Dataset Information

Simulating the effects of a clinical guidelines screening algorithm for fall risk in community dwelling older adults.

ABSTRACT: BACKGROUND:The current guidelines for fall prevention in community-dwelling older adults issued by the American Geriatrics Society and British Geriatrics Society (AGS/BGS) indicate an algorithm for identifying who is at increased risk of falling. The predictive accuracy of this algorithm has never been assessed, nor have the consequences that its introduction in clinical practice would bring about. AIMS:To evaluate this risk screening algorithm, estimating its predictive accuracy and its potential impact. METHODS:The analyses are based on 438 community-dwelling older adults, participating in the InCHIANTI study. We analysed different tests for gait and balance assessment. We compared the AGS/BGS algorithm with alternative strategies for fall prevention not based on fall risk evaluation. RESULTS:The AGS/BGS screening algorithm (using TUG, cut-off 13.5 s) has a sensitivity for single falls of 35.8% (95% confidence interval 23.2%-52.7%) and a specificity of 84.0% (79.3%-88.4%). It marks 18.0% (13.7%-22.4%) of the older population as at high risk. A policy of targeting people with preventive intervention regardless of their individual risk could be as effective as the policy based on risk screening but at the price of intervening on 17.3% (4.1%-34.0%) more people of the older population. DISCUSSION:This study is the first that validates and estimates the impact of the screening algorithm of these guidelines. Main limitations are related to some modelling assumptions. CONCLUSIONS:The AGS/BGS screening algorithm has low sensitivity. Nevertheless, its adoption would bring benefits with respect to policies of preventive interventions that act regardless of individual risk assessment.

SUBMITTER: Palumbo P

PROVIDER: S-EPMC6661027 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Simulating the effects of a clinical guidelines screening algorithm for fall risk in community dwelling older adults.

Palumbo Pierpaolo P Becker Clemens C Bandinelli Stefania S Chiari Lorenzo L

Aging clinical and experimental research 20181019 8

<h4>Background</h4>The current guidelines for fall prevention in community-dwelling older adults issued by the American Geriatrics Society and British Geriatrics Society (AGS/BGS) indicate an algorithm for identifying who is at increased risk of falling. The predictive accuracy of this algorithm has never been assessed, nor have the consequences that its introduction in clinical practice would bring about.<h4>Aims</h4>To evaluate this risk screening algorithm, estimating its predictive accuracy ...[more]

PMID: 30341644

Similar Datasets

Project description:IntroductionFall rates and fall-related injuries among community-dwelling older adults (≥65 years) are expected to increase rapidly, due to the aging population worldwide. Fall prevention programs (FPPs), consisting of strength and balance exercises, have been proven effective in reducing fall rates among older adults. However, these FPPs have not reached their full potential as most programs are under-enrolled. Therefore, this study aims to identify promising strategies that promote participation in FPPs among community-dwelling older adults.MethodsThis is an exploratory qualitative study. Previously, barriers and facilitators for participation in FPPs by older adults had been identified. Next, six strategies had been designed using the Intervention Mapping approach: (1) reframing; (2) informing about benefits; (3) raising awareness of risks; (4) involving social environment; (5) offering tailored intervention; (6) arranging practicalities. Strategies were validated during semi-structured interviews with community-dwelling older adults (n = 12) at risk of falling. Interviews were audio-recorded, transcribed, and analyzed following a qualitative thematic methodology, with a hybrid approach.ResultsAll strategies were considered important by at least some of the respondents. However, two strategies stood out: (1) reframing 'aging' and 'fall prevention': respondents preferred to be approached differently, taking a 'life course' perspective about falls, and avoiding confronting words; and (2) 'informing about benefits' (e.g., 'living independently for longer'); which was mentioned to improve the understanding of the relevance of participating in FPPs. Other strategies were considered important to take into account too, but opinions varied more strongly.DiscussionThis study provides insight into potential strategies to stimulate older adults to participate in FPPs. Results suggest that reframing 'aging' and 'fall prevention' may facilitate the dialogue about fall prevention, by communicating differently about the topic, for example 'staying fit and healthy', while focusing on the benefits of participating in FPPs. Gaining insight into the strategies' effectiveness and working mechanisms is an area for future research. This could lead to practical recommendations and help professionals to enhance older adults' participation in FPPs. Currently, the strategies are further developed to be applied and evaluated for effectiveness in multiple field labs in a central Dutch region (Utrecht).

Project description:Background and objectivesMedication exposure is a potential risk factor for falls and subsequent death and functional decline among older adults. However, controversy remains on the best way to assess medication exposure and which approach best predicts falls. The objective of the current study was to examine the association between different measures of medication exposure and falls risk among community-dwelling older adults.Research design and methodsThis retrospective cohort study was conducted using Falls Free PA program data and a linked prescription claims data from Pennsylvania's Pharmaceutical Assistance Contract for the Elderly program. Participants were community-dwelling older adults living in Pennsylvania, United States. Three measures of medication exposure were assessed: (a) total number of regular medications (polypharmacy); (b) counts of potentially inappropriate medications derived from current prescription guidance tools (Fall Risk-Increasing Drugs [FRIDs], Beers Criteria); and (c) medication burden indices based on pharmacologic mechanisms (Anticholinergic Cognitive Burden, Drug Burden Index) all derived from claims data. The associations between the different medication risk measures and self-reported falls incidence were examined with univariate and multivariable negative binomial regression models to estimate incidence rate ratios (IRRs).ResultsOverall 343 older adults were included and there were 236 months with falls during 2,316 activity-adjusted person-months (10.2 falls per 100 activity-adjusted person-months). Of the 6 measures of medication risk assessed in multivariate models, only the use of 2 or more FRIDs (adjusted IRR 1.67 [95% CI: 1.04-2.68]) independently predicted falls risk. Among the 13 FRID drug classes, the only FRID class associated with an increased fall risk was antidepressants.Discussion and implicationsThe presence of multiple FRIDs in a prescription is an independent risk factor for falls, even in older adults with few medications. Further investigation is required to examine whether deprescribing focused on FRIDs effectively prevents falls among this population.

Dataset Information

Simulating the effects of a clinical guidelines screening algorithm for fall risk in community dwelling older adults.

Publications

Simulating the effects of a clinical guidelines screening algorithm for fall risk in community dwelling older adults.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets