ArticleBMJ open2021
Stakeholders' views on the organisational factors affecting application of artificial intelligence in healthcare: a scoping review protocol.
Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Digital interaction in practice (DIP) between patient, general practitioner and home care services. Evaluation of a pilot study.Scandinavian journal of primary health care · 2026Article
- Healthcare professionals' perspectives on artificial intelligence in clinical practice: a systematic review of facilitators and challenges.Oxford open digital health · 2026Article
- Analysing the Suitability of Artificial Intelligence in Healthcare and the Role of AI Governance.Health care analysis : HCA : journal of health philosophy and policy · 2025Article
- Willingness, preference, and resistance to frailty intervention for older gastric cancer based on stakeholder perspective: a qualitative study.BMC geriatrics · 2025Article
- Unlocking Patient Resistance to AI in Healthcare: A Psychological Exploration.European journal of investigation in health, psychology and education · 2025Article
- Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre.BMC health services research · 2024Article
- Expectations and attitudes towards medical artificial intelligence: A qualitative study in the field of stroke.PloS one · 2023Article
- Design considerations for a hierarchical semantic compositional framework for medical natural language understanding.PloS one · 2023Article
- Identifying performance factors of long-term care facilities in the context of the COVID-19 pandemic: a scoping review protocol.Systematic reviews · 2022Article
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
No grant is acknowledged in the PubMed record.
Abstract
introductionArtificial intelligence (AI) offers great potential for transforming healthcare delivery leading to better patient-outcomes and more efficient care delivery. However, despite these advantages, integration of AI in healthcare has not kept pace with technological advancements. Previous research indicates the importance of understanding various organisational factors that shape integration of new technologies in healthcare. Therefore, the aim of this study is to provide an overview of the existing organisational factors influencing adoption of AI in healthcare from the perspectives of different relevant stakeholders. By conducting this review, the various organisational factors that facilitate or hinder AI implementation in healthcare could be identified. METHODS AND ANALYSIS: This study will follow the Joanna Briggs Institute framework, which includes the following stages: (1) defining and aligning objectives and questions, (2) developing and aligning the inclusions criteria with objectives and questions, (3) describing the planned approach to evidence searching and selection, (4) searching for the evidence, (5) selecting the evidence, (6) extracting the evidence, (7) charting the evidence, and summarising the evidence with regard to the objectives and questions.The databases searched will be MEDLINE (Ovid), CINAHL (Plus), PubMed, Cohrane Library, Scopus, MathSciNet, NICE Evidence, OpenGrey, O'REILLY and Social Care Online from January 2000 to June 2021. Search results will be reported based on The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews guidelines. The review will adopt diffusion of innovations theory, technology acceptance model and stakeholder theory as guiding conceptual models. Narrative synthesis will be used to integrate the findings. ETHICS AND DISSEMINATION: Ethics approval will not be sought for this scoping review as it only includes information from previously published studies. The results will be disseminated through publication in a peer-reviewed journal. In addition, to ensure its findings reach relevant stakeholders, they will be presented at relevant conferences.
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.