Model of Hospital Nutrition Intervention Based on Concepts of Center of Excellence in Health
Author(s)
Valencia CF1, Pinzon Espitia OL2, Lopez Gutierrez PA3, Pombo L3
1Javeriana University / OES, Bogotá DC, Colombia, 2National University of Colombia / Méderi, Bogotá DC, Colombia, 3OES, Bogotá DC, Colombia
Introduction: Healthcare processes must uphold their design and execution in order to guarantee optimal clinical results for hospitalized patients whilst maintaining sustainable expenses. These are fundamental principles for the creation and implementation of a center of excellence for healthcare and as such also apply for institutional nutrition intervention. Objective: To design and disseminate a model of intrahospital nutritional care based on the principles of a center of excellence that will minimize adverse events related to malnutrition. Methods: All through 2016, a systemic review of literature regarding intrahospital nutritional intervention and the processes involved was carried out. Consequently, a nutritional healthcare model for hospitalized patients based on the previously revised literature was designed. The model was modified according to nutritional expert’s feedback. Simultaneously, the model was applied in a healthcare institution in order to corroborate its applicability, its value for continuous institutional improvement and its validity. Results: The designed nutritional healthcare model implemented on patient admission included four sequential facets. Firstly a personalized risk assessment upon admission and follow up, secondly establishing clearly defined nutritional and clinical objectives, thirdly impact measurement and finally and implementing feedback models for continuous education. Conclusions: Model construction in healthcare, such as this one, lead to processes of higher value. These better patient outcomes and rationalize resources.
Conference/Value in Health Info
2017-09, ISPOR Latin America 2017, Sao Paulo, Brazil
Value in Health, Vol. 20, No. 9 (October 2017)
Code
PRM26
Topic
Methodological & Statistical Research
Topic Subcategory
Confounding, Selection Bias Correction, Causal Inference
Disease
Multiple Diseases