semi-automation of nutritional risk screening in the hospital results in systematic scoring

semi-automation of nutritional risk screening in the hospital results in systematic scoring

;J. Fournier;M. Coutaz;H. Hertzog;P. Piccot;J. Lamon;M.M. Berger
clinical nutrition experimental 2016 Vol. 8 pp. 1-8
202
fournier2016clinicalsemi-automation

Abstract

Background: Hospital malnutrition is a costly phenomenon as it contributes to complicate and prolong hospital stays. Optimal care of malnutrition requires the identification of patients at risk with an early screening: the latter is not systematically carried out due to lack of specific education, but also of time and user-friendly tools. The aim was to achieve a systematic nutritional screening of all hospital patients and to increase the recording of the diagnosis in the discharge letter. Methods: Multidisciplinary work group to create nutrition protocols and equivalences between three patient assessment tools: nursing ePA-AC, nutritional risk screening (NRS) and Mini Nutritional Assessment (MNA-SF); mapping of the related variables of the 3 tools. Validation by the physician of automatically generates score triggers a dietician visit. Validation of malnutrition by the dietician prompts malnutrition diagnosis proposal for the discharge letter. Results: After the pilot phase, NRS or MNA-SF scores are now available in all patients of the 2 first implementation sites (geriatry, surgery). Assessment of the patients stress level generated difficulties (over-scoring) that required additional teaching. Doctor validation of pathological scores has increased request for dietician visits. Economical impact of increased diagnosis in discharge letter is yet to come. Conclusion: The semi-automation of nutritional risk screening is possible without increasing the nurse workload, by mapping their nursing activities to specific nutrition scores adapted to the patient age. The increased diagnosis of malnutrition within 48 h of the hospital admission should lead to better care and optimize hospital reimbursement.

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