ArticleThe Yale journal of biology and medicine2012
How the electronic health record will change the future of health care.
Article in The Yale journal of biology and medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses 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, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Designing Clinical Decision Support Systems (CDSS)-A User-Centered Lens of the Design Characteristics, Challenges, and Implications: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Understanding women's, caregivers', and providers' experiences with home-based records: A systematic review of qualitative studies.PloS one · 2018Pooled it
- A scoping review of future research trends and priorities in health systems.Health research policy and systems · 2025Article
- Precision Medicine Landscape of Genomic Testing for Patients With Cancer in the National Institutes of Health All of Us Database Using Informatics Approaches.JCO clinical cancer informatics · 2022Observational
- Personalized treatment options for chronic diseases using precision cohort analytics.Scientific reports · 2021Article
- Physiotherapists' Perspectives on the Threats Facing Their Profession in the Areas of Leadership, Burnout, and Branding: A Pan-Canadian Perspective from the Physio Moves Canada Project, Part 3.Physiotherapy Canada. Physiotherapie Canada · 2020Article
- Assessing the readiness of precision medicine interoperabilty: An exploratory study of the National Institutes of Health genetic testing registry.Journal of innovation in health informatics · 2017Article
- Adoption Factors of the Electronic Health Record: A Systematic Review.JMIR medical informatics · 2016Article
- Sex-specific patterns and differences in dementia and Alzheimer's disease using informatics approaches.Journal of women & aging · 2016Article
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 at 1 institution in 1 country.
Funding
Abstract
Genetic testing is expected to play a critical role in patient care in the near future. Advances in genomic research have the potential to impact medicine in very tangible and direct ways, from carrier screening to disease diagnosis and prognosis to targeted treatments and personalized medicine. However, numerous barriers to widespread adoption of genetic testing continue to exist, and health information technology will be a critical means of addressing these challenges. Electronic health records (EHRs) are a digital replacement for the traditional paper-based patient chart designed to improve the quality of patient care. EHRs have become increasingly essential to managing the wealth of existing clinical information that now includes genetic information extracted from the patient genome. The EHR is capable of changing health care in the future by transforming the way physicians use genomic information in the practice of medicine.
Indexed as
Identifiers
23012585PMC3447201W1497770369What 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.