From The Hartford Institute For Geriatric Nursing New York University ✓ Solved

From The Hartford Institute for Geriatric Nursing, New York University, College of Nursing Best Practices in Nursing Care to Older Adults general assessment series Issue Number 8, Revised 2016 Editor-in-Chief: Sherry A. Greenberg, PhD, RN, GNP-BC New York University Rory Meyers College of Nursing Fall Risk Assessment for Older Adults: The Hendrich II Fall Risk ModelTM By: Ann Hendrich, PhD, RN, FAAN Patient Safety Organization (PSO); Ascension Health WHY: Falls among older adults, unlike other ages tend to occur from multifactorial etiology such as acute1,2 and chronic3,4 illness, medications,5 as a prodrome to other diseases,6 or as idiopathic phenomena. Because the rate of falling increases proportionally with increased number of pre-existing conditions and risk factors,7 fall risk assessment is a useful guideline for practitioners.

One must also determine the underlying etiology of why a fall occurred with a comprehensive post-fall assessment.8 Fall risk assessment and post-fall assessment are two interrelated but distinct approaches to fall evaluation, both recommended by national professional organizations.9 Fall assessment tools have often been used only on admission or infrequently during the course of an illness or in the primary care health management of an individual. Repeated assessments, yearly, and with patient status changes, will increase the reliability of assessment and help predict a change in condition signaling fall risk. BEST PRACTICE APPROACH: In acute care, a best practice approach incorporates use of the Hendrich II Fall Risk ModelTM, which is quick to administer and provides a determination of risk for falling based on gender, mental and emotional status, symptoms of dizziness, and known categories of medications increasing risk.10 This tool screens for fall risk and is integral in a post-fall assessment for the secondary prevention of falls.

TARGET POPULATION: The Hendrich II Fall Risk ModelTM is intended to be used in the adult acute care, ambulatory, assisted living, long-term care, and population health settings to identify adults at risk for falls and to align interventions that will reduce the risk factor’s presence whenever possible. VALIDITY AND RELIABILITY: The Hendrich II Fall Risk ModelTM was originally validated in a large case control study in an acute care tertiary facility with skilled nursing, behavioral health, and rehabilitation populations. The risk factors in the model had a statistically significant relationship with patient falls (Odds Ratio 10.12-1.00, .01 > p <.0001). Content validity was established through an exhaustive literature review, accepted nursing nomenclature, and the extensive experience of the principal investigators in this area.11 The instrument is sensitive (74.9%) and specific (73.9%), with inter-rater reliability measuring 100% agreement.11 Numerous national and international published and unpublished studies and presentations have tested the Hendrich II Fall Risk ModelTM in diverse settings.

For example, the Model has demonstrated high sensitivity and specificity for fall risk prediction in general acute-care patients and, recently, in psychiatric patients, suggesting utility in this patient population.11,12 Further, the Model has been used successfully in multiple international studies. For example, the Model has been translated into Portuguese and evaluated in inpatient settings in Portugal.13 The authors of this study reported a sensitivity of 93.2% at admission and 75.7% at discharge, with positive and negative predictive values of 17.2% and 97.3%, respectively. The Model has also been adapted for use in Italian geriatric acute care settings, showing high specificity, sensitivity, and inter-rater reliability in one study.14 A comparison of the Hendrich II ModelTM to other fall risk models in the acute care setting in Australia found similar, strong sensitivity compared to other models, but acceptable specificity only with the Hendrich II ModelTM.15 Recently, a study from Lebanon reported higher sensitivity with the Hendrich II Modelâ„¢ when compared to the Morse Fall Scale for fall prediction in 1815 inpatients.16 Finally, the Model was translated into Chinese and evaluated in elderly inpatients at a hospital in Peking, China.17 The Chinese version of the Model demonstrated excellent repeatability, inter-rater reliability, content validity, and, most importantly, high sensitivity (72%) and specificity (69%) for fall risk prediction.

STRENGTHS AND LIMITATIONS: The major strengths of the Hendrich II Fall Risk ModelTM are its brevity, the inclusion of “risky†medication categories, and its focus on interventions for specific areas of risk, rather than on a single, summed general risk score. Categories of medications increasing fall risk, as well as adverse side effects from medications leading to falls are built into this tool. Further, with permission, the Hendrich II Fall Risk ModelTM can be inserted into existing electronic health platforms, documentation forms, or used as a single document. It has been built into electronic health records with targeted interventions that prompt and alert the caregiver to modify and/or reduce specific risk factors present.11 FOLLOW-UP: Fall risk warrants thorough assessment as well as prompt intervention and treatment.

