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Healthcare professionals strive to enhance care delivery to improve patient outcomes, with a key focus on prioritizing and maintaining patient safety. Falls are the leading cause of unintentional mortality among individuals aged 65 and older in the United States (CDC, 2020), resulting in approximately 2.8 million elderly individuals seeking emergency room treatment annually (CDC, 2020). Several factors, such as confusion, mobility limitations, and urgent toileting needs, contribute to the increased risk of falls among the elderly, both in and out of hospital settings (LeLaurin & Shorr, 2019).
In the hospital, between 700,000 and 1 million patients experience falls each year (LeLaurin & Shorr, 2019), with an incidence rate ranging from 3.5 to 9.5 falls per 1000 bed days (LeLaurin & Shorr, 2019). Galet et al. (2018) conducted a study involving 931 patients, identifying 633 individuals at the highest risk of falls due to mental or physical impairments and incontinence. The occurrence of a single fall can prolong a patient’s hospital stay.
To mitigate the risk of falls, OhioHealth’s informatics team developed the Schmid tool (Lee et al., 2019) to identify high-risk individuals and implement appropriate preventive measures. The Schmid tool assesses various factors, including mobility, mental status, toileting abilities, history of falls, and current medications. This study aims to evaluate the Schmid tool’s effectiveness in enhancing patient safety and overall healthcare outcomes by utilizing data in conjunction with informatics models.
Introduction
Annually, approximately 2.8 million adults seek emergency department care for fall-related injuries (LeLaurin & Shorr, 2019). Hospitalized patients also face a significant risk of falling, with between 700,000 and 1 million falls occurring each year (LeLaurin & Shorr, 2019). Falls contribute to extended hospital stays, leading to increased healthcare costs.
The Schmid tool is utilized to identify patients at high risk of falls by considering factors such as mobility, mental status, toileting abilities, history of falls, and medications. Evaluating the Schmid tool’s effectiveness is essential to enhance patient safety and healthcare outcomes.
Analyzing the Use of the Informatics Model
The Schmid fall risk scale categorizes a patient’s fall risk into four main categories: mobility, cognition, toileting abilities, and medication usage (Amundsen et al., 2020). Mobility includes four subcategories: mobile (0), mobile with assistance (1), unstable (1b), and immobile (0a). Cognition is assessed as alert (0), occasionally confused (1a), always confused (1b), or unresponsive (0b). Toileting abilities are classified as completely independent (0a), independent with frequency (1a), requiring assistance (1b), or incontinent (1c). Finally, medication usage is categorized into various medications such as anticonvulsants (1a), psychotropics (1b), tranquilizers (1c), hypnotics (1d), or none (0) (Amundsen et al., 2020).
Despite a gradual decline, in-hospital falls remain a significant concern for healthcare institutions, as they are a leading cause of harm to patients. Patients suffer increased injury and fatality rates, leading to a diminished quality of life, while healthcare providers face rising expenses due to prolonged hospital stays and medical care costs. Since 2008, Medicare and Medicaid no longer cover fall-related injuries for hospitalization reimbursement (LeLaurin & Shorr, 2019). Hospitals must take preventive measures to reduce patient falls due to the substantial financial burden they impose.
Recent studies indicate an alarming trend of readmissions among older patients with traumatic injuries, such as falls, highlighting the need for social support networks and fall prevention initiatives for the elderly (Galet et al., 2018). Falls are the primary cause of injury and mortality among individuals aged 65 and older in the United States (CDC, 2020), emphasizing the importance of fall prevention strategies.
Conclusion
The comprehensive approach outlined in this study demonstrates the potential to reduce hospital falls. Previous research has identified falls as the leading cause of death in the United States. By employing the informatics model throughout the development of the Schmid tool for quality improvement, this study observed a significant reduction in the incidence of falls.
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