Selection of Top 10 Quality Indicators for Nutrition Therapy

Background: The identification of useful quality indicators for nutrition therapy (QINTs) is of great interest and a challenge. This study attempted to identify the 10 QINTs that best suit the practice of quality control in nutrition therapy (NT) by evaluating the opinion of experts in NT with the use of psychometric techniques and statistical tools. Methods: Thirty-six QINTs available for clinical application in Brazil were assessed in 2 distinct phases. In phase 1, 26 nutrition experts ranked QINTs by scoring 4 attributes (utility, simplicity, objectivity, low cost) to assess each QINT on a 5-point Likert scale. The top 10 QINTs were identified from the 10 best scores obtained, and the reliability of expert opinion for each indicator was assessed by Cronbach's alpha. In phase 2, experts provided feedback regarding the selected top 10 QINTs by answering 2 closed questions. Results: The top 10 QINTs, in descending order, are the frequency of nutrition screening of hospitalized patients, diarrhea, involuntary withdrawal of enteral feeding tubes, feeding tube obstruction, fasting longer than 24 hours, glycemic dysfunction, estimated energy expenditure and protein needs, central venous catheter infection, compliance of NT indication, and frequency of application of subjective global assessment. Opinions were consistent among the interviewed experts. During feedback, 96% of experts were satisfied with the top 10 QINTs, and 100% had considered them in accordance with their previous opinion. Conclusion: The top 10 QINTs were identified according to their usefulness in clinical practice by obtaining adequate agreement and representativeness of opinion of nutrition experts. (Nutr Clin Pract. 2012;27:261-267)

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.