ArticleJournal of medical Internet research2022
Implementation Frameworks for Artificial Intelligence Translation Into Health Care Practice: Scoping Review.
Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers, 9 of them syntheses that pooled it.
What it found
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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
107 citing papers in PubMed, 9 syntheses or guidelines pooled it.
- Facilitators and Barriers to Implementing AI in Routine Medical Imaging: Systematic Review and Qualitative Analysis.Journal of medical Internet research · 2025Pooled it
- Challenges in Implementing Artificial Intelligence in Breast Cancer Screening Programs: Systematic Review and Framework for Safe Adoption.Journal of medical Internet research · 2025Pooled it
- Implementation of Machine Learning Applications in Health Care Organizations: Systematic Review of Empirical Studies.Journal of medical Internet research · 2024Pooled it
- A 25-Year Retrospective of the Use of AI for Diagnosing Acute Stroke: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Availability of Evidence for Predictive Machine Learning Algorithms in Primary Care: A Systematic Review.JAMA network open · 2024Pooled it
- Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers.Journal of medical Internet research · 2024Pooled it
- Health Care Professionals' Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-Synthesis.JMIR mental health · 2024Pooled it
- Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain.Journal of the American Medical Informatics Association : JAMIA · 2024Pooled it
- Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework.Journal of the American Medical Informatics Association : JAMIA · 2023Pooled it
- Integrating Artificial Intelligence in Nursing Practice With Decubitus Risk Prediction Alerts: A Pilot Process Evaluation.Journal of clinical nursing · 2026Article
- AI for Health Care Quality and Patient Safety: Scoping Review of Diagnostic, Predictive, and Decision Support Applications.Journal of medical Internet research · 2026Article
- Construction and validation of a liquid neural network-based prediction model and bedside tool for spontaneous passage of common bile duct stones.Surgical endoscopy · 2026Article
- Factors Influencing Physician Adherence to Venous Thromboembolism Risk Assessment Model Recommendations: A Best-Worst Scaling.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2026Article
- Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.International urology and nephrology · 2026Review
- Medical artificial intelligence and the right to health.BMC medical ethics · 2026Article
- Implementing a Commercial AI Fracture Detection Tool in Health Care Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability Framework: A Formative Evaluation Study.JMIR formative research · 2026Article
- Artificial Intelligence in Peripheral Artery Disease: A Science Advisory From the American Heart Association.Circulation. Population health and outcomes · 2026Review
- Framework for artificial intelligence implementation research in healthcare: synthesizing current evidence on barriers and facilitators.NPJ digital medicine · 2026Article
- From Pilot Trap to Institutional Capacity: A Governance Framework for Sustainable Clinical AI Implementation in Health Systems.Journal of medical Internet research · 2026Article
- Investigating the Implementation and Impact of AI-Assisted Fall Prevention in Hospitals: Protocol for a Multicenter, Multimethod Observational Study in Sweden (SAFE).JMIR research protocols · 2026Observational
47 more citing papers are in PubMed but not listed here.
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
backgroundSignificant efforts have been made to develop artificial intelligence (AI) solutions for health care improvement. Despite the enthusiasm, health care professionals still struggle to implement AI in their daily practice.
objectiveThis paper aims to identify the implementation frameworks used to understand the application of AI in health care practice.
methodsA scoping review was conducted using the Cochrane, Evidence Based Medicine Reviews, Embase, MEDLINE, and PsycINFO databases to identify publications that reported frameworks, models, and theories concerning AI implementation in health care. This review focused on studies published in English and investigating AI implementation in health care since 2000. A total of 2541 unique publications were retrieved from the databases and screened on titles and abstracts by 2 independent reviewers. Selected articles were thematically analyzed against the Nilsen taxonomy of implementation frameworks, and the Greenhalgh framework for the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) of health care technologies.
resultsIn total, 7 articles met all eligibility criteria for inclusion in the review, and 2 articles included formal frameworks that directly addressed AI implementation, whereas the other articles provided limited descriptions of elements influencing implementation. Collectively, the 7 articles identified elements that aligned with all the NASSS domains, but no single article comprehensively considered the factors known to influence technology implementation. New domains were identified, including dependency on data input and existing processes, shared decision-making, the role of human oversight, and ethics of population impact and inequality, suggesting that existing frameworks do not fully consider the unique needs of AI implementation.
conclusionsThis literature review demonstrates that understanding how to implement AI in health care practice is still in its early stages of development. Our findings suggest that further research is needed to provide the knowledge necessary to develop implementation frameworks to guide the future implementation of AI in clinical practice and highlight the opportunity to draw on existing knowledge from the field of implementation science.
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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.