ReviewJAMIA open2023
How can artificial intelligence decrease cognitive and work burden for front line practitioners?
Review in JAMIA open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 3 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
49 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Reimagining nursing practice in the era of AI: a qualitative systematic review and meta-synthesis of nurses' lived experiences.Journal of health, population, and nutrition · 2026Pooled it
- How Does Medical Artificial Intelligence Revolutionize Physician Productivity?Yonsei medical journal · 2026Pooled it
- Artificial intelligence in endoscopy and colonoscopy: a comprehensive bibliometric analysis of global research trends.Frontiers in medicine · 2025Pooled it
- AI-Based EMG Reporting: A Randomized Controlled Trial.Journal of neurology · 2025Trial
- An Electronic Health Record-Integrated, Large Language Model-Powered Tool to Triage Surgical Patients.JAMA network open · 2026Article
- Automated Health Care Messages and Unexpected Patient Responses.JAMA network open · 2026Article
- Real-World Data Needs Real-World Doctors: When Automation Advances Faster Than Clinical Workflow.Journal of participatory medicine · 2026Article
- IFSO Survey: Use of Large Language Models (LLMs) by Metabolic Bariatric Surgeons and Integrated Health Professionals.Obesity surgery · 2026Article
- Human-centered digital ecosystem: safeguarding healthcare workers' sleep, ergonomics, and occupational health.Frontiers in public health · 2026Article
- Using AI to enhance healthcare resource management and allocation: A focus on the autism community in Alabama.PloS one · 2026Article
- The unintended negative consequences of artificial intelligence use for psychologists.Frontiers in psychology · 2026Article
- From predictive algorithms to generative intelligence: a decadal bibliometric mapping of global research frontiers in AI-driven mental health (2016-2025).Australian journal of psychology · 2026Review
- Optimal presentation of decision explanations: investigating the effects of explainability and reliability on medical diagnostic performance with conversational AI.Frontiers in psychology · 2026Article
- Data in Diabetic Foot Care: From Current State to a Management Framework for Implementation.Journal of clinical medicine · 2025Review
- Enhancing segmentation accuracy of the common iliac vein in OLIF51 surgery in intraoperative endoscopic video through gamma correction: a deep learning approach.International journal of computer assisted radiology and surgery · 2025Article
- Primary care physician digital health profile and burnout: an international cross-sectional study.European journal of public health · 2025Article
- Shifts in emergency physicians' attitudes toward large language model-based documentation: a pre- and post-implementation study.Scientific reports · 2025Article
- AI-generated neurology consultation summaries improve efficiency and reduce documentation burden in the emergency department.Scientific reports · 2025Article
- Artificial Intelligence for Cardiovascular Care in Action: From Learning to Implementation in Health Systems.JACC. Advances · 2025Review
- Use of Ambient AI Scribes to Reduce Administrative Burden and Professional Burnout.JAMA network open · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has tremendous potential to improve the cognitive and work burden of clinicians across a range of clinical activities, which could lead to reduced burnout and better clinical care. The recent explosion of generative AI nicely illustrates this potential. Developers and organizations deploying AI have a responsibility to ensure AI is designed and implemented with end-user input, has mechanisms to identify and potentially reduce bias, and that the impact on cognitive and work burden is measured, monitored, and improved. This article focuses specifically on the role AI can play in reducing cognitive and work burden, outlines the critical issues associated with the use of AI, and serves as a call to action for vendors and users to work together to develop functionality that addresses these challenges.
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.