Testing the accuracy of a bedside screening tool framework to clinical records for identification of patients at risk of malnutrition in a rural setting: An exploratory study Alston, Laura, Green, M, Nichols, Melanie, Partridge, SR, Buccheri, A, Bolton, Kristy, Versace, Vincent, Field, M, Launder, AJ, Lily, A, Allender, Steven and Orellana, Liliana 2022, Testing the accuracy of a bedside screening tool framework to clinical records for identification of patients at risk of malnutrition in a rural setting: An exploratory study, Nutrients, vol. 14, no. 1, pp. 1-9, doi: 10.3390/nu14010205. Attached Files Name Description MIMEType Size Downloads Title Testing the accuracy of a bedside screening tool framework to clinical records for identification of patients at risk of malnutrition in a rural setting: An exploratory study Author(s) Alston, Laura orcid.org/0000-0002-4551-8845 Green, M Nichols, Melanie orcid.org/0000-0002-7834-5899 Partridge, SR Buccheri, A Bolton, Kristy orcid.org/0000-0001-6721-4503 Versace, Vincent orcid.org/0000-0002-8514-1763 Field, M Launder, AJ Lily, A Allender, Steven orcid.org/0000-0002-4842-3294 Orellana, Liliana orcid.org/0000-0003-3736-4337 Journal name Nutrients Volume number 14 Issue number 1 Article ID 205 Start page 1 End page 9 Total pages 9 Publisher MDPI Place of publication Basel, Switzerland Publication date 2022 ISSN 2072-6643 2072-6643 Keyword(s) CARE CRITERIA IMPACT Life Sciences & Biomedicine malnutrition risk malnutrition screening NUTRITION Nutrition & Dietetics PREVALENCE rural rural health services Science & Technology Summary This study aimed to explore the diagnostic accuracy of the Patient-Generated Subjective Global Assessment (PG-SGA) malnutrition risk screening tool when used to score patients based on their electronic medical records (EMR), compared to bedside screening interviews. In-patients at a rural health service were screened at the bedside (n = 50) using the PG-SGA, generating a bedside score. Clinical notes within EMRs were then independently screened by blinded researchers. The accuracy of the EMR score was assessed against the bedside score using area under the receiver operating curve (AUC), sensitivity, and specificity. Participants were 62% female and 32% had conditions associated with malnutrition, with a mean age of 70.6 years (SD 14.9). The EMR score had moderate diagnostic accuracy relative to PG-SGA bedside screen, AUC 0.74 (95% CI: 0.59–0.89). The accuracy, specificity and sensitivity of the EMR score was highest for patients with a score of 7, indicating EMR screen is more likely to detect patients at risk of malnutrition. This exploratory study showed that applying the PG-SGA screening tool to EMRs had enough sensitivity and specificity for identifying patients at risk of malnutrition to warrant further exploration in low-resource settings Language eng DOI 10.3390/nu14010205 Field of Research 0908 Food Sciences 1111 Nutrition and Dietetics HERDC Research category C1 Refereed article in a scholarly journal Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30161288 Document type: Journal Article Collections: Faculty of Health School of Health and Social Development Open Access Collection Institute for Health Transformation Related Links Link Description Link to full-text (open access)   Connect to Elements publication management system Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Wed, 12 Jan 2022, 07:31:07 EST Wed, 12 Jan 2022, 14:18:38 EST Fri, 28 Jan 2022, 05:04:13 EST Sat, 19 Feb 2022, 01:31:16 EST Wed, 23 Mar 2022, 13:00:22 EST Wed, 23 Mar 2022, 15:20:23 EST Wed, 23 Mar 2022, 15:39:27 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 7 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Wed, 12 Jan 2022, 07:31:07 EST