- Finch, Caroline, Stephan, Karen, Shee, Anna Wong, Hill, Keith, Haines, Terry, Clemson, Lindy, Day, Lesley
- Authors: Finch, Caroline , Stephan, Karen , Shee, Anna Wong , Hill, Keith , Haines, Terry , Clemson, Lindy , Day, Lesley
- Date: 2015
- Type: Text , Journal article
- Relation: Injury Prevention Vol. 21, no. 4 (2015), p. 254-259
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Relation: http://purl.org/au-research/grants/nhmrc/1058737
- Relation: http://purl.org/au-research/grants/nhmrc/546282
- Full Text: false
- Reviewed:
- Description: Background: There has been limited research investigating the relationship between injurious falls and hospital resource use. The aims of this study were to identify clusters of community-dwelling older people in the general population who are at increased risk of being admitted to hospital following a fall and how those clusters differed in their use of hospital resources. Methods: Analysis of routinely collected hospital admissions data relating to 45 374 fall-related admissions in Victorian community-dwelling older adults aged ≥65 years that occurred during 2008/2009 to 2010/2011. Fall-related admission episodes were identified based on being admitted from a private residence to hospital with a principal diagnosis of injury (International Classification of Diseases (ICD)-10-AM codes S00 to T75) and having a first external cause of a fall (ICD-10-AM codes W00 to W19). A cluster analysis was performed to identify homogeneous groups using demographic details of patients and information on the presence of comorbidities. Hospital length of stay (LOS) was compared across clusters using competing risks regression. Results: Clusters based on area of residence, demographic factors (age, gender, marital status, country of birth) and the presence of comorbidities were identified. Clusters representing hospitalised fallers with comorbidities were associated with longer LOS compared with other cluster groups. Clusters delineated by demographic factors were also associated with increased LOS. Conclusions: All patients with comorbidity, and older women without comorbidities, stay in hospital longer following a fall and hence consume a disproportionate share of hospital resources. These findings have important implications for the targeting of falls prevention interventions for community-dwelling older people. © 2015, BMJ Publishing Group. All right reserved.
- Vu, Trang, Finch, Caroline, Day, Lesley
- Authors: Vu, Trang , Finch, Caroline , Day, Lesley
- Date: 2012
- Type: Text , Journal article
- Relation: Injury Prevention Vol. 18, no. Supplement 1 (2012), p. A121
- Full Text: false
- Reviewed:
- Description: Background: Nearly half to 60% of falls in community-dwelling older people aged 65+ years result in physical injuries and 20%–50% of these require medical attention, including emergency department visit and hospitalisation. Fallers who stay in hospital longer than would be expected based on the primary injury diagnosis create an excess financial burden on the health system and represent a priority target group for fall prevention. Objectives: To identify and characterise high-length-of-stay (HLOS) patients among community-dwelling older people aged 65+ years hospitalised for fall-related injury. Methods: We analysed hospital discharge data from Victoria, Australia, to identify and characterise HLOS patients among community-dwelling older people aged 65+ years hospitalised for fall-related injury. We defined an episode as HLOS if the length of stay (LOS) was more than three times the average LOS for a particular diagnosis-related group. Results: Between 2005/06 and 2007/08 6822 patients (14.2% of the study group of which 73.8% were women) had ≥1 episode classified as HLOS. The HLOS patients accounted for 19.9% of episodes and 39.9% of bed days. HLOS patients were similar to non-HLOS patients in terms of indigenous status, in-hospital mortality and ethnicity. However, HLOS patients were older, less likely to be married, less likely to have hospital insurance and more likely to have comorbidity than non-HLOS patients. Significance/Contribution to the Field: This study identifies priority groups for a targeted prevention approach.
A protocol for evidence-based targeting and evaluation of statewide strategies for preventing falls among community-dwelling older people in Victoria, Australia
- Day, Lesley, Finch, Caroline, Hill, Keith, Haines, Terry, Clemson, Lindy, Thomas, Margaret, Thompson, Catherine
- Authors: Day, Lesley , Finch, Caroline , Hill, Keith , Haines, Terry , Clemson, Lindy , Thomas, Margaret , Thompson, Catherine
- Date: 2011
- Type: Text , Journal article
- Relation: Injury Prevention Vol. 17, no. 2 (2011), p. 1-8
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Relation: http://purl.org/au-research/grants/nhmrc/546282
- Full Text:
- Reviewed:
- Description: Background: Falls are a significant threat to the safety, health and independence of older citizens. Despite the now substantial evidence about effective falls prevention interventions, translation into falls reductions has not yet been fully realised. While the hip fracture rate is decreasing, the number and rate of fall-related hospital admissions among older people is increasing. The challenge now is to deliver the most effective interventions efficiently at a population level, and for these interventions to be taken up by older people. Objective: To support the development, and evaluation of, effective falls prevention policy and practice in the state of Victoria, Australia. Methods: The RE-AIM model (Reach, Efficacy, Adoption, Implementation, Maintenance) was used to identify strategies for an effective programme. Research objectives were developed to support the strategies. These include: (1) identification of subgroups of older people most frequently admitted to hospital for falls; (2) examining the acceptability of established falls interventions; (3) identification of factors that encourage and support relevant lifestyle changes; (4) identifying opportunities to incorporate confirmed interventions in existing programmes and services; (5) developing guidelines for sustainability. The research results will subsequently guide strategy details for the falls prevention plan. RE-AIM will provide the framework for the evaluation structure. Outcome measures: Measures to monitor the implementation of the selected interventions will be determined for each intervention, based on the five key factors of the RE-AIM model. The overall effect of the falls prevention plan will be monitored by time series analysis of fall-related hospital admission rates for community-dwelling older people.
