ArticleJournal of the American College of Radiology : JACR2018
Performing an Informatics Consult: Methods and Challenges.
Article in Journal of the American College of Radiology : JACR, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Oncoplastic Breast Surgery: Optimizing Resection Margins in Addition to Aesthetic Outcomes.Aesthetic plastic surgery · 2026Article
- Human-centered design of a health recommender system for orthopaedic shoulder treatment.BMC medical informatics and decision making · 2025Article
- Risks of peri- and postoperative complications with glucagon-like peptide-1 receptor agonists.Diabetes, obesity & metabolism · 2024Observational
- Human-centered Design of a Health Recommender System for Orthopaedic Shoulder Treatment.Research square · 2024Article
- The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19.Social science & medicine (1982) · 2022Review
- 'What is the risk to me from COVID-19?': Public involvement in providing mortality risk information for people with 'high-risk' conditions for COVID-19 (OurRisk.CoV).Clinical medicine (London, England) · 2021Article
- An informatics consult approach for generating clinical evidence for treatment decisions.BMC medical informatics and decision making · 2021Review
- ACE: the Advanced Cohort Engine for searching longitudinal patient records.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Treatment and Monitoring Variability in US Metastatic Breast Cancer Care.JCO clinical cancer informatics · 2021Article
- Personalized treatment options for chronic diseases using precision cohort analytics.Scientific reports · 2021Article
- A scoping review of clinical decision support tools that generate new knowledge to support decision making in real time.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- What You Need to Know Before Implementing a Clinical Research Data Warehouse: Comparative Review of Integrated Data Repositories in Health Care Institutions.JMIR formative research · 2020Review
- Opportunities and challenges in using real-world data for health care.The Journal of clinical investigation · 2020Review
- Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records.Cancer research · 2019Review
- It is time to learn from patients like mine.NPJ digital medicine · 2019Review
- Answering real-world clinical questions using large language model, retrieval-augmented generation, and agentic systems.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Our health care system is plagued by missed opportunities, waste, and harm. Data generated in the course of care are often underutilized, scientific insight goes untranslated, and evidence is overlooked. To address these problems, we envisioned a system where aggregate patient data can be used at the bedside to provide practice-based evidence. To create that system, we directly connect practicing physicians to clinical researchers and data scientists through an informatics consult. Our team processes and classifies questions posed by clinicians, identifies the appropriate patient data to use, runs the appropriate analyses, and returns an answer, ideally in a 48-hour time window. Here, we discuss the methods that are used for data extraction, processing, and analysis in our consult. We continue to refine our informatics consult service, moving closer to a learning health care system.
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.