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Design and Analysis for Fall Detection System Simplification
Published on: April 6, 2020
A Mixed Effects Model Analysis for Inpatient Falls Using Health Record Data From 72 Hospitals
Cynthia M LaFond1, Ana Christina Perez Moreno1, Vallire Hooper1
1Ascension, St. Louis, Missouri, USA.
Aim/Design:
This retrospective cohort study evaluated the relationship between patient falls, Morse Fall Scale (MFS) items, patient demographics, length of stay and hospital site.
Methods:
Data were acquired from 72 hospitals in a health system. Logistic regression models were conducted including MFS items, demographics, length of stay, and interaction terms. The final mixed effects logistic regression model included significant patient-level covariates as fixed effects and hospital site as a random effect.
Results:
6531 of 978,920 total admissions included a patient fall. Four MFS items (fall history, secondary diagnosis, gait weak/impaired, mental status-overestimates/forgets limitations) and three demographic items (male gender, increased age, longer length of stay) were associated with increased likelihood of falling. Two MFS items (ambulatory aids, intravenous therapy/lock) and Hispanic ethnicity were associated with decreased risk of falling. An interaction effect was present between male gender and mental status. Males who overestimate/forget limitations had 3.16 times higher odds of falling than females oriented to their own ability. The proportion of variance in falls between hospitals was 0.23 and the median odds ratio (MOR) 1.57.
Conclusion:
This study uniquely assessed fall risk at the level of the patient and hospital, using data from nearly 1 million admissions at 72 hospitals. Controlling for patient characteristics, results demonstrate variability in fall risk among hospitals. Research informing hospital differences as well as gender and racial/ethnic differences in falls is needed to identify appropriate interventions.
Implications For Patient Care:
As hospitals increasingly adopt risk-directed fall prevention, assessment tools should be re-evaluated for clinical utility and corresponding prevention practices. The MFS may be enhanced by removing intravenous lock as a risk and screening for additional risks such as medications and medical equipment. Quality improvement efforts must also consider the hospital's environment and processes that may further contribute to fall risk.
Reporting Method:
Authors adhered to STROBE guidelines for reporting.
Patient Contribution:
No Patient or Public Contribution.
Insights
Patient falls are linked to specific Morse Fall Scale items and demographics like male gender and increased age. Hospital site also influences fall risk, indicating a need for tailored prevention strategies.
Area of Science:
- Healthcare research
- Patient safety
- Clinical epidemiology
Background:
- Patient falls represent a significant safety concern in healthcare settings.
- The Morse Fall Scale (MFS) is widely used to assess fall risk.
- Understanding factors contributing to falls is crucial for effective prevention.
Purpose of the Study:
- To evaluate the relationship between patient falls and Morse Fall Scale (MFS) items.
- To examine the association of patient demographics, length of stay, and hospital site with fall risk.
- To identify specific risk factors for patient falls within a large health system.
Main Methods:
- Retrospective cohort study of 978,920 admissions across 72 hospitals.
- Logistic regression models were used to analyze MFS items, demographics, and length of stay.
- A mixed-effects logistic regression model incorporated patient-level covariates and hospital site as a random effect.
Main Results:
- A total of 6,531 falls were recorded.
- Increased fall risk was associated with MFS items (fall history, secondary diagnosis, gait, mental status) and demographics (male gender, increased age, longer stay).
- Decreased fall risk was linked to MFS items (ambulatory aids, IV therapy) and Hispanic ethnicity. Male gender and mental status showed an interaction effect, increasing fall odds by 3.16 times.
Conclusions:
- Significant variability in fall risk exists among hospitals, even after controlling for patient characteristics.
- The MFS may require re-evaluation, potentially removing IV lock and adding medication/equipment screening.
- Future research should explore hospital-specific factors and gender/ethnic differences to inform targeted fall prevention interventions.
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