- Authors: Day, Lesley , Finch, Caroline , Hill, Keith , Haines, Terry , Clemson, Lindy , Thomas, Margaret , Thompson, Catherine
- Date: 2011
- Type: Text , Journal article
- Relation: Injury Prevention Vol. 17, no. 2 (2011), p. 1-8
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Relation: http://purl.org/au-research/grants/nhmrc/546282
- Full Text:
- Reviewed:
- Description: Background: Falls are a significant threat to the safety, health and independence of older citizens. Despite the now substantial evidence about effective falls prevention interventions, translation into falls reductions has not yet been fully realised. While the hip fracture rate is decreasing, the number and rate of fall-related hospital admissions among older people is increasing. The challenge now is to deliver the most effective interventions efficiently at a population level, and for these interventions to be taken up by older people. Objective: To support the development, and evaluation of, effective falls prevention policy and practice in the state of Victoria, Australia. Methods: The RE-AIM model (Reach, Efficacy, Adoption, Implementation, Maintenance) was used to identify strategies for an effective programme. Research objectives were developed to support the strategies. These include: (1) identification of subgroups of older people most frequently admitted to hospital for falls; (2) examining the acceptability of established falls interventions; (3) identification of factors that encourage and support relevant lifestyle changes; (4) identifying opportunities to incorporate confirmed interventions in existing programmes and services; (5) developing guidelines for sustainability. The research results will subsequently guide strategy details for the falls prevention plan. RE-AIM will provide the framework for the evaluation structure. Outcome measures: Measures to monitor the implementation of the selected interventions will be determined for each intervention, based on the five key factors of the RE-AIM model. The overall effect of the falls prevention plan will be monitored by time series analysis of fall-related hospital admission rates for community-dwelling older people.
Statistical modelling for falls count data
- Ullah, Shahid, Finch, Caroline, Day, Lesley
- Authors: Ullah, Shahid , Finch, Caroline , Day, Lesley
- Date: 2010
- Type: Text , Journal article
- Relation: Accident Analysis and Prevention Vol. 42, no. 2 (2010), p. 384-392
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: Falls and their injury outcomes have count distributions that are highly skewed toward the right with clumping at zero, posing analytical challenges. Different modelling approaches have been used in the published literature to describe falls count distributions, often without consideration of the underlying statistical and modelling assumptions. This paper compares the use of modified Poisson and negative binomial (NB) models as alternatives to Poisson (P) regression, for the analysis of fall outcome counts. Four different count-based regression models (P, NB, zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB)) were each individually fitted to four separate fall count datasets from Australia, New Zealand and United States. The finite mixtures of P and NB regression models were also compared to the standard NB model. Both analytical (F, Vuong and bootstrap tests) and graphical approaches were used to select and compare models. Simulation studies assessed the size and power of each model fit. This study confirms that falls count distributions are over-dispersed, but not dispersed due to excess zero counts or heterogeneous population. Accordingly, the P model generally provided the poorest fit to all datasets. The fit improved significantly with NB and both zero-inflated models. The fit was also improved with the NB model, compared to finite mixtures of both P and NB regression models. Although there was little difference in fit between NB and ZINB models, in the interests of parsimony it is recommended that future studies involving modelling of falls count data routinely use the NB models in preference to the P or ZINB or finite mixture distribution. The fact that these conclusions apply across four separate datasets from four different samples of older people participating in studies of different methodology, adds strength to this general guiding principle. © 2009 Elsevier Ltd. All rights reserved.
- Authors: Ullah, Shahid , Finch, Caroline , Day, Lesley
- Date: 2010
- Type: Text , Journal article
- Relation: Accident Analysis and Prevention Vol. 42, no. 2 (2010), p. 384-392
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: Falls and their injury outcomes have count distributions that are highly skewed toward the right with clumping at zero, posing analytical challenges. Different modelling approaches have been used in the published literature to describe falls count distributions, often without consideration of the underlying statistical and modelling assumptions. This paper compares the use of modified Poisson and negative binomial (NB) models as alternatives to Poisson (P) regression, for the analysis of fall outcome counts. Four different count-based regression models (P, NB, zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB)) were each individually fitted to four separate fall count datasets from Australia, New Zealand and United States. The finite mixtures of P and NB regression models were also compared to the standard NB model. Both analytical (F, Vuong and bootstrap tests) and graphical approaches were used to select and compare models. Simulation studies assessed the size and power of each model fit. This study confirms that falls count distributions are over-dispersed, but not dispersed due to excess zero counts or heterogeneous population. Accordingly, the P model generally provided the poorest fit to all datasets. The fit improved significantly with NB and both zero-inflated models. The fit was also improved with the NB model, compared to finite mixtures of both P and NB regression models. Although there was little difference in fit between NB and ZINB models, in the interests of parsimony it is recommended that future studies involving modelling of falls count data routinely use the NB models in preference to the P or ZINB or finite mixture distribution. The fact that these conclusions apply across four separate datasets from four different samples of older people participating in studies of different methodology, adds strength to this general guiding principle. © 2009 Elsevier Ltd. All rights reserved.
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