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 adults of 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, and both are 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 that increase 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 Model™ when compared to the Morse Fall Scale for fall prediction in 18,15 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 that increase fall risk, as well as adverse 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: www.ConsultGeri.org.


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), 383-389.

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), 1184-1190.

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), 461-469.

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), 321-326.

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), 429-434.

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.

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), 148-157.

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), 129-139.

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.1471-6712.2012.01031.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), 468-474.

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), 427-435.

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, 23(11-12), 1620-1629.

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), e0142395.