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Falls in Acute Care Patients-Exploring the Predictive Value of the Morse Fall Scale: A Retrospective Analysis
Yanjia Zhang1, Venkataraghavan Ramamoorthy, Anshul Saxena
1Yanjia Zhang is a biostatistician at Baptist Health South Florida, Coral Gables, where Venkataraghavan Ramamoorthy is a health care data research scientist, Donna Lee Armaignac is a senior health care data research scientist, Catherina Chang Martinez is a nurse scientist, Alejandra Angel is a clinical RN educator, Lisette Hurtado is assistant vice president of nursing, and Harold Girado is vice president of nursing. Anshul Saxena is technical director of artificial intelligence and machine learning at Baptist Health South Florida and at the Herbert Wertheim College of Medicine, Florida International University, Miami. Contact author: Venkataraghavan Ramamoorthy, venkataraghavan.ramamoorthy@baptisthealth.net. The authors have disclosed no potential conflicts of interest, financial or otherwise.
Background:
Falls among hospitalized patients are a substantial cause of adverse health outcomes, making prevention efforts an important priority. The Morse Fall Scale (MFS) is a popular tool to assess fall risk, although its predictive usefulness is limited in certain health care settings.
Purpose:
We aimed to explore the predictive value of the MFS, as well as additional factors associated with falls in acute care settings.
Methods:
This retrospective analysis included data from 4,887 adult patients 18 years of age and older stored in the repository of an acute care inpatient hospital. Data were analyzed using multivariate regression models and area under the receiver operating characteristic curves to determine the validity of the MFS as a predictor of falls.
Results:
Of the 4,887 patients admitted to the acute care hospital setting, 343 (7%) experienced a fall. The median age of the cohort was 70.9 years. After propensity score matching, MFS scores did not differ significantly between those who experienced falls and those who did not. Several variables, such as All Patient Refined Diagnosis Related Group severity, environmental factors, unsteady gait, low bowel continence level, lack of alertness, skin moisture status as either dry or moist, benzodiazepine administration, diabetes, previous drug use, discharge status documented in the electronic health record, sepsis, atrial fibrillation, and hospitalization duration, were significantly associated with a greater risk of falls.
Conclusions:
The MFS did not adequately predict falls. Several additional factors were associated with a greater risk of falls. Nurses and other clinicians should incorporate these insights into fall prevention protocols. These findings warrant inclusion in fall risk assessment guidelines, protocols, and fall prevention training programs.
Insights
The Morse Fall Scale (MFS) inadequately predicts patient falls in hospitals. Additional factors like unsteady gait and diabetes significantly increase fall risk, requiring updated prevention protocols.
Area of Science:
- Healthcare research
- Patient safety
- Clinical assessment
Background:
- Hospitalized patient falls are a major cause of adverse health outcomes.
- The Morse Fall Scale (MFS) is widely used but has limited predictive accuracy in some settings.
Purpose of the Study:
- To evaluate the predictive value of the MFS for falls in acute care.
- To identify additional factors associated with patient falls.
Main Methods:
- Retrospective analysis of 4,887 adult inpatient records.
- Multivariate regression and ROC curve analysis to assess MFS validity.
- Propensity score matching was used for analysis.
Main Results:
- 7% of patients experienced falls; MFS scores did not significantly differ between fallers and non-fallers.
- Factors like unsteady gait, diabetes, sepsis, and hospitalization duration were linked to increased fall risk.
- Alertness, continence, and medication administration also showed significant associations.
Conclusions:
- The MFS is not a sufficient predictor of falls in acute care settings.
- Several other clinical and demographic factors significantly increase fall risk.
- Findings should inform updated fall risk assessment guidelines and prevention training for clinicians.
