Name
Capella University
NURS-FPX 6414 Advancing Health Care Through Data Mining
Prof. Name
Date
Healthcare professionals are dedicated to enhancing care delivery to improve patient outcomes, with a significant emphasis on prioritizing and ensuring patient safety. In the United States, falls represent the primary cause of unintentional mortality among individuals aged 65 and older (CDC, 2020), leading to approximately 2.8 million elderly individuals seeking emergency room treatment each year (CDC, 2020). Various factors contribute to the heightened risk of falls in this population, including confusion, mobility limitations, and urgent toileting needs, occurring both within hospital environments and in the community (LeLaurin & Shorr, 2019).
In hospitals, an estimated 700,000 to 1 million patients experience falls annually, with an incidence rate ranging from 3.5 to 9.5 falls per 1,000 bed days (LeLaurin & Shorr, 2019). A study by Galet et al. (2018) involving 931 patients found that 633 individuals were at the highest risk of falls due to mental or physical impairments and incontinence. A single fall can extend a patient’s hospital stay significantly.
To address the risk of falls, OhioHealth’s informatics team created the Schmid tool (Lee et al., 2019), designed to identify high-risk individuals and implement effective preventive strategies. The Schmid tool evaluates multiple factors, including mobility, mental status, toileting abilities, fall history, and current medications. The goal of this study is to assess the effectiveness of the Schmid tool in enhancing patient safety and overall healthcare outcomes by integrating data with informatics models.
Each year, around 2.8 million adults seek emergency care for fall-related injuries (LeLaurin & Shorr, 2019). Hospitalized patients are particularly vulnerable, with between 700,000 and 1 million falls occurring annually (LeLaurin & Shorr, 2019). These falls often lead to extended hospital stays, contributing to increased healthcare costs.
The Schmid tool serves as a means to identify patients at high risk of falls by analyzing factors such as mobility, mental status, toileting abilities, fall history, and medications. Assessing the effectiveness of the Schmid tool is crucial for improving patient safety and healthcare outcomes.
The Schmid fall risk scale categorizes a patient’s fall risk into four main domains: mobility, cognition, toileting abilities, and medication use (Amundsen et al., 2020). The mobility domain comprises four subcategories: mobile (0), mobile with assistance (1), unstable (1b), and immobile (0a). Cognition is evaluated as alert (0), occasionally confused (1a), always confused (1b), or unresponsive (0b). The toileting abilities are classified as completely independent (0a), independent with frequency (1a), requiring assistance (1b), or incontinent (1c). Finally, medication usage is categorized into several types, including anticonvulsants (1a), psychotropics (1b), tranquilizers (1c), hypnotics (1d), or none (0) (Amundsen et al., 2020).
Category | Subcategories | Description |
---|---|---|
Mobility | Mobile (0) | Fully independent |
Mobile with assistance (1) | Requires help to move | |
Unstable (1b) | Has difficulty maintaining balance | |
Immobile (0a) | Cannot move independently | |
Cognition | Alert (0) | Fully aware and responsive |
Occasionally confused (1a) | Periodically disoriented | |
Always confused (1b) | Consistently disoriented | |
Unresponsive (0b) | Does not respond to stimuli | |
Toileting | Completely independent (0a) | Manages toileting without assistance |
Independent with frequency (1a) | Requires frequent trips to the restroom | |
Requires assistance (1b) | Needs help to use the toilet | |
Incontinent (1c) | Unable to control bladder/bowel function | |
Medications | Anticonvulsants (1a) | Taking medications for seizure disorders |
Psychotropics (1b) | Medications affecting mental state | |
Tranquilizers (1c) | Drugs for anxiety/sedation | |
Hypnotics (1d) | Medications for sleep issues | |
None (0) | No relevant medications |
Despite a gradual decline, falls occurring in hospitals continue to be a major concern for healthcare facilities, representing a leading cause of patient harm. Patients affected by falls often experience increased rates of injury and mortality, which adversely affects their quality of life. Simultaneously, healthcare providers encounter rising costs due to extended hospital stays and increased medical care needs. Since 2008, Medicare and Medicaid have stopped covering fall-related injuries for hospitalization reimbursement (LeLaurin & Shorr, 2019). Consequently, hospitals must take proactive measures to reduce patient falls due to the significant financial burden they impose.
Recent studies reveal a troubling trend of readmissions among older patients suffering from traumatic injuries, such as falls, underscoring the necessity for robust social support systems and fall prevention strategies for the elderly (Galet et al., 2018). Falls remain the primary cause of injury and mortality for individuals aged 65 and older in the United States (CDC, 2020), highlighting the urgent need for effective fall prevention initiatives.
The comprehensive approach detailed in this study illustrates the potential to decrease the incidence of falls within hospitals. Prior research has established falls as a leading cause of death in the United States. By integrating the informatics model in developing the Schmid tool for quality improvement, this study has observed a noteworthy reduction in the frequency of falls.
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