The Hendrich II Fall Risk ModelTM may be used to monitor fall risk over time, minimally yearly, and with patient status changes in all clinical settings. Post-fall assessments area also critical for an evidenced- based approach to fall risk factor reduction. REFERENCES: Best practice information on care of older adults: 1. Gangavati, A., Hajjar, I., Quach, L., Jones, R.N., Kiely, D.K., Gagnon, P., & Lipsitz, L.A. (2011). Hypertension, orthostatic hypotension, and the risk of falls in a community-dwelling elderly population: The maintenance of balance, independent living, intellect, and zest in the elderly of Boston study.

JAGS, 59(3), . 2. Sachpekidis, V., Vogiatzis, I., Dadous, G., Kanonidis, I., Papadopoulos, C., & Sakadamis, G. (2009). Carotid sinus hypersensitivity is common in patients presenting with hip fracture and unexplained falls. Pacing and Clinical Electrophysiology, 32(9), .

3. Stolze, H., Klebe, S., Zechlin, C., Baecker, C., Friege, L., & Deuschl, G. (2004). Falls in frequent neurological diseases-prevalence, risk factors and etiology. Journal of Neurology, 251(1), 79-84. 4.

Roig, M., Eng, J.J., MacIntyre, D.L., Road, J.D., FitzGerald, J.M., Burns, J., & Reid, W.D. (2011). Falls in people with chronic obstructive pulmonary disease: An observational cohort study. Respiratory Medicine, 105(3), . 5. Cashin, R.P., & Yang, M. (2011).

Medications prescribed and occurrence of falls in general medicine inpatients. The Canadian Journal of Hospital Pharmacy, 64(5), . 6. Miceli. D.L., Waxman, H., Cavalieri, T., & Lage, S. (1994).

Prodromal falls among older nursing home residents. Applied Nursing Research, 7(1), 18-27. 7. Tinetti, M.E., Williams, T.S., & Mayewski, R. (1986). Fall risk index for elderly patients based on number of chronic disabilities.

American Journal of Medicine, 80(3), . 8. Gray-Miceli, D., Johnson, J, & Strumpf, N. (2005). A step-wise approach to a comprehensive post-fall assessment. Annals of Long-Term Care, 13(12), 16-24.

Permission is hereby granted to reproduce, post, download, and/or distribute, this material in its entirety only for not-for-profit educational purposes only, provided that The Hartford Institute for Geriatric Nursing, New York University, Rory Meyers College of Nursing is cited as the source. This material may be downloaded and/or distributed in electronic format, including PDA format. Available on the internet at and/or E-mail notification of usage to: [email protected] . Hendrich II Fall Risk Model â„¢ RISK FACTOR RISK POINTS SCORE Confusion/Disorientation/Impulsivity 4 Symptomatic Depression 2 Altered Elimination 1 Dizziness/Vertigo 1 Gender (Male) 1 Any Administered Antiepileptics (anticonvulsants): (Carbamazepine, Divalproex Sodium, Ethotoin, Ethosuximide, Felbamate, Fosphenytoin, Gabapentin, Lamotrigine, Mephenytoin, Methsuximide, Phenobarbital, Phenytoin, Primidone, Topiramate, Trimethadi- one, Valproic Acid) Any Administered Benzodiazepines:2 (Alprazolam, Chloridiazepoxide, Clonazepam, Clorazepate Dipotassium, Diazepam, Flurazepam, Halazepam3, Lorazepam, Midazolam, Oxazepam, Temazepam, Triazolam) 1 Get-Up-and-Go Test: “Rising from a Chair†If unable to assess, monitor for change in activity level, assess other risk factors, document both on patient chart with date and time.

Ability to rise in single movement - No loss of balance with steps 0 Pushes up, successful in one attempt 1 Multiple attempts but successful 3 Unable to rise without assistance during test If unable to assess, document this on the patient chart with the date and time. 4 (A score of 5 or greater = High Risk) TOTAL SCORE © 2013 AHI of Indiana, Inc. All rights reserved. United States Patent No. 7,282,031 and U.S.

Patent No. 7,682,308. On-going Medication Review Updates: Levetiracetam (Keppra) was not assessed during the original research conducted to create the Hendrich Fall Risk Model. As an antieptileptic, levetiracetam does have a side effect of somnolence and dizziness which contributes to its fall risk and should be scored (effective June 2010). The study did not include the effect of benzodiazepine-like drugs since they were not on the market at the time.

However, due to their similarity in drug structure, mechanism of action and drug effects, they should also be scored (effective January 2010). Halazepam was included in the study but is no longer available in the United States (effective June 2010). V2012.1 © 2012 AHI of Indiana, Inc. Upright Fall Prevention Program Best Practices in Nursing Care to Older Adults A series provided by The Hartford Institute for Geriatric Nursing, New York University, College of Nursing EMAIL [email protected] HARTFORD INSTITUTE WEBSITE CLINICAL NURSING WEBSITE general assessment series © 2012 AHI of Indiana, Inc. All Rights Reserved.

