HENDRICH II FALL RISK MODEL PDF

Sebastiano Hospital, Correggio, Italy. The data supporting the findings of this manuscript can be obtained from the corresponding author on reasonable request. Falls are a common adverse event in both elderly inpatients and patients admitted to rehabilitation units. The occurrence of falls was checked and recorded daily. One hundred ninety-one patents were admitted.

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Sebastiano Hospital, Correggio, Italy. The data supporting the findings of this manuscript can be obtained from the corresponding author on reasonable request. Falls are a common adverse event in both elderly inpatients and patients admitted to rehabilitation units. The occurrence of falls was checked and recorded daily. One hundred ninety-one patents were admitted. Failures in administration were mainly due to bedridden patients e. AUC was 0. Moreover, the median score for non-fallers at rehabilitation units was higher than that reported in literature for geriatric non fallers.

The best trade-off between sensitivity and specificity was obtained by using a cutoff of 8. Based on both available literature and these results, the prediction of falls among all hospital wards, with high risk of falling, could be achieved by means of a unique tool and two different cutoffs: a standard cutoff of 5 in geriatric wards and an adjusted higher cutoff in rehabilitation units, with predictive performances similar to those of the best-preforming pathology specific tools for fall-risk assessment.

Accidental falls are the major cause of hospital injuries, resulting in extended length of stay and a decline in quality of life [ 1 ].

Higher rates are reported in neurological, geriatric and rehabilitative wards. Patients participating in rehabilitation may experience falls, as they are being encouraged to be more independent and mobile and may over-stimulate their balance systems [ 4 ].

The topic of fall prevention has been emerging in recent literature on neurological patients [ 5 , 6 ]. Fall prevention strategies, which rely on tailored multifactorial intervention programs, need to be based on the prior identification of patients at risk of falling, as reported in the systematic review from Cameron and colleagues [ 7 ].

Reliable tools for fall risk assessment would allow for actions on selected patients only, thus ensuring interventions to be both appropriate and cost effective. Recently, there has been a spate of interest in falls risk assessment tools specific for stroke patients, such as the Stroke Assessment Fall Risk [ 5 ] and the 4-Item Falls Assessment Tool [ 6 ].

Nonetheless, no specific tools for a whole rehabilitation department have been provided. Among the above-mentioned tools, the HIIFRM is a multifactorial, eight-item tool that showed the best performance in terms of sensitivity and specificity.

It has been validated by three independent studies on very large series in geriatric and acute care wards [ 14 , 16 , 17 ]. In addition, it can be carried out in just a few minutes [ 14 , 18 ].

However, a description of its feasibility and predictive performance in rehabilitative patients is still missing in the literature. The aim of the present paper is to address both the feasibility, i. This prospective observational study was conducted during 6 consecutive months at the St. All patients or relatives gave informed consent to data treatment in this research study and permission to publish anonymous data and results. In this scale, the term altered elimination is qualified by the presence of any of the following symptoms: urinary or fecal incontinence, urgency or stress incontinence, diarrhea, frequent urination, and nocturia.

The specific scores are based on their likelihood to cause a fall [ 14 , 19 ]. These are summed up to a total score that can range between 0 lowest risk and 16 highest risk. Patients who cannot attempt the rising-from-chair test are classified as at-risk in the case of a total score from the remaining items equal to, or greater than the cutoff score.

The occurrence of falls was checked and recorded on a daily basis by professionals nurses, physiotherapists, physicians , from their admission until discharge, death or transfer to another unit.

Descriptive statistics were used to assess the risk fall assessment feasibility in the sample as a whole and split by wards.

This procedure allowed considering the whole sample, including those patients unable to perform the rise-from-chair test. As expected, the duration of the observation period was greater in NR, where more compromised patients were admitted.

The t -test was used for statistical comparisons. No adverse event took place during the administration of the scale. Lastly, 1 patient refused participating in the study. The most time-consuming items were, as expected, the rise-from-chair test and the analysis of pharmacologic treatments.

Out of the screened patients, 11 fell during hospitalizion 7. Mean age SD was 63 22 years range 20—87 and mean observation time was 52 23 days. The fall rate was 3. It appears from our data that falls in a rehabilitative hospital mainly take place among neurological patients and may involve young subjects, too. The large majority of neurological patients needed for assistance to stand up from a chair score 4 , and suffered from dizziness or vertigo, which scores 1.

As a consequence, a very large number of NR subjects exceeded the threshold level of 5 and was classified as at risk of falling. Conversely, high score items were not frequent in patients at OR and PR wards. Hence, the contemporary presence of many low-score risk factors was required to reach the threshold score. The chair test was not feasible in most of the orthopaedic patients, whose most frequent risk factors were altered elimination and dizziness or vertigo. The rise-from-chair test was relatively easy for patients at PR, while it was frequently impossible to be administered at the OR ward, mainly due to recent surgery, such as total hip or knee replacements.

The presence of depression and the use of antiepileptic drugs were similar among wards, altered elimination at OR and PR was about twice frequent than at NR and the use of benzodiazepines was lower at OR compared to the other two wards. It is evident in Fig. Predictive performance was computed based on 11 falls from subjects. The ROC curve is reported in Fig. As expected, sensitivity progressively decreased and specificity progressively increased when the cutoff score increased.

Confidence Interval. Conversely, a cutoff equal to 9 would dramatically reduce sensitivity, thus being not adequate. The two subject who fell at the OR ward had a total score of 7 and 11, respectively.

