ArticleiScience2026
Why health recommender systems struggle to reach clinical practice: A lifecycle-oriented systematic review.
Article in iScience, 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
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Health recommender systems (HRSs) are increasingly being proposed to support personalized and data-driven healthcare decisions, yet their translation into real-world practice remains limited. Existing reviews typically analyze HRSs through isolated dimensions such as algorithms, application domains, or evaluation methods, offering limited insight into why technically advanced systems rarely progress beyond prototypes. Following PRISMA 2020, we reviewed 136 peer-reviewed journal articles published between 2014 and 2025 from Scopus and PubMed. We adopted a lifecycle-oriented analytical framework, examining HRSs across six interrelated dimensions: clinical intent, data governance, recommendation logic, user interaction, evaluation strategy, and clinical integration and ethics. Our findings show that limited clinical adoption is not primarily driven by algorithmic immaturity but by persistent misalignment between intended use, evaluation design, and integration pathways. By reframing translational stagnation as a lifecycle coherence problem rather than a technical one, this review provides a unifying perspective for designing clinically credible and deployment-aware HRSs.
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What Socratic 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 Socratic graph.