Predictive validity of the Hendrich fall risk model II in an acute ...

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Table 4 Psychometric values of Hendrich II Model in different studies. Authors Hendrich et al. (2003) Kim et al. (2007) Sensitivity 0.75 0.70 0.86 Specificity 0.74 0.61 0.43 PPV ne 0.02 0.11 NPV ne, not evaluated. ne 0.95 0.97 Our higher sensitivity could be related to the fact that the risk factors included in the Hendrich fall risk model are highly relevant for the elderly comparing to a general hospitalized population admitted to medical–surgical units or persons younger than 65 years old. In fact giving higher scores to confusion and depression (4 and 2 respectively), can help to predict falls in geriatric patients as these conditions are more frequent in elderly admitted to hospital and are recognized as important risk factors for hospitalized elderly patients (Rubenstein, 2006; Scott et al., 2007). This study was the first one to test this assessment tool specifically on geriatric patients so far and we could not know if this discriminative value depends on characteristics of population admitted to our unit. Compared to a relatively high specificity of the Hendrich study, in our study the specificity was quite low, with proportion of false-positive fallers (risk-score patients who did not fall) of 57%. This was not completely unexpected since lower specificity values have been found frequently by researchers other than those who developed the risk assessment tools because of settings and population changes (Oliver et al., 2004). According to Myers, on the accuracy calculations two confounders can have impact: treatment paradox and ward prevention measures. Treatment paradox occurs when nurses are aware of the risk scores and implement fall prevention measures for high risk patients and not for low risk patients. For this reason it is important that nurses remain blind to the results of the assessment when testing the accuracy of a tool. Even if nurses are blind to the risk assessment it is likely that some type of fall prevention protocol is in place in the hospital setting. Fall might therefore be prevented by normal ward practices. This issue is difficult to counter as it would be unethical to ask nursing staff not to implement fall prevention measures (Myers, 2003). This could be occurred also in our study as, even if in the geriatric unit do not exist a formal protocol for preventing falls, the nurses plan and implement fall preventive interventions when they judge that a patient is at high risk on the basis of their clinical nursing assessment at the patient admission. For example, if the older patient is confused or agitated they usually ask one of the relatives to stay by the older patients during the day and/or the night; the nurses check more and more times patients considered at risk of falling during their shifts; moreover the relatives employ family assistants to help their elderly during the hospital stay whether they have some physical limitations. These interventions can be effective and reduce the risk of falling in some patients at risk. D. Ivziku et al. / International Journal of Nursing Studies 48 (2011) 468–474 473 Ivziku et al. (current study) One more explanation could be that severely impaired patient and patient’s family may become more aware of the risk of falling in hospital settings and consequently better protected those at risk applying some precautions. In addition, the patient health conditions can improve during the hospital stay and consequently the risk scores can change, so the admission score, that we used in our research to assess the risk, might not represent the risk of the patients during his/her hospital stay. The weak specificity of a fall risk assessment tool is of some relevant concern when evaluating its clinical utility, because many patients who do not fall are identified at high risk. This has implications for the implementation of fall prevention interventions that should be mainly targeted at those at high risk. Fall prevention programs may lose some of their significance if staff perceives that too many patients are identified at high risk for falls. We found an inter-rater reliability very similar to that calculated in the Kim et al.‘s study (k = 0.81 vs 0.87). The analysis of the reasons of rater disagreement indicated the need to include in the training program more examples and explanations about particular clinical situations (for example how to score the patient with prescription of benzodiazepine at occurrence, patients with cognitive impairment, temporary or permanent vertigo at admission). 