Implementation of evidence-based clinical nutrition: Usability of the new digital platform clinicalnutrition.science.

Abstract

Aim of the study: Malnutrition is a common and complex challenge in inpatient and outpatient settings, associated with increased risk of morbidity and mortality. Its management is often neglected, despite strong evidence of the benefits of adequate nutritional therapy. We introduced clinicalnutrition.science (https://clinicalnutrition.science/en/), a digital platform that provides healthcare professionals with easy online access to evidence and streamlines the nutritional care process. The aim of this study was to assess the usability and to validate improvements in nutritional management when the digital platform is used by healthcare professionals.

Methods: The usability study, conducted from 28 September to 16 November 2023, involved 56 healthcare professionals from the University Hospital of Bern and the Cantonal Hospital of Aarau. In an adapted cross-over study design, participants completed key steps of nutritional management for a simulated hepatology and oncology case both with and without the clinicalnutrition.science platform. Usability was assessed using the validated Healthcare Systems Usability Scale questionnaire, supplemented by collection of demographic data. Subgroup analysis was performed for recommended protein and energy intakes by different professional representatives.

Results: Clinicalnutrition.science achieved a good overall usability score of 71.8%. Use of the platform significantly improved the protein intake recommendation (p = 0.03; median 96.5 and 80.0 g/d) and the basal metabolic rate estimate (p <0.01; median 1420.8 and 1755.5 kcal/d) of the simulated oncology case. The variance in protein and energy intake recommendations, basal metabolic rate estimation and energy deficit estimation was reduced by using the digital platform. These improvements were achieved without increasing the time required to complete key steps in nutritional management for the two patient cases (median between 10.5 and 15.0 minutes; p = 0.09 and p = 0.67) and without prior training on the platform. There was no effect on the malnutrition detection rate, the selection of an appropriate nutritional product or the identification of the most appropriate guideline.

Conclusions: The use of clinicalnutrition.science improved evidence-based clinical practice in prescribing personalised nutritional therapy and increased the accuracy of both protein and energy intake recommendations, without increasing the time taken to complete key steps in the nutritional management process.