ReviewTranslational psychiatry2024
Optimising the use of electronic medical records for large scale research in psychiatry.
Review in Translational psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Big data and psychiatry: advances, constraints and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026Article
- Implicit Bias in Large Language Model Diagnosis of Eating Disorders: Experimental Vignette Study.JMIR AI · 2026Article
- Artificial Intelligence in Psychiatry: Five Decades of Progress and Persistent Translational Challenges.Psychiatric research and clinical practice · 2026Article
- Depression as a Disease of White Matter Network Disruption: Learning From Multiple Sclerosis.Biological psychiatry · 2026Review
- Leveraging natural language processing and machine learning to identify chronic conditions from primary care electronic medical records.Scientific reports · 2026Article
- Challenges and solutions to participation in mental health clinical trials: Count Me In 2.0.BMJ mental health · 2026Article
- Leveraging electronic health record data for precision medicine insights: the precision medicine registry at NYU Langone Health.npj health systems · 2026Article
- From Billing Codes to Breakthroughs: Filtering Signal From Noise in Electronic Medical Records-Based Research.The Journal of neuropsychiatry and clinical neurosciences · 2026Article
- The distinctive psychopathology of NMDAR-antibody encephalitis compared with primary psychoses: an international, multicentre, retrospective phenotypic analysis.The lancet. Psychiatry · 2026Article
- Supporting complex mental health care and services research today and beyond: a mini-review of real-world evidence strategies and informed approaches.Frontiers in health services · 2026Review
- Programming literacy for physician-scientists in the AI era.PCN reports : psychiatry and clinical neurosciences · 2025Article
- Large Language Models for Psychiatric Phenotype Extraction from Electronic Health Records.medRxiv : the preprint server for health sciences · 2025Article
- Generalizability of clinical prediction models in mental health.Molecular psychiatry · 2025Observational
- Uncinate Fasciculus Lesion Burden and Anxiety in Multiple Sclerosis.JAMA network open · 2025Article
- Leveraging reddit data for context-enhanced synthetic health data generation to identify low self esteem.Frontiers in psychiatry · 2025Article
- From Paper to Digital: Evaluating Electronic Medical Records and their Compliance with EMA Guidelines in European Clinical Trials.Reviews on recent clinical trials · 2025Article
- Association of Anxiety with Uncinate Fasciculus Lesion Burden in Multiple Sclerosis.medRxiv : the preprint server for health sciences · 2024Article
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
The explosion and abundance of digital data could facilitate large-scale research for psychiatry and mental health. Research using so-called "real world data"-such as electronic medical/health records-can be resource-efficient, facilitate rapid hypothesis generation and testing, complement existing evidence (e.g. from trials and evidence-synthesis) and may enable a route to translate evidence into clinically effective, outcomes-driven care for patient populations that may be under-represented. However, the interpretation and processing of real-world data sources is complex because the clinically important 'signal' is often contained in both structured and unstructured (narrative or "free-text") data. Techniques for extracting meaningful information (signal) from unstructured text exist and have advanced the re-use of routinely collected clinical data, but these techniques require cautious evaluation. In this paper, we survey the opportunities, risks and progress made in the use of electronic medical record (real-world) data for psychiatric research.
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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.