Malnutrition and pressure ulcer risk in adults in Australian health care facilities

Aims To determine the effect of nutritional status on the presence and severity of pressure ulcers in statewide? public healthcare facilities, in Queensland, Australia. Research Methods A multicentre, cross sectional audit of nutritional status of a convenience sample of subjects was carried out as part of a large audit of pressure ulcers in a sample of state based public healthcare facilities in 2002 and 2003. Dietitians in 20 hospitals and six residential aged care facilities conducted single day nutritional status audits of 2208 acute and 839 aged care subjects using the Subjective Global Assessment. The effect of nutritional status on the presence, highest stage and number of pressure ulcers was determined by logistic regression in a model controlling for age, gender, medical specialty and facility location. The potential clustering effect of facility was accounted for in the model using an analysis of correlated data approach. Results Subjects with malnutrition had an adjusted odds risk of 2.6 (95% CI 1.8-3.5, p<0.001) of having a pressure ulcer in acute facilities and 2.0 (95% CI 1.5-2.7, p<0.001) for residential aged care facilities. There was also increased odds risk of having a pressure ulcer, having a higher stage pressure ulcer and a higher number of pressure ulcers with increased severity of malnutrition. Conclusion Malnutrition was associated with at least twice the odds risk of having a pressure ulcer of in public healthcare facilities in Queensland. Action must be taken to identify, prevent and treat malnutrition, especially in patients at risk of pressure ulcer.

The costs arising from pressure ulcers attributable to malnutrition

Aim To estimate the economic consequences of pressure ulcers attributable to malnutrition. Method Statistical models were developed to predict the number of cases of pressure ulcer, associated bed days lost and the dollar value of these losses in public hospitals in 2002/2003 in Queensland, Australia. The following input parameters were specified and appropriate probability distributions fitted • Number of at risk discharges per annum • Incidence rate for pressure ulcer • Attributable fraction of malnutrition in the development of pressure ulcer • Independent effect of pressure ulcer on length of hospital stay • Opportunity cost of hospital bed day One thousand random re-samples were made and the results expressed as (output) probabilistic distributions. Results The model predicts a mean 16060 (SD 5 671) bed days lost and corresponding mean economic cost of AU$12 968 668 (SD AU$4 924 148) (EUROS 6 925 268 SD 2 629 495; US$ 7 288 391 SD 2 767 371) of pressure ulcer attributable to malnutrition in 2002/2003 in public hospitals in Queensland, Australia. Conclusion The cost of pressure ulcer attributable to malnutrition in bed days and dollar terms are substantial. The model only considers costs of increased length of stay associated with pressure ulcer and not other factors associated with care.

The malnutrition screening tool is a useful tool for identifying malnutrition risk in residential aged care

Background: The Malnutrition Screening Tool (MST) is a valid nutrition screening tool in the acute hospital setting but has not been assessed in residential aged care facilities. The aim of this secondary analysis was to determine whether the MST could be a useful nutrition screening tool when compared with a full nutrition assessment by Subjective Global Assessment (SGA) in the residential aged care setting. ----- Methods: Two hundred and eighty-five residents (29% male; mean age: 84 ± 9 years) from eight residential aged care facilities in Australia participated. A secondary analysis of data collected during a nutrition intervention study was conducted. The MST consists of two questions related to recent weight loss and appetite. While the MST was not specifically applied, weight loss and appetite information was available and an estimated MST score (0-5) calculated. Nutritional status was assessed by a research assistant trained in using SGA. ----- Results: Malnutrition prevalence was 42.8% (122 malnourished out of 285 residents). Compared to the SGA, the MST was an effective predictor of nutritional risk (sensitivity = 83.6%, specificity = 65.6%, positive predictive value = 0.65, negative predictive value =0.84). ----- Conclusions: The components of the MST have acceptable sensitivity and specificity suggesting it can play a valuable role in quickly identifying malnutrition risk in the residential aged care setting. Further prospective research using the MST tool against a broader array of objective and subjective nutritional parameters is required to confirm its validity as a screening tool in aged care settings.

Comparison of three expert elicitation methods for logistic regression on predicting the presence of the threatened brush-tailed rock-wallaby petrogale penicillata

Numerous expert elicitation methods have been suggested for generalised linear models (GLMs). This paper compares three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression. These methods were trialled on two experts in order to model the habitat suitability of the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The first elicitation approach is a geographically assisted indirect predictive method with a geographic information system (GIS) interface. The second approach is a predictive indirect method which uses an interactive graphical tool. The third method uses a questionnaire to elicit expert knowledge directly about the impact of a habitat variable on the response. Two variables (slope and aspect) are used to examine prior and posterior distributions of the three methods. The results indicate that there are some similarities and dissimilarities between the expert informed priors of the two experts formulated from the different approaches. The choice of elicitation method depends on the statistical knowledge of the expert, their mapping skills, time constraints, accessibility to experts and funding available. This trial reveals that expert knowledge can be important when modelling rare event data, such as threatened species, because experts can provide additional information that may not be represented in the dataset. However care must be taken with the way in which this information is elicited and formulated.