A Preliminary Report on the Functioning and Data Collection Capabilities of a Web-based Nutrition Algorithm for Patients With Chronic Kidney Disease

Abstract

The purpose of this study was to test the functional and data collection capabilities of an online nutrition algorithm for patients with chronic kidney disease by comparing dietitian-selected nutrition diagnoses, etiologies, and interventions in hemodialysis (HD) patients with and without diabetes mellitus (DM). Data were collected using an online nutrition screening tool and algorithm for HD patients based on the American Dietetic Association's Nutrition Care Process. Data were collected by dietitians in the United States, New Zealand, Australia, and Brazil. Patients undergoing HD under the care of a participating dietitian and who were deemed at nutrition risk at visit 1 were eligible to participate. Other inclusion criteria included age >19 years, able to speak and write English, and not receiving hospice care or the international equivalent. Data were available on 26 patients (50% males, 39% with DM). Mean baseline values were as follows: age, 56.3 years; body mass index, 28.2 kg/m(2); and serum albumin (bromocresol green), 36.8 g/L (3.68 g/dL). There were no statistically significant differences between DM and non-DM patients except in mean hemoglobin A1C. Differences in the frequency of selection of diagnoses, etiology, and intervention categories were compared. The algorithm is under continuous development using input from participating dietitians, but its use was generally considered feasible. The initial data analysis showed that the algorithm is an effective method for collecting data on HD patients. In this small cohort, patients with and without DM had similar dietitian-selected nutrition diagnoses and etiologies, but had statistically significant differences in the dietitian-selected nutrition interventions that were selected most frequently. Health Care Team Referral was selected more often in DM patients (P < .003) and Recommendation of Specific Foods was selected more often in non-DM patients (P < .0170). This preliminary analysis shows that the algorithm can be used as both a clinical and a data collection tool. The test analysis, although small in sample size, showed interesting differences in the care of DM and non-DM HD patients.