NURS FPX 6414 Assessment 1 Conference Poster Presentation

Name

Capella university

NURS-FPX 6414 Advancing Health Care Through Data Mining

Prof. Name

Date

Abstract

In the ever-evolving healthcare environment, professionals continuously seek ways to enhance care delivery and optimize patient outcomes, with a significant emphasis on patient safety. Falls remain a primary concern, especially among adults aged 65 and older in the United States, leading to approximately 2.8 million emergency department visits each year (Centers for Disease Control and Prevention [CDC], 2020). A range of risk factors, such as cognitive impairment, restricted mobility, and urgent toileting needs, contribute to fall incidents across hospital and community settings (LeLaurin & Shorr, 2019).

Within hospital environments, falls account for roughly 700,000 to 1 million incidents annually, with an occurrence rate between 3.5 and 9.5 falls per 1,000 bed days (LeLaurin & Shorr, 2019). Galet et al. (2018) conducted a study involving 931 patients and found that 633 individuals were at an elevated fall risk due to challenges including impaired cognition, reduced mobility, and incontinence. These incidents not only threaten patient health but also result in longer hospital stays and increased healthcare expenses.

To address this issue, OhioHealth’s informatics team introduced the Schmid tool—a structured assessment instrument designed to pinpoint patients at high risk of falling and implement preventive interventions accordingly (Lee et al., 2019). This tool evaluates essential factors such as mobility, mental status, toileting needs, fall history, and medication profiles. The purpose of this study is to analyze the Schmid tool’s role in bolstering patient safety and promoting favorable healthcare outcomes by integrating informatics-based solutions.

Introduction

Falls persist as a critical public health issue, particularly for hospitalized patients. Each year, nearly 2.8 million older adults require emergency medical care following fall-related injuries (LeLaurin & Shorr, 2019). Within clinical settings, estimates suggest that between 700,000 and 1 million falls occur annually, often resulting in prolonged hospitalizations and escalating medical costs (LeLaurin & Shorr, 2019). Recognizing the serious consequences of falls, healthcare organizations must adopt effective assessment tools to detect high-risk patients and implement timely preventive measures.

The Schmid fall risk assessment tool has gained recognition as a practical method for identifying individuals at risk of falling by evaluating crucial indicators such as cognitive function, mobility, toileting abilities, fall history, and medication use. Assessing the efficacy of this tool is vital for refining fall prevention efforts and enhancing the quality of patient care. By focusing on early risk detection and intervention, healthcare teams can better manage and reduce fall-related incidents within their institutions.

Analyzing the Use of the Informatics Model

The Schmid fall risk assessment tool operates by categorizing a patient’s fall risk based on four primary domains: mobility, cognition, toileting independence, and medication usage (Amundsen et al., 2020). Each domain encompasses specific categories that enable healthcare professionals to accurately identify patients requiring targeted fall prevention strategies. Mobility assessments, for example, classify patients from fully independent to immobile. Cognitive evaluations categorize individuals from fully alert to unresponsive. Similarly, toileting ability ranges from completely independent to incontinent, and medication review includes drugs known to increase fall risk, such as psychotropics and hypnotics.

The detailed classification within the Schmid tool assists clinicians in creating individualized care plans, ensuring that high-risk patients receive appropriate supervision and interventions. By integrating this informatics-based assessment into routine clinical practice, healthcare providers can enhance patient safety and reduce the incidence of preventable falls.

Table 1

Schmid Tool Fall Risk Assessment Criteria

Category	Assessment Criteria	Description
Mobility	Mobile (0)	Fully independent without mobility assistance.
	Mobile with assistance (1)	Requires help from a caregiver or device to ambulate.
	Unstable (1b)	Exhibits balance instability, increasing fall risk.
	Immobile (0a)	Completely dependent on others for movement.
Cognition	Alert (0)	Fully oriented and responsive.
	Occasionally confused (1a)	Periodically disoriented or forgetful.
	Always confused (1b)	Constantly disoriented, requiring supervision.
	Unresponsive (0b)	Unable to respond or engage meaningfully.
Toileting Abilities	Completely independent (0a)	Manages toileting without assistance.
	Independent with frequency (1a)	Requires frequent restroom visits but remains independent.
	Requires assistance (1b)	Needs help from caregivers for toileting.
	Incontinent (1c)	Unable to control bladder or bowel functions.
Medication Use	Anticonvulsants (1a)	Seizure medications contributing to fall risk.
	Psychotropics (1b)	Drugs affecting cognition and mental state.
	Tranquilizers (1c)	Sedatives that may cause drowsiness and imbalance.
	Hypnotics (1d)	Sleep medications impairing balance and alertness.
	None (0)	No medications contributing to fall risk.

Literature Review

Although significant progress has been made in fall prevention within healthcare settings, falls continue to present a serious challenge to patient safety and operational costs. Falls remain a prominent cause of injury, disability, and mortality, particularly among the elderly. This not only impacts patient quality of life but also places financial strain on healthcare facilities. Since 2008, Medicare and Medicaid have stopped covering expenses related to hospital-acquired fall injuries, emphasizing the urgency of proactive fall management measures (LeLaurin & Shorr, 2019).

Studies have shown a notable association between falls and hospital readmissions among older adults, underscoring the importance of comprehensive prevention strategies and adequate social support systems (Galet et al., 2018). Falls have been identified as the leading cause of injury-related deaths in individuals aged 65 and older in the U.S., reinforcing the necessity for evidence-based interventions such as the Schmid tool (CDC, 2020). Implementing structured assessment instruments like this not only improves patient safety but also reduces readmission rates and optimizes healthcare resource utilization.

Conclusion

The findings highlighted through this assessment reinforce the value of integrating standardized fall prevention tools into clinical practice. Falls persist as a leading cause of injury and mortality, particularly among elderly populations. By incorporating informatics-driven solutions like the Schmid tool, healthcare facilities can effectively identify at-risk individuals, implement targeted preventive interventions, and ultimately reduce the incidence of falls. These strategies contribute to enhanced patient safety, improved clinical outcomes, and greater operational efficiency within hospital environments.

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. https://doi.org/10.xxxx/jhir.2020.75

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