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 consistently work toward improving patient care and ensuring safety, with particular attention to fall prevention. Falls are a significant cause of unintentional injuries and fatalities among individuals aged 65 and older in the United States, contributing to approximately 2.8 million emergency room visits annually (CDC, 2020). Several risk factors, including cognitive impairment, reduced mobility, and urgent toileting needs, contribute to falls in both hospital and community settings (LeLaurin & Shorr, 2019).

In hospital settings, between 700,000 and 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 by Galet et al. (2018) involving 931 patients indicated that 633 were at an elevated risk of falling due to cognitive dysfunction, mobility impairments, and incontinence. A single fall can lead to extended hospital stays, increased healthcare costs, and poorer patient outcomes.

To mitigate fall risks, OhioHealth’s informatics team developed the Schmid tool, a structured assessment that identifies patients at high risk of falling and facilitates targeted interventions (Lee et al., 2019). The tool evaluates key factors such as mobility, cognitive function, toileting needs, fall history, and medication use. This study explores the effectiveness of the Schmid tool in improving patient safety and overall healthcare outcomes by leveraging informatics-driven solutions.

Introduction

Falls represent a significant public health concern, especially among hospitalized patients. Each year, approximately 2.8 million adults require emergency medical care due to fall-related injuries (LeLaurin & Shorr, 2019). In hospital settings, falls result in prolonged hospitalizations and increased medical expenses, with an annual occurrence of 700,000 to 1 million falls (LeLaurin & Shorr, 2019). Given the substantial impact of falls on patient safety and healthcare costs, effective fall prevention strategies are imperative.

The Schmid tool is a widely used assessment method designed to identify patients at an elevated risk of falling. It evaluates critical factors such as mobility, cognitive function, toileting abilities, medication use, and fall history. Assessing the effectiveness of this tool is essential to enhancing fall prevention strategies and improving patient care outcomes.

Analyzing the Use of the Informatics Model

The Schmid fall risk assessment tool categorizes patients based on four primary domains: mobility, cognitive function, toileting ability, and medication use (Amundsen et al., 2020). Each domain includes specific subcategories that enable healthcare professionals to determine patients requiring additional fall prevention measures.

The mobility domain assesses a patient’s ability to move independently, ranging from fully mobile to completely immobile. Cognitive function is evaluated based on alertness, occasional confusion, persistent disorientation, or unresponsiveness. Similarly, toileting ability is classified from independent function to complete incontinence. Lastly, medication use is assessed based on drug classifications, including anticonvulsants, psychotropics, tranquilizers, and hypnotics, all of which may increase fall risk (Amundsen et al., 2020).

Literature Review

Despite advances in fall prevention strategies, falls continue to present challenges for healthcare institutions. Falls are a leading cause of injury, disability, and mortality among older adults, significantly affecting their quality of life. Moreover, hospitals face financial burdens due to increased healthcare costs and prolonged hospital stays. Since 2008, Medicare and Medicaid have ceased reimbursement for fall-related injuries, emphasizing the importance of implementing effective fall prevention measures (LeLaurin & Shorr, 2019).

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

Conclusion

The study findings emphasize the importance of integrating structured fall prevention tools in hospital settings. Falls remain a significant contributor to injury and mortality, particularly among elderly patients. By adopting informatics-driven solutions such as the Schmid tool, healthcare institutions can reduce fall incidents, improve patient safety, and enhance overall healthcare outcomes.

Schmid Fall Risk Assessment Criteria

Category	Assessment Criteria	Description
Mobility	Mobile (0)	Fully independent with no mobility assistance required.
	Mobile with assistance (1)	Requires caregiver or assistive device for movement.
	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 caregiver help for toileting.
	Incontinent (1c)	Unable to control bladder or bowel function.
Medication Use	Anticonvulsants (1a)	Uses seizure medications, which may increase fall risk.
	Psychotropics (1b)	Takes medications affecting mental state and cognition.
	Tranquilizers (1c)	Uses sedative medications that may cause dizziness.
	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