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 continually strive to enhance care delivery and improve patient outcomes, with a strong focus on ensuring patient safety. Falls are a leading cause of unintentional mortality among individuals aged 65 and older in the United States, accounting for nearly 2.8 million emergency room visits annually (CDC, 2020). Various risk factors contribute to falls, including confusion, limited mobility, and urgent toileting needs, affecting both hospital and community settings (LeLaurin & Shorr, 2019).

Within hospital environments, an estimated 700,000 to 1 million falls occur each year, with an incidence rate of 3.5 to 9.5 falls per 1,000 bed days (LeLaurin & Shorr, 2019). A study conducted by Galet et al. (2018) involving 931 patients revealed that 633 individuals exhibited a higher risk of falls due to cognitive impairments, mobility challenges, and incontinence. A single fall can significantly extend a patient’s hospital stay, increasing healthcare costs and adverse outcomes.

NURS FPX 6414 Assessment 1 Conference Poster Presentation

To mitigate these risks, OhioHealth’s informatics team developed the Schmid tool, a structured assessment designed to identify patients at a heightened risk of falls and implement preventive strategies (Lee et al., 2019). The tool evaluates key factors, including mobility, cognitive function, toileting needs, fall history, and medication use. This study aims to assess the effectiveness of the Schmid tool in enhancing patient safety and improving overall healthcare outcomes by integrating informatics-based solutions.

Introduction

Falls remain a major public health concern, particularly among hospitalized patients. Each year, approximately 2.8 million adults seek emergency treatment for fall-related injuries (LeLaurin & Shorr, 2019). In hospital settings, between 700,000 and 1 million falls occur annually, leading to extended hospital stays and increased medical expenses (LeLaurin & Shorr, 2019). Given the significant impact of falls, healthcare providers must adopt effective risk assessment tools to enhance patient safety.

The Schmid tool is a widely utilized assessment method that helps identify patients at high risk of falling by analyzing key indicators such as mobility, cognitive status, toileting capabilities, fall history, and medication use. Evaluating the effectiveness of this tool is crucial in advancing fall prevention strategies and improving patient care outcomes.

Analyzing the Use of the Informatics Model

The Schmid fall risk assessment tool categorizes a patient’s risk based on four primary domains: mobility, cognition, toileting abilities, and medication use (Amundsen et al., 2020). Each domain is further classified into specific subcategories, allowing healthcare professionals to identify patients who require additional fall prevention interventions. Mobility levels range from fully independent to immobile, while cognitive assessments categorize patients from fully alert to unresponsive. Similarly, toileting abilities range from independent to completely incontinent, and medication use includes classifications such as anticonvulsants, psychotropics, tranquilizers, and hypnotics (Amundsen et al., 2020).

Literature Review

Despite advancements in fall prevention strategies, hospital-related falls continue to pose significant challenges to healthcare institutions. Falls are a leading cause of injury, disability, and mortality among elderly patients, negatively impacting their quality of life. Additionally, hospitals face financial burdens due to increased healthcare costs and extended hospital stays. Since 2008, Medicare and Medicaid have ceased reimbursement for fall-related injuries, further emphasizing the need for proactive fall prevention measures (LeLaurin & Shorr, 2019).

Research highlights the growing concern of hospital readmissions among elderly patients who have sustained fall-related injuries, emphasizing the importance of effective fall prevention strategies and social support systems (Galet et al., 2018). Falls remain the leading cause of injury-related deaths among individuals aged 65 and older in the United States, reinforcing the urgency for evidence-based interventions such as the Schmid tool (CDC, 2020).

Conclusion

The findings of this study underscore the potential benefits of implementing structured fall prevention tools within hospital settings. Falls continue to be a significant cause of injury and mortality, particularly among elderly patients. By integrating informatics-based solutions such as the Schmid tool, healthcare institutions can effectively reduce fall incidents, enhance patient safety, and improve overall healthcare outcomes.

Category	Assessment Criteria	Description
Mobility	Mobile (0)	Fully independent with no mobility assistance required.
	Mobile with assistance (1)	Requires help from a caregiver or assistive device to move.
	Unstable (1b)	Experiences balance issues and is at risk of falling.
	Immobile (0a)	Unable to move independently, requiring full assistance.
Cognition	Alert (0)	Fully aware, oriented, and responsive.
	Occasionally confused (1a)	Experiences intermittent disorientation or forgetfulness.
	Always confused (1b)	Consistently disoriented and requires supervision.
	Unresponsive (0b)	Unable to respond to stimuli or interact meaningfully.
Toileting Abilities	Completely independent (0a)	Manages toileting without assistance.
	Independent with frequency (1a)	Requires frequent restroom visits but manages independently.
	Requires assistance (1b)	Needs help from a caregiver for toileting.
	Incontinent (1c)	Unable to control bladder or bowel function.
Medication Use	Anticonvulsants (1a)	Uses seizure medications, which may contribute to fall risk.
	Psychotropics (1b)	Takes medications that impact mental state and cognition.
	Tranquilizers (1c)	Uses sedative medications that may cause dizziness or drowsiness.
	Hypnotics (1d)	Takes sleep-inducing medications that could impair balance.
	None (0)	No medications contributing to fall risk.

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.

Centers for Disease Control and Prevention (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.