Currently submitted to: JMIR mHealth and uHealth
Date Submitted: May 13, 2026
Open Peer Review Period: May 15, 2026 - Jul 10, 2026
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Applications of Digital and Intelligent Technologies in Comprehensive Geriatric Assessment: Scoping Review
ABSTRACT
Background:
Comprehensive geriatric assessment (CGA) is central to the care of older adults with complex and multidimensional needs, but its delivery in routine practice is often limited by substantial time, workforce, and coordination demands. Digital and intelligent technologies are increasingly being applied to CGA delivery across clinical and community settings; however, evidence on their assessment coverage, technological formats, functional features, and architectural patterns remains fragmented and has not been comprehensively synthesized.
Objective:
This scoping review aimed to synthesize existing evidence on the assessment domain coverage, technological formats, functional features, and architectural patterns of digital and intelligent technologies used in CGA for older adults., thereby providing a reference for future research and Clinical practice.
Methods:
A systematic retrieval of relevant research was conducted using databases including PubMed, EMBASE, Web of Science, Scopus and the Cochrane Library, The time frame for the retrieval spans from database inception to March 2026. Relevant studies were screened and analyzed systematically.
Results:
A total of 34 studies published between 2008 and 2025 were included. Digital and intelligent CGA tools were used across inpatient, outpatient, home-based, community, and long-term care settings, with 14 studies (41.2%) involving more than one care setting. The most frequently assessed domains were functional status (30, 88.2%), cognition (28, 82.4%), and nutrition and psychological well-being (24, 70.6%). Web-based systems (21, 61.8%) and applications (16, 47.1%) were the main technological formats. The most common functions were electronic data capture and management (34, 100%), rule-driven clinical decision support (33, 97.1%), and automated scoring (30, 88.2%). Technological formats showed different domain-coverage patterns. Web-based systems were mainly used for functional status, cognition, nutrition, and psychological well-being. EHR/EMR/HIS-integrated systems were more concentrated in medication, comorbidities, and pressure injury, whereas audio-video telecommunication systems covered few. Technologies for continuous objective monitoring, performance-based assessment, and specialised interpretation remained less commonly applied. Overall, existing tools mainly digitised scale-based CGA domains and routinely recorded clinical information, relied on rule-based rather than adaptive decision support, and extended assessment across care settings.
Conclusions:
Digital and intelligent CGA shows potential to make multidomain assessment more structured, efficient, and continuous. However, current systems still have incomplete domain coverage, limited integration of emerging technologies, and insufficient evidence on measurement validation, adaptive intelligence, and downstream care implementation. Future research should use more rigorous designs to evaluate effectiveness and develop age-friendly, interoperable, and care pathway–embedded CGA systems that support earlier risk identification, personalised care planning, and continuous health management for older adults.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.