ReviewOpen medicine (Warsaw, Poland)2025
Leveraging artificial intelligence for collaborative care planning: Innovations and impacts in shared decision-making - A systematic review.
Review in Open medicine (Warsaw, Poland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Shared Decision Making and Advance Care Planning in the Context of Promoting Home Medical Care in Japan: A Narrative Review.Geriatrics & gerontology international · 2026Review
- The IMPACT framework for evaluating generative AI in critical care: development and multinational consensus validation.Annals of intensive care · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Advance care planning is a critical process that brings patients, their families, and healthcare providers together to set goals and outline preferences for future medical treatments, especially when chronic or terminal illnesses are involved. Recently, artificial intelligence has begun playing a key role in shared decision making, offering personalized recommendations based on detailed data analysis to help refine treatment decisions. Objective: This review explores Artificial Intelligence's role in shared decision making, noting its potential to enhance treatment precision, reduce the workload for healthcare providers, and empower patients to engage more actively in their cares. Methods: The systematic review was conducted using the The Preferred Reporting Items for a Systematic Review and Meta-Analysis Statement 2020 guidelines to ensure a comprehensive and transparent approach. We utilized the online tool Rayyan for screening and selection of relevant studies. Results: The review highlights the importance of transparency and clinician involvement to ensure that artificial intelligence remains a supportive, rather than dominant, element in patient care. Emphasizing the human aspect of decision-making is essential, as is fostering a collaborative approach between artificial intelligence and healthcare professionals. Conclusion: Artificial intelligence holds promise in transforming shared decision making, ongoing research must address these implementation challenges to secure its ethical and patient-centered use in healthcare.
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.