ArticleJournal of the American Medical Informatics Association : JAMIA2021
Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions.
Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed.
- Evaluation of decision support to wean patients from mechanical ventilation in intensive care: a prospective study reporting clinical and physiological outcomes.Journal of clinical monitoring and computing · 2025Trial
- Person-Centered Technology for Older Adults: Benefits, Limitations, and Considerations in Design and Use.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2026Article
- Clinical Artificial Intelligence Agents in Nephrology: From Prediction to Action Through Workflow-Native Intelligence-A Roadmap for Workflow-Integrated Care.Journal of clinical medicine · 2026Review
- Clinical decision fatigue: a systematic and scoping review with meta-synthesis.Family medicine and community health · 2025Article
- Clinical practice, decision-making, and use of clinical decision support systems in invasive mechanical ventilation: a narrative review.British journal of anaesthesia · 2024Review
- Obstructive respiratory disease simulation device.HardwareX · 2024Article
- Editorial: Personalized therapy in ARDS, volume II.Frontiers in medicine · 2024Article
- A randomized control trial evaluating the advice of a physiological-model/digital twin-based decision support system on mechanical ventilation in patients with acute respiratory distress syndrome.Frontiers in medicine · 2024Article
- Redefining ARDS: a paradigm shift.Critical care (London, England) · 2023Review
- Combining text mining with clinical decision support in clinical practice: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Understanding clinical and biological heterogeneity to advance precision medicine in paediatric acute respiratory distress syndrome.The Lancet. Respiratory medicine · 2023Review
- Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- A scoping review of medical practice variation research within the informatics literature.International journal of medical informatics · 2022Article
- Automated Workflow for Usability Audits in the PHR Realm.International journal of environmental research and public health · 2022Article
- The Future of Critical Care: Optimizing Technologies and a Learning Healthcare System to Potentiate a More Humanistic Approach to Critical Care.Critical care explorations · 2022Article
- Transparent decision support for mechanical ventilation using visualization of clinical preferences.Biomedical engineering online · 2022Article
- Ethical Implications of e-Health Applications in Early Preventive Healthcare.Frontiers in genetics · 2022Article
- Progress toward a science of learning systems for healthcare.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Applying PEST analysis to evaluate the adoption of electronic health records in Tanzanian healthcare: A scoping review.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
68 authors.
Funding
Abstract
Clinical decision-making is based on knowledge, expertise, and authority, with clinicians approving almost every intervention-the starting point for delivery of "All the right care, but only the right care," an unachieved healthcare quality improvement goal. Unaided clinicians suffer from human cognitive limitations and biases when decisions are based only on their training, expertise, and experience. Electronic health records (EHRs) could improve healthcare with robust decision-support tools that reduce unwarranted variation of clinician decisions and actions. Current EHRs, focused on results review, documentation, and accounting, are awkward, time-consuming, and contribute to clinician stress and burnout. Decision-support tools could reduce clinician burden and enable replicable clinician decisions and actions that personalize patient care. Most current clinical decision-support tools or aids lack detail and neither reduce burden nor enable replicable actions. Clinicians must provide subjective interpretation and missing logic, thus introducing personal biases and mindless, unwarranted, variation from evidence-based practice. Replicability occurs when different clinicians, with the same patient information and context, come to the same decision and action. We propose a feasible subset of therapeutic decision-support tools based on credible clinical outcome evidence: computer protocols leading to replicable clinician actions (eActions). eActions enable different clinicians to make consistent decisions and actions when faced with the same patient input data. eActions embrace good everyday decision-making informed by evidence, experience, EHR data, and individual patient status. eActions can reduce unwarranted variation, increase quality of clinical care and research, reduce EHR noise, and could enable a learning healthcare system.
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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.