This meta-analysis failed to reveal a significant effect of fall prevention interventions on falls or fallers but, for the first time, showed that fall prevention interventions significantly reduced the number of recurrent fallers by 21%.

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Objectives: To identify the barriers and facilitators for fall prevention implementation in residential care facilities. Design: Systematic review. Review registration number on PROSPERO: CRD42013004655. Data sources: Two independent reviewers systematically searched five databases (i.e. MEDLINE, EMBASE, CINAHL, PsycINFO, and Web of Science) and the reference lists of relevant articles. Review methods: This systematic review was conducted in line with the Center for Reviews and Dissemination Handbook and reported according to the PRISMA guideline. Only original research focusing on determinants of fall prevention implementation in residential care facilities was included. We used the Mixed Method Appraisal Tool for quality appraisal. Thematic analysis was performed for qualitative data; quantitative data were analyzed descriptively. To synthesize the results, we used the framework of Grol and colleagues that describes six healthcare levels wherein implementation barriers and facilitators can be identified. Results: We found eight relevant studies, identifying 44 determinants that influence implementation. Of these, 17 were facilitators and 27 were barriers. Results indicated that the social and organizational levels have the greatest number of influencing factors (9 and 14, respectively), whereas resident and economical/political levels have the least (3 and 4, respectively). The most cited facilitators were good communication and facility equipment availability, while staff feeling overwhelmed, helpless, frustrated and concerned about their ability to control fall management, staffing issues, limited knowledge and skills (i.e., general clinical skill deficiencies, poor fall management skills or lack of computer skills); and poor communication were the most cited barriers. Conclusion: Successful implementation of fall prevention depends on many factors across different healthcare levels. The focus of implementation interventions, however, should be on modifiable barriers and facilitators such as communication, knowledge, and skills. Effective fall prevention must consist of multifactorial interventions that target each resident's fall risk profile, and should be tailored to overcome context-specific barriers and put into action the identified facilitators.© 2017 Elsevier Ltd. All rights reserved.What is already known about the topic? Multifactorial interventions, tailored to each resident's fall risk profile, can reduce the number of falls and recurrent fallers under highly controlled circumstances, but seems to be ineffective under "real-world" conditions, presumably due to poor implementation.Successful implementation of complex, multifactorial interventions in clinical practice involves a tailored, multifaceted approach based on a good understanding of barriers and facilitators for implementation. No reviews exist that comprehensively summarize the evidence on fall prevention implementation barriers and facilitators in residential care settings. What this paper addsSeventeen facilitators and 27 barriers that ...

Objectives: To evaluate and compare the predictive accuracy of fall history, staff clinical judgment, the Care Home Falls Screen (CaHFRiS) and the Fall Risk Classification Algorithm (FRiCA). Design: Prospective multicenter cohort study with six months' follow-up. Setting & participants: 420 residents from 15 nursing homes participated. Methods: Fall history, clinical judgment of staff (i.e., physiotherapists, nurses and nurses' aides), the CaHFRiS and the FRiCA were assessed at baseline and falls were documented in the follow-up period. Predictive accuracy was calculated at one, three and six months by means of sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, Youden Index and overall accuracy. Results: In total, 658 falls occurred and 50.2% of the residents had at least one fall with an average fall rate of 1.57 (SD=2.78, range 0-20) per resident. The overall accuracy for all screening methods at all measuring points ranged from 54.8% to 66.5%. Fall history, FRiCA and a CaHFRiS score of ≥ 4 had better sensitivity, ranging from 64.4% to 80.8%, compared to the clinical judgment of all disciplines (sensitivity ranging from 47.4% to 71.2%). The negative predictive value (ranging from 92.9% at one month to 59.6% at six months) had higher scores for fall history, FRiCA and a CaHFRiS score of ≥ 4. Specificity ranged from 50.3% at one month to 77.5% at six months, with better specificity for clinical judgment of physiotherapists and worse specificity for FRiCA. Positive predictive value ranged from 22.2% (clinical judgment of nurses' aides) at one month to 67.8% at six months (clinical judgment of physiotherapists). Conclusion & implications:No strong recommendations can be made for the use of any screening method. More research on identifying residents with the highest fall risk is crucial, as these residents benefit the most from multifactorial assessments and subsequent tailored interventions.

One of the effects of late-stage dementia is the loss of the ability to communicate verbally. Patients become unable to call for help if they feel uncomfortable. The first objective of this article was to record facial expressions of bedridden demented elderly. For this purpose, we developed a video acquisition system (ViAS) that records synchronized video coming from two cameras. Each camera delivers uncompressed color images of 1,024 x 768 pixels, up to 30 frames per second. It is the first time that such a system has been placed in a patient's room. The second objective was to simultaneously label these video recordings with respect to discomfort expressions of the patients. Therefore, we developed a Digital Discomfort Labeling Tool (DDLT). This tool provides an easy-to-use software representation on a tablet PC of validated "paper" discomfort scales. With ViAS and DDLT, 80 different datasets were obtained of about 15 minutes of recordings. Approximately 80% of the recorded datasets delivered the labeled video recordings. The remainder were not usable due to under- or overexposed images and due to the patients being out of view as the system was not properly replaced after care. In one of 6 observed patients, nurses recognized a higher discomfort level that would not have been observed without the DDLT.

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