SynthesisFrontiers in digital health2025
Large language models in real-world clinical workflows: a systematic review of applications and implementation.
Synthesis in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 6 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
39 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Usability and User Experience Assessment of Health Care Conversational Agents Using Validated Subjective Instruments: Systematic Review and Comparative Analysis.JMIR human factors · 2026Pooled it
- Large Language Models in Colorectal Cancer Care and Clinical Decision Support: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Applications of Natural Language Processing and Large Language Models for Social Determinants of Health: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Validations and applications of markerless motion capture using OpenCap: a scoping review.Frontiers in digital health · 2026Pooled it
- Large language models in healthcare: applications, evaluation frameworks, and governance pathways - a scoping review and multidimensional framework.Frontiers in digital health · 2026Pooled it
- Knowledge-Practice Performance Gap in Clinical Large Language Models: Systematic Review of 39 Benchmarks.Journal of medical Internet research · 2025Pooled it
- From Model to Product: Understanding and Teaching AI Evidence.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026Article
- [Application effect of LLMs as decision-support tools in emergency burn treatment].Zhonghua shao shang yu chuang mian xiu fu za zhi · 2026Article
- Large language models for tympanostomy patient education: readability and guideline adherence.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- Intelligent Real-Time Healthcare and Biomedical Monitoring Systems: A Narrative Review of AI, IoT, and Emerging Technologies.Bioengineering (Basel, Switzerland) · 2026Review
- AI-Enabled Interpretation Guidance for Hemostasis Testing with TEGDiagnostics (Basel, Switzerland) · 2026Article
- Article
- Large language models in oncology: promise, pitfalls, and the path to real-world adoption.ESMO real world data and digital oncology · 2026Article
- Large Language Models as a New Tool for Therapists in Internet-Based Cognitive Behavioral Therapy: Blinded Clinician Rating Pilot Experiment.JMIR mental health · 2026Article
- Artificial Intelligence in Psychiatry: Five Decades of Progress and Persistent Translational Challenges.Psychiatric research and clinical practice · 2026Article
- Conversational Large Language Models for Vestibular Diagnosis in Outpatient Clinics: Prospective Multicenter Diagnostic Accuracy Study.Journal of medical Internet research · 2026Article
- Iterative Development of an AI-Assisted Data Extraction Tool for Literature Synthesis in Oncology.Cureus · 2026Article
- Review
- Performance of DeepSeek-R1 and ChatGPT-5 in the Generation of North American Spine Society Clinical Guidelines for Adult Vertebral Compression Fractures: Comparative Study.Journal of medical Internet research · 2026Article
- From manual entry to machine precision: challenges and evolution of metadata schema development in collaborative research centers.BMC research notes · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Large language models (LLMs) offer promise for enhancing clinical care by automating documentation, supporting decision-making, and improving communication. However, their integration into real-world healthcare workflows remains limited and under characterized. This systematic review aims to evaluate the literature on real-world implementation of LLMs in clinical workflows, including their use cases, clinical settings, observed outcomes, and challenges. Methods: We searched MEDLINE, Scopus, Web of Science, and Google Scholar for studies published between January 2015 and April 2025 that assessed LLMs in real-world clinical applications. Inclusion criteria were peer-reviewed, full-text studies in English reporting empirical implementation of LLMs in clinical settings. Study quality and risk of bias were assessed using the PROBAST tool. Results: Four studies published between 2024 and 2025 met inclusion criteria. All used generative pre-trained transformers (GPTs). Reported applications included outpatient communication, mental health support, inbox message drafting, and clinical data extraction. LLM deployment was associated with improvements in operational efficiency, user satisfaction, and reduced workload. However, challenges included performance variability across data types, limitations in generalizability, regulatory delays, and lack of post-deployment monitoring. Conclusions: Early evidence suggests that LLMs can enhance clinical workflows, but real-world adoption remains constrained by systemic, technical, and regulatory barriers. To support safe and scalable use, future efforts should prioritize standardized evaluation metrics, multi-site validation, human oversight, and implementation frameworks tailored to clinical settings. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/recorddashboard, PROSPERO CRD420251030069.
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.