Therefore, they would be properly classified by using the cutoff score of 7. This study aimed at addressing feasibility and predictive performance of the HIIFRM, when used in a rehabilitative department including units of different specialization. In our sample the 7. This value is similar to that reported for high-risk non-geriatric medical wards [ 21 ]. This confirms the need for screening procedures and prevention strategies at rehabilitative wards.

The HIIFRM was selected in this study because of both its multifactorial structure and the satisfactory predictive performance in the assessment of inpatients in medical, surgical and geriatric wards, which has been outlined by several independent studies on wide samples and by recent systematic revisions [ 14 , 16 , 18 , 22 — 24 ]. Along with the inpatient rehabilitative wards, these are all the hospital wards where it is reasonable to seek to identify patients at risk of falling by a tool, as this event is not rare.

The possibility of extending the use of HIIFRM to the rehabilitative settings too, would allow utilizing a unique fall risk assessment tool across all wards with high fall occurrence. This would be easy to implement in hospitals and should enhance compliance of nurses and other professionals [ 6 ]. We consider this result satisfactory. The majority of failures in tool administration took place in the NR unit and was related to minimally conscious patients and vegetative states at admission.

These patients are not at risk of falling as they cannot leave the bed and would not be included in a screening procedure at least until volitional movements reappear. The presence of highly compromised patients e. Thanks to the HIIFRM classifying procedure, the fall risk status can be assessed also for patients who underwent orthopaedic surgery before admission, such as a total hip arthroplasty, despite of their inability in performing the functional task.

As recommended, all unavailable patients of NR and OR wards have to be reassessed as soon as safely permitted by their clinical condition [ 14 ]. Feasibility was not investigated by previous studies on fall risk assessment tools, hence a comparison with literature cannot be carried out. It indirectly measures the residual ability of generating force in the lower limbs. This ability has been progressively recognized as a requisite for counteracting the unexpected imbalance that may lead to falls [ 26 ] and its evaluation boosts the predictive performance of clinical tools for fall-risk assessments [ 27 — 29 ].

Interestingly, the performance of the HIIFRM resulted similar to that obtained by patient-specific tools assessed by the recent literature [ 5 , 6 , 30 , 31 ]. Along with predictive power, the identification of a tool with good specificity is of major importance to plan both screening procedures and sustainable prevention pathways. By using the cutoff of 7 i. The selection for a cutoff value between 7 and 8 should be made according to the available hospital resources.

An increase in threshold reduces false positives and therefore makes it less burdensome and more feasible the implementation in prevention protocols for those identified at risk. In this ward, the two items that score 4, that is confusion and the inability to rise from chair without assistance, were found in many patients.

As a consequence, the average score at NR was particularly high and the majority of NR patients presented a total score greater than 5, thus resulting at high risk of falling according to the HIIFRM classification rule. The well-known relationship between older age and fall-risk may not extend to the whole inpatient rehabilitation population.

No falls occurred at the PR ward, in our study. This result could be explained by the case-mix, where patients were either highly compromised and bedridden or with good functional ability. The occurrence of risk factors at OR was similar to that reported by Ivziku for a sample of geriatric patients [ 18 ].

Thus, the HIIFRM risk factors with the greatest score were rare and the total score for these patients was in general low. Finally, whilst a pathology-specific tool could be appropriate where a very narrow case-mix of patients is admitted, such as in a stroke unit, a multifactorial tool is to be preferred where a wide case-mix of patients is treated, as in the case of a rehabilitation department. The main limitation of this study is the low number of subjects included and of falls recorded.

This would suggest caution in generalizing our results, even if the fall rate was congruent to those in the literature. A further weakness is that patients were assessed at admission only, according to the aim of the study. Hence, eventual changes in the clinical conditions and in the consequent fall risk status have not been considered. In conclusion, the HIIFRM showed satisfactory feasibility and predictive performances in the assessment of fall-risk in rehabilitative settings.

Hence, apart from being used in geriatric, in the long-term care, medicine, and surgery departments with a cutoff of 5, the HIIFRM could also be used to determine the risk of falling of hospitalized patients in rehabilitation departments i. Based on both available literature on geriatric patients and our findings in the rehabilitative wards, we propose the assessment of fall risk amongst all hospital units with high fall occurrence by means of a unique tool, the HIIFRM, with two different cutoff values.

Authors would like to acknowledge dr. IC: Concept and design, study coordination, interpretation of data, preparation and review of manuscript. FL, ST, ML: management of data acquisition at wards, AM: study design, analysis and interpretation of data, preparation and review of manuscript. All authors contributed in critically revising the manuscript and have given final approval of the version to be published.

Written consent was obtained from all individuals from whom data was collected. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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How to Try This: Predicting Patient Falls

Already a member? Sign in. November , Volume Number 11 , p 50 - Designed to be administered quickly, it focuses on eight independent risk factors: confusion, disorientation, and impulsivity; symptomatic depression; altered elimination; dizziness or vertigo; male sex; administration of antiepileptics or changes in dosage or cessation ; administration of benzodiazepines; and poor performance in rising from a seated position in the Get-Up-and-Go test. Alvin Stewart was a healthy, independent year-old when he was hospitalized for partial lung resection for a nonmalignant tumor.

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The reliability of the Chinese version of the HFRM was determined using the internal consistency and test-rested methods. Validity was determined using construct validity and convergent validity. Receiver operating characteristic ROC curves were created to determine the sensitivity and specificity. The inter-rater reliability was high with an ICC of 0. Content validity was excellent, with a content validity ratio of 0.

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