5. Study limitations Even though the inter-rater reliability in our study was quite high, the range of CI at 95% of 0.71–1.00 indicated that it should have been necessary to test a higher sample size in order to have a power at least of 0.80 with an alpha of 0.05 as the literature suggests (Papaioannou et al., 2004). Moreover this study presents a low number of patients studied due to the small number of beds in our geriatric unit and to the short period of study. Even if the total fall rate of 7.5 per 1000 patient days is consistent with the range of the rates reported in the literature, the number of falls recorded (n = 14) is very limited and do not permit to generalize our results. In addition, as the research was carried out in one single geriatric unit, further validation studies will be necessary to extend the use in other geriatric units or on the general elderly population admitted to hospital. We did not reassess the patients when the clinical conditions changed to not burden the nurses working in the unit. We do not know if the fall risk score remained the same or changed just prior to the fall. Elderly patients should be reassessed during their hospital stay as their health conditions can change rapidly, and new medications can be prescribed (Hendrich et al., 2003). We did not compare the HFRM with other fall risk assessment tools to evaluate the different discriminative power and the effectiveness of different tools. A comparison with other tools could be useful to verify the power of other risk factors and tools in our population. 6. Conclusions The use of quick, reliable and valid fall risk tools to identify high risk patients and to elicit further fall related
474 assessments and interventions is recognized important in all clinical practice settings. The international research has not identified one optimal fall risk assessment tool for the acute care settings, and in particular for elderly inpatients. We aimed with our research to contribute to the search of a valid and reliable risk assessment tool by evaluating the predictive validity of the HFRM II in a geriatric unit. We found that this tool is easy to apply, the data can be collected simply, the score is quick to calculate, and has good sensitivity but low specificity. Hence we can moderately recommend the routine use of HFRM II to assess the fall risk in the geriatric unit of our Teaching Hospital. Acknowledgements The authors wish to acknowledge the nursing staff of the Geriatric Unit of the Campus Bio-Medico University Hospital for the collaboration. The authors also extend their acknowledgements to Ann Hendrich, PhD, author of the Hendrich II Fall Risk Model ß , for her invaluable advice and support. Conflict of interest: None declared. Funding: We do not have any sources of funding for our research. Ethical approval: This study was approved by the ethical Committee of the Campus Bio-Medico University Hospital. References Barros, C., De Marinis, M.G., Matarese, M., Murgese, S., Tartaglini, D., 2007. Un modello di organizzazione dell’attività assistenziale infermieristica che metta al centro il paziente ricoverato: l’esperienza del policlinico Campus Bio-medico di Roma. Medic 15 (2), 92–97. Coussement, J., De Paepe, L., Schwendimann, R., Denhaerynck, K., Dejaeger, E., Milisen, K., 2008. Interventions for preventing falls in acute- D. Ivziku et al. / International Journal of Nursing Studies 48 (2011) 468–474 and chronic-care hospitals: a systematic review and meta-analysis. Journal of American Geriatric Society 56 (1), 29–36. Dempsey, J., 2004. Falls prevention revisited: a call for a new approach. Journal of Clinical Nursing 13 (4), 479–485. Gillespie, L.D., Gillespie, W.J., Robertson, M.C., Lamb, S.E., Cumming, R., Rowe, B.H., 2003. Interventions for preventing falls in elderly people (Cochrane Review). The Cochrane Library 4, 3. 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. Hendrich, A., 2007. How to try this: predicting patient falls. Using the Hendrich II Fall Risk Model in clinical practice. American Journal of Nursing 107 (11), 50–58. Hauer, K., Lamb, S., Jorstad, E.C., Todd, C., Becker, C., 2003. Systematic review of definitions and methods of measuring falls in randomised controlled fall prevention trials. Age and Ageing 35, 5–10. Kannus, P., Sievanen, H., Palvanen, M., Järvinen, T., Parkkari, J., 2005. Prevention of falls and consequent injuries in elderly people. Lancet 366 (9500), 1885–1893. Kim, E.A., Mordiff, 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. Myers, H., 2003. Hospital fall risk assessment tools: a critique of the literature. International Journal of Nursing Practice 9 (4), 223– 225. Oliver, D., Daly, F., Martin, F.C., McMurdo, M.E., 2004. Risk factors and risk assessment tools for falls in hospital in-patients: a systematic review. Age and Ageing 33 (2), 122–130. Oliver, D., 2007. Older people who fall: why they matter and what you can do. British Journal of Community Nursing 12 (11), 500–507. Papaioannou, A., Parkinson, W., Cook, R., Ferko, N., Coker, E., D’Adachi, J., 2004. Prediction of falls using a risk assessment tool in the acute care setting. Biomed Central Medicine 2, 1–7. Perrell, K.L., Nelson, A., Goldman, R.L., Luther, S.L., Prieto-Lewis, N., Rubenstein, L.Z., 2001. Fall risk assessment measures: an analytic review. Journal of Gerontology 50 (12), M761–M766. Rubenstein, L.Z., Josephson, K.R., 2001. Guidelines for prevention of falls in older persons. Journal of American Geriatric Society 49, 664–672. Rubenstein, L.Z., 2006. Falls in older people: epidemiology, risk factors and strategies for prevention. Age and Ageing 35 S2, ii34–ii41. Scott, V., Votova, K., Scanlan, A., Close, J., 2007. Multifactorial and functional mobility assessment tools for falls risk among older adults in the community, home-support, long-term care and acute settings. Age and Ageing 36 (2), 130–140.
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