ReviewNPJ digital medicine2019
It is time to learn from patients like mine.
Review in NPJ digital medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed.
- The bottleneck was never data or algorithms: building a learning utility for AI-enabled learning health systems.npj health systems · 2026Article
- A Data-Centric Approach for Health Care and Research in a Health Knowledge Management Platform: Implementation and Requirement-Based Evaluation Study.JMIR medical informatics · 2026Article
- Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study.JMIR medical informatics · 2025Article
- Toward expert-level medical question answering with large language models.Nature medicine · 2025Article
- Human-centered design of a health recommender system for orthopaedic shoulder treatment.BMC medical informatics and decision making · 2025Article
- Current Applications and Future Perspectives of Artificial and Biomimetic Intelligence in Vascular Surgery and Peripheral Artery Disease.Biomimetics (Basel, Switzerland) · 2024Review
- Human-centered Design of a Health Recommender System for Orthopaedic Shoulder Treatment.Research square · 2024Article
- Automated generation of comparator patients in the electronic medical record.Learning health systems · 2024Article
- Building a Learning Health System: Creating an Analytical Workflow for Evidence Generation to Inform Institutional Clinical Care Guidelines.Applied clinical informatics · 2022Article
- Fast prototyping of a local fuzzy search system for decision support and retraining of hospital staff during pandemic.Health information science and systems · 2021Article
- An informatics consult approach for generating clinical evidence for treatment decisions.BMC medical informatics and decision making · 2021Review
- Data Consult Service: Can we use observational data to address immediate clinical needs?Journal of the American Medical Informatics Association : JAMIA · 2021Article
- ACE: the Advanced Cohort Engine for searching longitudinal patient records.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Leveraging Machine Learning and Artificial Intelligence to Improve Peripheral Artery Disease Detection, Treatment, and Outcomes.Circulation research · 2021Review
- Treatment and Monitoring Variability in US Metastatic Breast Cancer Care.JCO clinical cancer informatics · 2021Article
- Enabling Counterfactual Survival Analysis with Balanced Representations.ACM CHIL 2021 : proceedings of the 2021 ACM Conference on Health, Inference, and Learning : April 8-9, 2021, Virtual Event. ACM Conference on Health, Inference, and Learning (2021 : Online) · 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
- Time to reality check the promises of machine learning-powered precision medicine.The Lancet. Digital health · 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
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Clinicians are often faced with situations where published treatment guidelines do not provide a clear recommendation. In such situations, evidence generated from similar patients' data captured in electronic health records (EHRs) can aid decision making. However, challenges in generating and making such evidence available have prevented its on-demand use to inform patient care. We propose that a specialty consultation service staffed by a team of medical and informatics experts can rapidly summarize 'what happened to patients like mine' using data from the EHR and other health data sources. By emulating a familiar physician workflow, and keeping experts in the loop, such a service can translate physician inquiries about situations with evidence gaps into actionable reports. The demand for and benefits gained from such a consult service will naturally vary by practice type and data robustness. However, we cannot afford to miss the opportunity to use the patient data captured every day via EHR systems to close the evidence gap between available clinical guidelines and realities of clinical practice. We have begun offering such a service to physicians at our academic medical center and believe that such a service should be core offering by clinical informatics professional throughout the country. Only if we launch such efforts broadly can we systematically study the utility of learning from the record of routine clinical practice.
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.