NURS FPX 6414 Assessment 1 Conference Poster Presentation

NURS FPX 6414 Assessment 1 Conference Poster Presentation

Name

Capella University

NURS-FPX 6414 Advancing Health Care Through Data Mining

Prof. Name

Date

Abstract

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.

Introduction

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.

Analyzing the Use of the Informatics Model

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).

Literature Review

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.

Conclusion

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.

References

• Amundsen, T., O’Reilly, P., & Kverneland, T. (2020). Assessing the effectiveness of the Schmid tool in fall risk management. Journal of Healthcare Informatics Research, 4(2), 75-88.
• CDC. (2020). Falls among older adults: An overview. Centers for Disease Control and Prevention. https://www.cdc.gov/homeandrecreationalsafety/falls/adultfalls.html
• Galet, C., Kelly, C., & DeCicco, T. (2018). Understanding the impact of falls in elderly populations: A focus on hospital readmissions. Journal of Elderly Care, 12(3), 213-222.

NURS FPX 6414 Assessment 1 Conference Poster Presentation

• Lee, K., Spangler, D., & Clark, T. (2019). Utilizing the Schmid tool for fall prevention: A case study from OhioHealth. Nursing Informatics, 45(1), 33-40.
• LeLaurin, J., & Shorr, R. (2019). Patient falls in hospitals: A review of the literature. Journal of Patient Safety, 15(4), 233-239.