TY - JOUR
T1 - Malnutrition, Health and the Role of Machine Learning in Clinical Setting
AU - Sharma, Vaibhav
AU - Sharma, Vishakha
AU - Khan, Ayesha
AU - Wassmer, David J.
AU - Schoenholtz, Matthew D.
AU - Hontecillas, Raquel
AU - Bassaganya-Riera, Josep
AU - Zand, Ramin
AU - Abedi, Vida
N1 - Publisher Copyright:
© Copyright © 2020 Sharma, Sharma, Khan, Wassmer, Schoenholtz, Hontecillas, Bassaganya-Riera, Zand and Abedi.
PY - 2020/4/15
Y1 - 2020/4/15
N2 - Nutrition plays a vital role in health and the recovery process. Deficiencies in macronutrients and micronutrients can impact the development and progression of various disorders. However, malnutrition screening tools and their utility in the clinical setting remain largely understudied. In this study, we summarize the importance of nutritional adequacy and its association with neurological, cardiovascular, and immune-related disorders. We also examine general and specific malnutrition assessment tools utilized in healthcare settings. Since the implementation of the screening process in 2016, malnutrition data from hospitalized patients in the Geisinger Health System is presented and discussed as a case study. Clinical data from five Geisinger hospitals shows that ~10% of all admitted patients are acknowledged for having some form of nutritional deficiency, from which about 60–80% of the patients are targeted for a more comprehensive assessment. Finally, we conclude that with a reflection on how technological advances, specifically machine learning-based algorithms, can be integrated into electronic health records to provide decision support system to care providers in the identification and management of patients at higher risk of malnutrition.
AB - Nutrition plays a vital role in health and the recovery process. Deficiencies in macronutrients and micronutrients can impact the development and progression of various disorders. However, malnutrition screening tools and their utility in the clinical setting remain largely understudied. In this study, we summarize the importance of nutritional adequacy and its association with neurological, cardiovascular, and immune-related disorders. We also examine general and specific malnutrition assessment tools utilized in healthcare settings. Since the implementation of the screening process in 2016, malnutrition data from hospitalized patients in the Geisinger Health System is presented and discussed as a case study. Clinical data from five Geisinger hospitals shows that ~10% of all admitted patients are acknowledged for having some form of nutritional deficiency, from which about 60–80% of the patients are targeted for a more comprehensive assessment. Finally, we conclude that with a reflection on how technological advances, specifically machine learning-based algorithms, can be integrated into electronic health records to provide decision support system to care providers in the identification and management of patients at higher risk of malnutrition.
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U2 - 10.3389/fnut.2020.00044
DO - 10.3389/fnut.2020.00044
M3 - Review article
C2 - 32351968
AN - SCOPUS:85083965928
SN - 2296-861X
VL - 7
JO - Frontiers in Nutrition
JF - Frontiers in Nutrition
M1 - 44
ER -