Comparative analysis of undernutrition screening and diagnostic tools as predictors of hospitalisation costs

BackgroundUndernutrition is associated with higher hospitalisation costs. The present study aims (i) to explore whether undernutrition status at hospital admission, as evaluated by different screening and diagnostic tools, can predict patient's hospitalisation costs and (ii) to provide an updated economic analysis of undernutrition burden. MethodsA prospective study was conducted in a university hospital. Participants' (n=637) nutritional risk was evaluated within 72h of admission using the Nutritional Risk Screening (NRS-2002) and the Malnutrition Universal Screening Tool (MUST'). Undernutrition status was determined by Academy of Nutrition and Dietetics (AND) and American Society for Parenteral and Enteral Nutrition (ASPEN) recommended clinical characteristics and by the Patient Generated Subjective Global Assessment (PG-SGA). The hospitalisation cost was calculated for each inpatient using the diagnosis-related group system. Multivariable linear regression analysis was conducted to identify predictors of hospitalisation costs via percentage deviation from the mean cost, after adjustment for patients' characteristics and comorbidities. ResultsUndernutrition risk according to NRS-2002 and high undernutrition risk according to MUST' increased patient's costs, respectively, by 21.1% [95% confidence interval (CI)=9.0-33.2%] and 28.8% (95% CI=13.7-39.9%). Severe undernutrition by AND-ASPEN recommended clinical characteristics and by PG-SGA was also associated with higher hospitalisation costs, respectively 19.4% (95% CI=7.3-31.5%) and 27.5% (95% CI=14.0-41.1%). The cost of a nutritionally-at-risk or undernourished patient is between Euro416 (95% CI=Euro156-675) and Euro617 (95% CI=Euro293-855) higher than the average of the respective diagnosis-related group. ConclusionsUndernutrition is a predictor of hospitalisation costs, increasing costs by between 19% and 29%. Undernutrition screening tools have an ability for predicting hospitalisation costs similar to that of diagnostic tools. An updated analysis of undernutrition associated costs was provided, highlighting the economic burden of undernutrition.