alston-testingtheaccuracy-2022.pdf (561.77 kB)
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
journal contribution
posted on 2022-01-01, 00:00 authored by Laura AlstonLaura Alston, M Green, Melanie NicholsMelanie Nichols, S R Partridge, A Buccheri, Kristy BoltonKristy Bolton, Vincent VersaceVincent Versace, M Field, A J Launder, A Lily, Steven AllenderSteven Allender, Liliana OrellanaLiliana OrellanaThis 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
History
Journal
NutrientsVolume
14Issue
1Article number
205Pagination
1 - 9Publisher
MDPILocation
Basel, SwitzerlandPublisher DOI
Link to full text
ISSN
2072-6643eISSN
2072-6643Language
engPublication classification
C1 Refereed article in a scholarly journalUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC