SynthesisAsian Pacific journal of cancer prevention : APJCP2026
Optimizing Care Trajectories with Artificial Intelligence: A Systematic Review and Meta-Analysis.
Synthesis in Asian Pacific journal of cancer prevention : APJCP, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aims to provide a critical and comprehensive summary of existing research on the effectiveness of AI-assisted care pathways by analyzing their impact on hospital stays and readmissions.
methodThis review was conducted in accordance with the PRISMA 2020 guidelines, which specify the selection and analysis steps from the outset. The search strategy targeted three international databases: Scopus, Web of Science (WoS), and PubMed (Medline). The inclusion criteria focused on randomized controlled trials (RCTs), before-and-after studies, quasi-experimental studies, longitudinal studies, and literature reviews involving hospitalized patients without age or pathology restrictions, provided that their care was based on the "clinical pathway" method. Studies that did not meet these criteria were excluded. A PRISMA diagram illustrates the systematic selection process, which resulted in the selection of 31 studies. Data extraction was performed using a structured methodology to ensure the validity and comparability of the results. The description of random sequence generation processes was adequate in 24 studies, partially addressed in five studies, and insufficient in two studies. This limits the ability to assess the risk of bias.
resultsWith regard to economic outcomes, such as length of stay and readmission, most studies [reported] positive effects associated with AI-assisted pathways. The Covidence tool (version 101) was used for the selection and extraction of data on the 18 studies analyzing pathways, AI, length of stay, and readmission. Group analyses indicated that the implementation of clinical protocols incorporating AI optimized care without increasing readmission rates or length of stay.
conclusionHowever, the limited number and heterogeneity of studies on the application of artificial intelligence currently prevent the establishment of a universal framework for the implementation of AI-assisted clinical protocols.
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42169563What 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.