ethical Points to Consider.Journal of personalized medicine · 2021Review
- Transparency and choice in learning healthcare systems.Learning health systems · 2018Article
- The Ethics of Artificial Intelligence in Pathology and Laboratory Medicine: Principles and Practice.Academic pathologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Learning healthcare systems rely on potentially sensitive data and biospecimens from patients who typically have no knowledge of secondary uses of these resources for research. While this failure to inform patients of these practices is consistent with human subject regulations for research, these practices risk controversy and a loss of trust in the integrity of healthcare institutions. This article reviews recent controversies in this domain and argues for new institutional practices that entail patient education about secondary uses of data and biospecimens and the opportunity for patient choice in the form of an opt-out system. This approach would enhance transparency and reduce the risk of a loss of public trust in the research enterprise.
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.