NURS FPX 6414 Assessment 1 Conference Poster Presentation
Student Name
Capella University
NURS-FPX 6414 Advancing Health Care Through Data Mining
Prof. Name
Date
Abstract
Healthcare professionals continually strive to enhance patient safety, with fall prevention being a critical focus area. Falls are a leading cause of unintentional injuries and fatalities among adults aged 65 and older in the United States, resulting in approximately 2.8 million emergency room visits annually (CDC, 2020). Multiple risk factors contribute to falls, including cognitive impairment, reduced mobility, and urgent toileting needs, affecting individuals in both hospital and community settings (LeLaurin & Shorr, 2019).
In hospital environments, annual fall rates range from 700,000 to 1 million, corresponding to 3.5–9.5 falls per 1,000 bed days (LeLaurin & Shorr, 2019). Research by Galet et al. (2018) with 931 patients demonstrated that 633 were at high risk for falls due to factors such as cognitive dysfunction, mobility limitations, and incontinence. Single fall incidents can lead to extended hospital stays, higher healthcare costs, and diminished patient outcomes.
To address these challenges, OhioHealth’s informatics team developed the Schmid tool, a structured fall risk assessment designed to identify high-risk patients and guide targeted interventions (Lee et al., 2019). This tool evaluates critical domains such as mobility, cognition, toileting needs, fall history, and medication use. This study examines the Schmid tool’s effectiveness in improving patient safety and overall healthcare outcomes through informatics-driven interventions.
Introduction
Falls are a substantial public health concern, particularly for hospitalized patients. Approximately 2.8 million adults annually require emergency care due to fall-related injuries (LeLaurin & Shorr, 2019). Within hospitals, falls lead to prolonged stays and increased healthcare costs, with 700,000 to 1 million incidents occurring each year (LeLaurin & Shorr, 2019). Given the clinical and financial implications, implementing effective fall prevention strategies is critical.
The Schmid tool is widely recognized for its ability to identify patients at elevated risk for falls. It assesses mobility, cognitive function, toileting abilities, medication use, and fall history. Evaluating the tool’s effectiveness is essential for refining fall prevention strategies and enhancing patient outcomes.
Analyzing the Use of the Informatics Model
The Schmid fall risk assessment organizes patients into four primary domains: mobility, cognitive function, toileting ability, and medication use (Amundsen et al., 2020). Each domain includes subcategories that help healthcare professionals determine the appropriate interventions for patients at risk of falls.
- Mobility: Evaluates the patient’s ability to move independently, ranging from fully mobile to immobile.
- Cognitive Function: Assesses awareness, orientation, and potential confusion, from alert to unresponsive states.
- Toileting Ability: Classifies patients from fully independent to incontinent.
- Medication Use: Reviews drugs that may elevate fall risk, including anticonvulsants, psychotropics, tranquilizers, and hypnotics (Amundsen et al., 2020).
The Schmid tool enables clinicians to implement personalized fall prevention measures and monitor outcomes, ensuring targeted and evidence-based interventions.
Literature Review
Despite technological and procedural advancements, falls remain a critical challenge for healthcare organizations. They are a leading cause of injury, disability, and mortality among older adults, profoundly affecting quality of life. Hospitals face financial pressures due to prolonged admissions and treatment costs associated with fall injuries. Since 2008, Medicare and Medicaid no longer reimburse hospitals for fall-related injuries, underscoring the necessity for effective prevention strategies (LeLaurin & Shorr, 2019).
Research indicates that fall-related hospital readmissions among elderly patients are rising, highlighting the importance of comprehensive prevention strategies and supportive care networks (Galet et al., 2018). Falls continue to be the leading cause of injury-related deaths for adults aged 65 and older in the United States, reinforcing the need for structured, evidence-based interventions such as the Schmid tool (CDC, 2020).
Conclusion
Integrating structured fall prevention tools, such as the Schmid assessment, is essential in hospital settings to safeguard patients. Falls remain a significant cause of injury and mortality among older adults. Utilizing informatics-driven strategies like the Schmid tool allows healthcare institutions to identify high-risk patients, implement targeted interventions, reduce fall incidents, and enhance overall patient safety and healthcare outcomes.
Schmid Fall Risk Assessment Criteria
| Category | Assessment Criteria | Description |
|---|---|---|
| Mobility | Mobile (0) | Fully independent, requires no assistance. |
| Mobile with assistance (1) | Needs caregiver or assistive device. | |
| Unstable (1b) | Experiences balance issues, at risk for falling. | |
| Immobile (0a) | Cannot move independently, requires full assistance. | |
| Cognition | Alert (0) | Fully aware, oriented, and responsive. |
| Occasionally confused (1a) | Intermittent disorientation or forgetfulness. | |
| Always confused (1b) | Consistently disoriented, needs supervision. | |
| Unresponsive (0b) | Cannot respond to stimuli or interact meaningfully. | |
| Toileting Abilities | Completely independent (0a) | Manages toileting without assistance. |
| Independent with frequency (1a) | Needs frequent restroom visits but manages independently. | |
| Requires assistance (1b) | Needs caregiver support for toileting. | |
| Incontinent (1c) | Cannot control bladder or bowel function. | |
| Medication Use | Anticonvulsants (1a) | Seizure medications that may increase fall risk. |
| Psychotropics (1b) | Drugs affecting mental state or cognition. | |
| Tranquilizers (1c) | Sedative medications causing dizziness. | |
| Hypnotics (1d) | Sleep-inducing drugs impairing 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.
NURS FPX 6414 Assessment 1 Conference Poster Presentation
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.
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.