Nutritional status classification in the Department of Veterans Affairs.

The Department of Veterans Affairs (VA) Nutrition Status Classification scheme uses clinical data that are routinely collected on admission or shortly thereafter for quick inpatient nutrition screening. In this scheme, patients are assigned to 1 of 4 classification levels according to 7 individual indicators. The indicators include nutrition history, unintentional weight loss as a percent of usual body weight, percent of ideal body weight, diet, diagnosis, albumin, and total lymphocyte count. After ratings (1 to 4) are assigned to each of the 7 indicators, overall nutritional status for each patient is determined by an algorithm. The VA classification system includes many of the same criteria used in other nutritional status classifications. Where it differs is in the greater emphasis on the use of objective criteria and in the rigorous evaluation of reliability and validity that went into its development. Because of these extra measures, the VA classification can be used for prioritizing workload, as well as for determining staff requirements and for comparing workload and productivity across health care facilities. So that others might benefit from using this system, this article provides information on how the classification scheme was developed and explains how it is used.

Comparison of professional judgment versus an algorithm for nutrition status classification.

OBJECTIVES: The classification of a patient's nutrition status is important for identifying patients who require nutrition care, for designing effective nutrition interventions, and for measuring severity of illness. The objective of this study was to evaluate the reliability and validity of two variants of the Department of Veterans Affairs' nutrition status classification: professional judgment versus an algorithm. METHODS: The study consisted of two phases, both of which included providing a sample of approximately 60 registered dietitians and 60 clinical dietetic technicians with data on 16 (phase I) and 20 (phase II) patients, to which they assigned nutrition statuses using both professional judgment and the algorithm. Improvements in instructions and training were implemented between the two phases. Interrater reliability of the responses was calculated, and content validity was measured by comparing the staff's responses with those of an expert panel. RESULTS: Reliability improved significantly between phases for both professional judgment and the algorithm. Greater reliability and validity were observed with use of the algorithm, by both dietitians and technicians, during both phases. CONCLUSION: Classification of a patient's nutrition status is important in the delivery of cost-effective health care. The Department of Veterans Affairs' nutrition status classification is a good one for assessing nutrition status quickly and reliably, especially when an algorithm is used. The results underscore the advantages of a classification system based on an algorithm when the system is designed to be used by many different staff across multiple facilities.

Some diets that meet the Dietary Goals for the United States.

Few people in the United States have diets with proportions of complex carbohydrate as high and proportions of protein, fat, and sugar as low as proposed in the second edition of the Dietary Goals for the United States by the Senate Select Committee on Nutrition and Human Needs. Sample diets, including low-calorie diets for adults, were planned to meet the Recommended Dietary Allowances and the Dietary Goals. Two possible "first steps" in modifying diets to meet the Goals explored the use of: (a) Specified ranges rather than specific Goals and (b) some but not all of the Goals.