ArticleClinical nursing research2026
Predicting Falls With the Morse Fall Scale: A Retrospective Assessment at the Veterans Health Administration.
Article in Clinical nursing research, 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accidental falls are the second most prevalent adverse event within hospital settings, including U.S.'s Veterans Health Administration (VHA), often resulting in injury and prolonging patient recovery. The Morse Fall Scale (MFS) is widely used to assess fall risk within patient settings. Despite its known limitations, it remains a key tool for determining which patients are at risk for falls across healthcare institutions. Veterans with a completed MFS, Care Assessment Need (CAN), and Charlson Comorbidity Index (CCI), admitted to a VHA hospital from July 1, 2020, to June 30, 2022, were included in this retrospective analysis. MFS total scores were captured using electronic health record data from the VHA's national Corporate Data Warehouse. Veterans were identified as having a documented fall through clinical notes. Logistic regression models were used to evaluate the tool's performance at predicting falls. Among 440,771 Veterans, 14,458 (3.3%) had a documented fall during their inpatient stay. On average, those who experienced a fall had higher MFS scores. However, despite this trend, this tool exhibited poor discrimination in the likelihood of falls. Although incorporating patient demographics, the CAN, and CCI into the model improved performance, the model still performed poorly when assessing fall risk. Although the MFS is a required component of clinical workflow in many hospital systems, including VHA, its suboptimal discrimination of fall risk undermines its practical utility. Improved risk models are needed to assess fall risk and from which appropriate fall prevention measures can be initiated.
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.