1. Public sector residential aged care: identifying novel associations between quality indicators and other demographic and health-related factors.
- Author
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Moore, Kirsten J., Doyle, Colleen J., Dunning, Trisha L., Hague, Ann T., Lloyd, Lucas A., Bourke, Jo, and Gill, Stephen D.
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ELDER care , *PRESSURE ulcers , *CHI-squared test , *CONFIDENCE intervals , *STATISTICAL correlation , *DEMENTIA , *ACCIDENTAL falls , *INFORMATION storage & retrieval systems , *MEDICAL databases , *LONGITUDINAL method , *ORTHOPEDIC apparatus , *MEDICAL protocols , *WEIGHT loss , *QUALITATIVE research , *LOGISTIC regression analysis , *PUBLIC sector , *BODY mass index , *RESIDENTIAL care , *REPEATED measures design , *RETROSPECTIVE studies , *POLYPHARMACY , *ADVERSE health care events , *ODDS ratio , *PREVENTION - Abstract
Objective. To explore associations among quality indicators (QI; e.g. pressure ulcers, falls and/or fractures, physical restraint, use of multiple medications, unplanned weight loss) of the Victorian Public Sector Residential Aged Care Services (VPSRACS) with other demographic and health-related factors. Methods. Data for 380 residents over a 3-month period were extracted retrospectively from client databases at four VPSRAC facilities. Results. Four significant logistic regression models were developed. The strongest models related to falls and polypharmacy. Significant associations for these models included the following: (1) residents with a higher body mass index were 6% less likely (95% confidence interval (CI) 1%-11%) to fall, whereas high levels of cognitive impairment increased the risk of falling by 8% (95% CI 2%-14%); (2) being ambulant with a gait aid more than doubled the risk of falling compared with non-ambulant residents (95% CI 19%-546%); and (3) higher cognitive impairment was associated with a 6% (95% CI 1%-11%) reduction in the likelihood of polypharmacy. Conclusions. Identification of significant relationships between the VPSRACS QI and other demographic and health-related factors is a preliminary step towards a more in-depth understanding of the factors that influence the QI and predict adverse events. [ABSTRACT FROM AUTHOR]
- Published
- 2014
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