Literature DB >> 34673925

Do home adaptation interventions help to reduce emergency fall admissions? A national longitudinal data-linkage study of 657,536 older adults living in Wales (UK) between 2010 and 2017.

Joe Hollinghurst1, Helen Daniels1, Richard Fry1, Ashley Akbari1, Sarah Rodgers2, Alan Watkins1, Sarah Hillcoat-Nallétamby1, Neil Williams3, Silviya Nikolova4, David Meads4, Andy Clegg4.   

Abstract

BACKGROUND: falls are common in older people, but evidence for the effectiveness of preventative home adaptations is limited. AIM: determine whether a national home adaptation service, Care&Repair Cymru (C&RC), identified individuals at risk of falls occurring at home and reduced the likelihood of falls. STUDY
DESIGN: retrospective longitudinal controlled non-randomised intervention cohort study.
SETTING: our cohort consisted of 657,536 individuals aged 60+ living in Wales (UK) between 1 January 2010 and 31 December 2017. About 123,729 individuals received a home adaptation service.
METHODS: we created a dataset with up to 41 quarterly observations per person. For each quarter, we observed if a fall occurred at home that resulted in either an emergency department or an emergency hospital admission. We analysed the data using multilevel logistic regression.
RESULTS: compared to the control group, C&RC clients had higher odds of falling, with an odds ratio (OR [95% confidence interval]) of 1.93 [1.87, 2.00]. Falls odds was higher for females (1.44 [1.42, 1.46]), older age (1.07 [1.07, 1.07]), increased frailty (mild 1.57 [1.55, 1.60], moderate 2.31 [2.26, 2.35], severe 3.05 [2.96, 3.13]), and deprivation (most deprived compared to least: 1.16 [1.13, 1.19]). Client fall odds decreased post-intervention; OR 0.97 [0.96, 0.97] per quarter. Regional variation existed for falls (5.8%), with most variation at the individual level (31.3%).
CONCLUSIONS: C&RC identified people more likely to have an emergency fall admission occurring at home, and their service reduced the odds of falling post-intervention. Service provisioning should meet the needs of an individual and need varies by personal and regional circumstance.
© The Author(s) 2021. Published by Oxford University Press on behalf of the British Geriatrics Society.

Entities:  

Keywords:  falls; falls prevention; frailty; older people

Mesh:

Year:  2022        PMID: 34673925      PMCID: PMC8753038          DOI: 10.1093/ageing/afab201

Source DB:  PubMed          Journal:  Age Ageing        ISSN: 0002-0729            Impact factor:   12.782


  16 in total

Review 1.  Falls in older people: epidemiology, risk factors and strategies for prevention.

Authors:  Laurence Z Rubenstein
Journal:  Age Ageing       Date:  2006-09       Impact factor: 10.668

2.  Residential Anonymous Linking Fields (RALFs): a novel information infrastructure to study the interaction between the environment and individuals' health.

Authors:  Sarah E Rodgers; Ronan A Lyons; Rohan Dsilva; Kerina H Jones; Caroline J Brooks; David V Ford; Gareth John; Jean-Philippe Verplancke
Journal:  J Public Health (Oxf)       Date:  2009-05-15       Impact factor: 2.341

3.  Frailty as a Risk Factor for Falls Among Community Dwelling People: Evidence From a Meta-Analysis.

Authors:  Mei-Hsun Cheng; Shu-Fang Chang
Journal:  J Nurs Scholarsh       Date:  2017-07-29       Impact factor: 3.176

4.  A multifactorial approach to understanding fall risk in older people.

Authors:  Kim Delbaere; Jacqueline C T Close; Jörg Heim; Perminder S Sachdev; Henry Brodaty; Melissa J Slavin; Nicole A Kochan; Stephen R Lord
Journal:  J Am Geriatr Soc       Date:  2010-09       Impact factor: 5.562

Review 5.  Using Electronic Health Records for Population Health Research: A Review of Methods and Applications.

Authors:  Joan A Casey; Brian S Schwartz; Walter F Stewart; Nancy E Adler
Journal:  Annu Rev Public Health       Date:  2015-12-11       Impact factor: 21.981

6.  Forecasted trends in disability and life expectancy in England and Wales up to 2025: a modelling study.

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Journal:  Lancet Public Health       Date:  2017-05-23

7.  The SAIL databank: linking multiple health and social care datasets.

Authors:  Ronan A Lyons; Kerina H Jones; Gareth John; Caroline J Brooks; Jean-Philippe Verplancke; David V Ford; Ginevra Brown; Ken Leake
Journal:  BMC Med Inform Decis Mak       Date:  2009-01-16       Impact factor: 2.796

8.  A case study of the Secure Anonymous Information Linkage (SAIL) Gateway: a privacy-protecting remote access system for health-related research and evaluation.

Authors:  Kerina H Jones; David V Ford; Chris Jones; Rohan Dsilva; Simon Thompson; Caroline J Brooks; Martin L Heaven; Daniel S Thayer; Cynthia L McNerney; Ronan A Lyons
Journal:  J Biomed Inform       Date:  2014-01-15       Impact factor: 6.317

9.  Development and validation of an electronic frailty index using routine primary care electronic health record data.

Authors:  Andrew Clegg; Chris Bates; John Young; Ronan Ryan; Linda Nichols; Elizabeth Ann Teale; Mohammed A Mohammed; John Parry; Tom Marshall
Journal:  Age Ageing       Date:  2016-03-03       Impact factor: 10.668

10.  Measuring follow-up time in routinely-collected health datasets: Challenges and solutions.

Authors:  Daniel Thayer; Arfon Rees; Jon Kennedy; Huw Collins; Dan Harris; Julian Halcox; Luca Ruschetti; Richard Noyce; Caroline Brooks
Journal:  PLoS One       Date:  2020-02-11       Impact factor: 3.240

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