Currently submitted to: Journal of Medical Internet Research
Date Submitted: Jul 29, 2026
Open Peer Review Period: Jul 29, 2026 - Sep 23, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited.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.
A Systematic Review of Remote Patient Monitoring for Falls in Older Adults.
ABSTRACT
Background:
One in four older adults falls each year. Remote patient monitoring (RPM), a digital health intervention, can support older adults who fall or are at risk of falling.
Objective:
To synthesize the evidence on RPM interventions for falls and assess their effectiveness, compared to usual care, in reducing fall rates, emergency department visits, hospitalizations, and length of hospital stay in adults 60 years and older.
Methods:
We searched MEDLINE, EMBASE, CINAHL, CENTRAL, ClinicalTrial registry, and ProQuest from inception to May 2026. Selection criteria included adults 60 years and above; randomized, quasi-randomized trials, and observational studies of interventions to monitor and reduce falls in homes, hospitals, and care facilities; any comparator that excludes the intervention. Two reviewers independently screened titles and abstracts, extracted full-text data, and assessed the risk of bias using the ROB-2 and ROBINS-I tools.
Results:
The studies included a pretest-posttest design, crossover trial, non-randomized cluster trial, two RCTs, two prospective cohort studies, and six retrospective cohort studies. The risk of bias in the included studies was low to some concerns to high risk. Twelve studies evaluated fall rate, which is our main outcome of interest, and six studies examined health care utilization. Three studies were home-based, five in nursing homes, and five in hospitals. Interventions were heterogeneous: passive motion sensors, patch devices, video monitoring, nightlight path, and visual and wearable artificial intelligence-based systems were associated with reduced falls, whereas wearable sensors, bed and bedside chair sensors, and bedroom exit monitors produced no beneficial effect on fall rates. RPM may be associated with fewer hospitalizations and emergency department visits, but length of stay was similar in both groups.
Conclusions:
This study shows that the effect of RPM on fall rates varies with interventions and settings. Studies on remote fall monitoring and its effects on acute healthcare use are needed. Our review highlights the need for more trials to draw a reasonable conclusion on the impact of RPM on fall-related outcomes. Clinical Trial: PROSPERO: CRD42025636565
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