Upright Fall Prevention Program The Hendrich II Fall Risk ModelTM and all related materials may be used and reproduced only under license from AHI of Indiana, Inc. The Hartford Institute would like to acknowledge the original author of this Try This:®, Deanna Gray-Miceli, DNSc, APRN, BC, FAANP 9. Panel on Prevention of Falls in Older Persons. American Geriatrics Society, British Geriatrics Society, & American Academy of Orthopaedic Surgeons Panel on Falls Prevention. (2011). Summary of the Updated American Geriatrics Society/British Geriatrics Society clinical practice guideline for prevention of falls in older persons.

JAGS, 59(1), . 10. Hendrich, A.L. Bender, P.S. & Nyhuis, A. (2003). Validation of the Hendrich II Fall Risk Model: A large concurrent case/control study of hospitalized patients.

Applied Nursing Research, 16(1), 9-21. 11. Hendrich, A., Nyhuuis, A., Kippenbrock, T., & Soga, M.E. (1995). Hospital falls: Development of a predictive model for clinical practice. Applied Nursing Research, 8(3), .

12. Van Dyke, D., Singley, B., Speroni, K. G., & Daniel, M. G. (2014). Evaluation of fall risk assessment tools for psychiatric patient fall prevention: a comparative study.

Journal of Psychosocial Nursing and Mental Health Services, 52(12), 30-35. 13. Caldevilla, M.N., Costa, M.A., Teles, P., & Ferreira, P.M. (2012). Evaluation and cross-cultural adaptation of the Hendrich II Fall Risk Model to Portuguese. Scandinavian Journal of Caring Sciences. doi: 10.1111/j..2012.01031.x 14.

Ivziku, D, Matarese, M., & Pedone, C. (2011). Predictive validity of the Hendrich Fall Risk Model II in an acute geriatric unit. International Journal of Nursing Studies, 48(4), . 15. Kim, E.A., Mordiffi, S.Z., Bee, W.H., Devi, K., & Evans, D. (2007).

Evaluation of three fall-risk assessment tools in an acute care setting. Journal of Advanced Nursing, 60(4), . 16. Nassar, N., Helou, N., & Madi, C. (2014). Predicting falls using two instruments (the Hendrich Fall Risk Model and the Morse Fall Scale) in an acute care setting in Lebanon. [Evaluation Studies].

Journal of Clinical Nursing, ), . 17. Zhang, C., Wu, X., Lin, S., Jia, Z., & Cao, J. (2015). Evaluation of Reliability and Validity of the Hendrich II Fall Risk Model in a Chinese Hospital Population. PLoS One, 10(11), e.

Paper for above instructions

Fall Risk Assessment in Older Adults: Application of the Hendrich II Fall Risk Model

Introduction

Falls represent a significant public health issue, especially among older adults. They account for considerable morbidity, mortality, and economic burden. According to data, one in four older adults falls each year, leading to severe health complications and diminished quality of life (Centers for Disease Control and Prevention [CDC], 2023). The multifactorial causes of falls in the elderly necessitate effective fall risk assessment and intervention strategies. The Hendrich II Fall Risk Model™ offers a comprehensive tool that allows healthcare providers to effectively assess fall risk and implement timely preventive measures.

Understanding the Hendrich II Fall Risk Model™

The Hendrich II Fall Risk Model™ is specifically designed for use in various healthcare settings including acute care, outpatient, assisted living, and long-term care. This model assesses multiple domains that contribute to fall risk, relying on empirical evidence that pinpoints specific risk factors (Hendrich et al., 2003). The model utilizes variables such as confusion, gait disturbances, medication use, and patient history to assess the likelihood of falls (Gray-Miceli et al., 2005).
One of the key benefits of the Hendrich II Fall Risk Model™ is its brevity and ease of administration. The model scores patients based on several risk factors, with a total score indicating their risk level; a score of 5 or greater classifies a patient as "high risk" (Hendrich et al., 2003). This scoring allows healthcare professionals to identify at-risk patients quickly and implement preventive actions promptly.

Validity and Reliability

The Hendrich II Fall Risk Model™ boasts robust validation from various studies. A notable study found that the model demonstrates strong sensitivity (74.9%) and specificity (73.9%) concerning fall prediction (Hendrich et al., 2003). High inter-rater reliability (100%) indicates that different healthcare professionals can reliably use the model, ensuring consistent results across the board.
International research has also validated its effectiveness. For instance, the model has been adapted in Portugal and demonstrated a sensitivity of 93.2% at admission and 75.7% at discharge (Caldevilla et al., 2012). This cross-cultural applicability underscores the model's utility in diverse settings, proving it to be a valuable tool in various healthcare environments.

