ArticleJournal of the American Medical Informatics Association : JAMIA2020
Recommendations for improving national clinical datasets for health equity research.
Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations.The Lancet. Digital health · 2025Pooled it
- Article
- MIDAS: a technology-enabled hub-and-spoke system for the collection and dissemination of high-quality medical datasets in India.BMC medical informatics and decision making · 2025Article
- Avenues for Strengthening PCORnet's Capacity to Advance Patient-Centered Economic Outcomes in Patient-Centered Outcomes Research (PCOR).Medical care · 2023Article
- The value of standards for health datasets in artificial intelligence-based applications.Nature medicine · 2023Article
- Reducing Adolescent and Young Adult Cancer Outcome Disparities Through Optimized Care Delivery: A Blueprint from the Children's Oncology Group.Journal of adolescent and young adult oncology · 2023Review
- A Scoping Review of Approaches to Improving Quality of Data Relating to Health Inequalities.International journal of environmental research and public health · 2022Article
- Commentary: Quantifying the health needs of migrants in vulnerable circumstances registered with a nurse-led primary care service.Journal of research in nursing : JRN · 2022Article
- Toward diversity, equity, and inclusion in informatics, health care, and society.Journal of the American Medical Informatics Association : JAMIA · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Health and healthcare disparities continue despite clinical, research, and policy efforts. Large clinical datasets may not contain data relevant to healthcare disparities and leveraging these for research may be crucial to improve health equity. The Health Disparities Collaborative Research Group was commissioned by the Patient-Centered Outcomes Research Institute to examine the data science needs for quality and complete data and provide recommendations for improving data science around health disparities. The group convened content experts, researchers, clinicians, and patients to produce these recommendations and suggestions for implementation. Our desire was to produce recommendations to improve the usability of healthcare datasets for health equity research. The recommendations are summarized in 3 primary domains: patient voice, accurate variables, and data linkage. The implementation of these recommendations in national datasets has the potential to accelerate health disparities research and promote efforts to reduce health inequities.
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.