ReviewFrontiers in digital health2026
Current status, challenges and future development of self-service appointment platforms in hospital radiology departments in China: a narrative review.
Review in Frontiers in digital health, 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, China has accelerated the implementation of precision medicine strategy, integrating accuracy, individualized care and evidence-based decision-making into clinical diagnosis and treatment. Meanwhile, the expansion of smart-hospital and the requirement of Level-5 electronic medical record (EMR) certification have made digital upgrading an indispensable component of radiological services. As a result, self-service appointment is increasingly replacing conventional manual registration and has become an important part of the digital infrastructure of modern radiology departments, with an increasing proportion of administrative pressure, and enhance overall operational performance. Nevertheless, their effectiveness remains restricted by several deficiencies, including limited differentiation among examination workflows, insufficient risk assessment before imaging procedures, inadequate accessibility for older adults, and delayed information exchange between heterogeneous systems; therefore, future improvement should focus on three major directions: (a) AI-supported scheduling tailored to individual patient needs, (b) closed-loop management covering the entire examination process, and (c) coordinated appointment mechanisms involving multiple clinical disciplines, thereby advancing radiology services toward a more refined, intelligent, and patient-centered model.
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.