Evidence map›Paper›PMID 39806932›Full record

ArticleJMIR human factors2025

Predictive Factors and the Predictive Scoring System for Falls in Acute Care Inpatients: Retrospective Cohort Study.

Chihiro Saito, Eiji Nakatani, Hatoko Sasaki, Naoko E Katsuki, Masaki Tago, Kiyoshi Harada

Abstract read
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Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Chihiro SaitoDepartment of Nursing, Shizuoka General Hospital, Shizuoka, Japan.ORCID 0009-0001-1753-6771
Eiji NakataniGraduate School of Public Health, Shizuoka Graduate University of Public Health, 4-27-2, Kita-ando, Aoi-ku, Shizuoka, 420-0881, Japan, 81 54-295-5400, 81 54-248-3520.ORCID 0000-0002-4876-446X
Hatoko SasakiGraduate School of Public Health, Shizuoka Graduate University of Public Health, 4-27-2, Kita-ando, Aoi-ku, Shizuoka, 420-0881, Japan, 81 54-295-5400, 81 54-248-3520.ORCID 0000-0002-5785-0482
Naoko E KatsukiDepartment of General Medicine, Saga University Hospital, Saga, Japan.ORCID 0000-0002-9599-5287
Masaki TagoDepartment of General Medicine, Saga University Hospital, Saga, Japan.ORCID 0000-0003-1092-1834
Kiyoshi HaradaDepartment of Medical Safety, Shizuoka General Hospital, Shizuoka, Japan.ORCID 0009-0008-6847-1622

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Falls in hospitalized patients are a serious problem, resulting in physical injury, secondary complications, impaired activities of daily living, prolonged hospital stays, and increased medical costs. Establishing a fall prediction scoring system to identify patients most likely to fall can help prevent falls among hospitalized patients. objectives: This study aimed to identify predictive factors of falls in acute care hospital patients, develop a scoring system, and evaluate its validity. Methods: This single-center, retrospective cohort study involved patients aged 20 years or older admitted to Shizuoka General Hospital between April 2019 and September 2020. Demographic data, candidate predictors at admission, and fall occurrence reports were collected from medical records. The outcome was the time from admission to a fall requiring medical resources. Two-thirds of cases were randomly selected as the training set for analysis, and univariable and multivariable Cox regression analyses were used to identify factors affecting fall risk. We scored the fall risk based on the estimated hazard ratios (HRs) and constructed a fall prediction scoring system. The remaining one-third of cases was used as the test set to evaluate the predictive performance of the new scoring system. Results: A total of 13,725 individuals were included. During the study period, 2.4% (326/13,725) of patients experienced a fall. In the training dataset (n=9150), Cox regression analysis identified sex (male: HR 1.60, 95% CI 1.21-2.13), age (65 to <80 years: HR 2.26, 95% CI 1.48-3.44; ≥80 years: HR 2.50, 95% CI 1.60-3.92 vs 20-<65 years), BMI (18.5 to <25 kg/m²: HR 1.36, 95% CI 0.94-1.97; <18.5 kg/m²: HR 1.57, 95% CI 1.01-2.44 vs ≥25 kg/m²), independence degree of daily living for older adults with disabilities (bedriddenness rank A: HR 1.81, 95% CI 1.26-2.60; rank B: HR 2.03, 95% CI 1.31-3.14; rank C: HR 1.23, 95% CI 0.83-1.83 vs rank J), department (internal medicine: HR 1.23, 95% CI 0.92-1.64; emergency department: HR 1.81, 95% CI 1.26-2.60 vs department of surgery), and history of falls within 1 year (yes: HR 1.66, 95% CI 1.21-2.27) as predictors of falls. Using these factors, we developed a fall prediction scoring system categorizing patients into 3 risk groups: low risk (0-4 points), intermediate risk (5-9 points), and high risk (10-15 points). The c-index indicating predictive performance in the test set (n=4575) was 0.733 (95% CI 0.684-0.782). Conclusions: We developed a new fall prediction scoring system for patients admitted to acute care hospitals by identifying predictors of falls in Japan. This system may be useful for preventive interventions in patient populations with a high likelihood of falling in acute care settings.

Indexed as

Accidental FallsInpatientsAdultAgedAged, 80 and overFemaleHospitalizationHumansJapanMaleMiddle AgedRetrospective StudiesRisk AssessmentRisk Factorsacute care hospitalfallsinpatient fallspredictive factorrisk factors

Identifiers

PMID39806932
PMCPMC11897365

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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.