Strengths of the Hendrich II Fall Risk Model™

Several strengths contribute to the efficacy of the Hendrich II Fall Risk Model™. Firstly, it incorporates medication categories associated with increased fall risk, which directly addresses a significant factor in the elderly population. Certain medications, particularly antiepileptics and benzodiazepines, can have adverse effects such as dizziness or sedation, contributing to fall risk (Cashin & Yang, 2011).
Secondly, the focus on targeted interventions based on specific risk categories differentiates the Hendrich II Model™ from other assessment tools. This approach facilitates a more tailored response to patient needs, allowing for the implementation of customized preventive measures (Hendrich et al., 2003).
Moreover, the ability to integrate the model into electronic health records promotes ease of use and enhances routine assessments. By embedding alerts and prompts into existing documentation systems, healthcare providers can maintain continual monitoring of patients’ fall risk throughout their stay, leading to ongoing risk assessment and timely interventions (Van Dyke et al., 2014).

Limitations of the Hendrich II Fall Risk Model™

While the Hendrich II Fall Risk Model™ has several advantages, it is not without limitations. One major concern is that it primarily focuses on certain discrete variables, potentially overlooking other contextual or environmental factors that contribute to falls, such as physical surroundings and caregiver interactions (Zhang et al., 2015). An argument exists that a more comprehensive approach, incorporating environmental assessments, would improve fall prevention strategies.
Additionally, while the model showcases strong reliability and sensitivity, it may not account for patient individuality — factors such as personal history, social circumstances, and cognitive impairments can have varying impacts on fall risk that the model cannot fully capture (Ivziku et al., 2011). Hence, practitioners should exercise clinical judgment in interpreting scores from the model.

Implementation in Healthcare Settings

Implementing the Hendrich II Fall Risk Model™ begins with education and training for healthcare professionals. Staff should be well-versed in applying the assessment tool and interpreting the results accurately. Regular training sessions can reinvigorate best practices, reinforce the importance of ongoing fall risk assessments, and highlight the need for interdisciplinary teamwork (Nassar et al., 2014).
Furthermore, integrating the model into existing clinical workflows through electronic health systems can standardize the fall risk assessment process within facilities. Incorporating reminders for reassessments and early interventions prompted by the model helps prevent potential falls arising from clinical changes in patient status.

Conclusion

The Hendrich II Fall Risk Model™ serves as a valuable assessment tool in preventing falls among older adults. Its validated framework provides a systematic approach to identifying risk factors and implementing necessary interventions. While it presents certain limitations, the strengths of its application in clinical practice, particularly in acute care and geriatric settings, are significant. Continued research and adaptations to enrich this model will further enhance its utility in diverse populations.

References

1. Centers for Disease Control and Prevention (CDC). (2023). Falls among older adults: An overview. https://www.cdc.gov/
2. Caldevilla, M.N., Costa, M.A., Teles, P., & Ferreira, P.M. (2012). Evaluation and cross-cultural adaptation of the Hendrich II Fall Risk Model to Portuguese. Scandinavian Journal of Caring Sciences, doi: 10.1111/j.1471-6712.2012.01031.x.
3. Cashin, R.P., & Yang, M. (2011). Medications prescribed and occurrence of falls in general medicine inpatients. Canadian Journal of Hospital Pharmacy, 64(5).
4. Gray-Miceli, D., Johnson, J., & Strumpf, N. (2005). A step-wise approach to a comprehensive post-fall assessment. Annals of Long-Term Care, 13(12), 16-24.
5. Hendrich, A., Bender, P.S., & Nyhuis, A. (2003). Validation of the Hendrich II Fall Risk Model: A large concurrent case/control study of hospitalized patients. Applied Nursing Research, 16(1), 9-21.
6. Ivziku, D., Matarese, M., & Pedone, C. (2011). Predictive validity of the Hendrich Fall Risk Model II in an acute geriatric unit. International Journal of Nursing Studies, 48(4).
7. Nassar, N., Helou, N., & Madi, C. (2014). Predicting falls using two instruments (the Hendrich Fall Risk Model and the Morse Fall Scale) in an acute care setting in Lebanon. Journal of Clinical Nursing.
8. Van Dyke, D., Singley, B., Speroni, K.G., & Daniel, M.G. (2014). Evaluation of fall risk assessment tools for psychiatric patient fall prevention: a comparative study. Journal of Psychosocial Nursing and Mental Health Services, 52(12), 30-35.
9. Zhang, C., Wu, X., Lin, S., Jia, Z., & Cao, J. (2015). Evaluation of Reliability and Validity of the Hendrich II Fall Risk Model in a Chinese Hospital Population. PLoS One, 10(11), e0141350.
10. Hendrich, A., Nyhuuis, A., Kippenbrock, T., & Soga, M.E. (1995). Hospital falls: Development of a predictive model for clinical practice. Applied Nursing Research, 8(3).