Zahid Ansari1, David Dunt, Shyamali C Dharmage. 1. Department of Epidemiology and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia.
Abstract
BACKGROUND AND OBJECTIVE: Effective and timely management of COPD should reduce the risk of hospitalization. The purpose of this study was to describe variations in COPD hospital admission rates as an indicator of the adequacy of primary care services. METHODS: Age- and gender-standardized hospital admission rates of COPD (2003-04) were computed using the Victorian Admitted Episodes Dataset. Potential predictors of COPD admission rates were identified from various sources of data. These included degree of remoteness, socio-economic status, number of general practitioners per population, percentage of Aboriginal or Torres Strait Islander people, percentage of smokers, and co-morbidities. These data were aggregated at the primary care partnership level, which are voluntary alliances of one or more local government areas in Victoria. Weighted least squares regression was used to identify the predictors of COPD admission rates. RESULTS: Hospital admission rates for COPD were higher in rural than in metropolitan areas of Victoria. Multiple logistic regression analysis showed significant associations between COPD admission rates and socio-economic status, smoking rates and remoteness of the area. CONCLUSIONS: Small-area analyses of COPD admission rates highlighted significant differences between urban and rural areas. The influence of socio-economic status and degree of remoteness on COPD admission rates highlights opportunities for policymakers to develop targeted public health and health service interventions.
BACKGROUND AND OBJECTIVE: Effective and timely management of COPD should reduce the risk of hospitalization. The purpose of this study was to describe variations in COPD hospital admission rates as an indicator of the adequacy of primary care services. METHODS: Age- and gender-standardized hospital admission rates of COPD (2003-04) were computed using the Victorian Admitted Episodes Dataset. Potential predictors of COPD admission rates were identified from various sources of data. These included degree of remoteness, socio-economic status, number of general practitioners per population, percentage of Aboriginal or Torres Strait Islander people, percentage of smokers, and co-morbidities. These data were aggregated at the primary care partnership level, which are voluntary alliances of one or more local government areas in Victoria. Weighted least squares regression was used to identify the predictors of COPD admission rates. RESULTS: Hospital admission rates for COPD were higher in rural than in metropolitan areas of Victoria. Multiple logistic regression analysis showed significant associations between COPD admission rates and socio-economic status, smoking rates and remoteness of the area. CONCLUSIONS: Small-area analyses of COPD admission rates highlighted significant differences between urban and rural areas. The influence of socio-economic status and degree of remoteness on COPD admission rates highlights opportunities for policymakers to develop targeted public health and health service interventions.
Authors: Bradford E Jackson; Sumihiro Suzuki; David Coultas; Fenghsiu Su; Ravi Lingineni; Karan P Singh; Alfred Bartolucci; Sejong Bae Journal: Int J Chron Obstruct Pulmon Dis Date: 2011-11-11