Small Area Analysis of Ambulatory Care Sensitive Conditions in Victoria, Australia

被引:15
作者
Ansari, Zahid [1 ,3 ]
Rowe, Stacey [2 ]
Ansari, Humaira [4 ]
Sindall, Colin [1 ]
机构
[1] Dept Hlth, Hlth Intelligence Unit, Melbourne, Vic 3000, Australia
[2] Dept Hlth, Hlth Protect Branch, Melbourne, Vic, Australia
[3] Monash Univ, Dept Epidemiol & Prevent Med, Clayton, Vic 3800, Australia
[4] Univ Melbourne, Sch Med, Parkville, Vic 3052, Australia
关键词
HEALTH-CARE; MEDICAL-CARE; PREVENTABLE HOSPITALIZATIONS; BEHAVIORAL-MODEL; OLDER WOMEN; ACCESS; RATES; URBAN; POPULATION; VARIABLES;
D O I
10.1089/pop.2012.0047
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Ambulatory care sensitive conditions (ACSCs) are used as a measure of access to primary health care. The purpose of this study was to identify factors associated with variation in ACSC admissions at a small area level in Victoria, Australia. The study was ecologic, using Victorian Primary Care Partnerships (PCPs) as the unit of analysis. Data sources were the Victorian Admitted Episodes Dataset, census data from the Australian Bureau of Statistics, and the Victorian Population Health Survey. Age- and sex-adjusted total ACSC admission rates were calculated, and weighted least squares multiple linear regression was used to examine the associations of total ACSC admission rates by various predictor variables. Key variables were categorized into 1 of 4 framework components for analyzing access and use of health care services: predisposing, enabling, need, or structural. Enabling characteristics explained 61.70% of the variation in ACSC admission rates across PCPs. Socioeconomic characteristics (income, education) and percentage with poor self-rated health were important factors in explaining variations in ACSC admissions at a small area-level [R-2 = 0.77]. Community-level variables differentially affect access to primary health care, with significant variation by socioeconomic status. This analytical approach will assist researchers to identify community-level predicators of access across populations at locations, including factors that may be affected by policy change. (Population Health Management 2013; 16: 190-200)
引用
收藏
页码:190 / 200
页数:11
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