Literature DB >> 25234612

The accuracy of food intake charts completed by nursing staff as part of usual care when no additional training in completing intake tools is provided.

Michelle Palmer1, Katrina Miller2, Sally Noble3.   

Abstract

BACKGROUND & AIMS: Dietary intake tools that require ongoing training may not be valid and useful in a busy acute care setting. We compared nutrient intakes of inpatients using weighed food records (WFR) with food charts completed by nursing staff who hadn't received recent intake tool training.
METHODS: The weight of individual foods remaining on patients' main meal trays was deducted from a reference tray weight. Mid-meal consumption was determined by patient report. WFR and food charts were converted to nutrients using suppliers' information. Food charts were also converted using a ready reckoner. Agreement between methods was tested using t-tests, cross-classification, correlations and Bland-Altman plots.
RESULTS: Forty-three intake days were compared (n = 15 inpatients, 77 ± 8 yrs, 60%M). Most (93%) food intake charts were incomplete. Energy and protein intakes across meals were similar between food charts and WFR (754 ± 442 kCal, 29.9 ± 19.7 g protein; p > 0.05). Significant correlations were observed at breakfast between WFR and food chart ready reckoner (energy: r = 0.793; protein: r = 0.588; p < 0.01), and breakfast, morning tea and lunch using the food chart supplier's information (energy: r = 0.767-0.898, p < 0.05; protein: r = 0.786-0.912, p < 0.05). Cross-classification was unacceptable (11-33% gross misclassification), and mealtime limits of agreement were wide (-497-+552 kCal, -27-+36 g protein).
CONCLUSIONS: The poor agreement between intake methods suggests that food charts completed by nursing staff as part of usual care with no additional intake tool training may not accurately measure inpatient intake. Given that nursing staff may require ongoing training on completion of intake tools, alternative efficient and accurate means of measuring inpatient intake may be needed. Crown
Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Energy; Food intake chart; Hospital; Protein; Validation

Mesh:

Substances:

Year:  2014        PMID: 25234612     DOI: 10.1016/j.clnu.2014.09.001

Source DB:  PubMed          Journal:  Clin Nutr        ISSN: 0261-5614            Impact factor:   7.324


  9 in total

1.  The My Meal Intake Tool (M-MIT): Validity of a Patient Self- Assessment for Food and Fluid Intake at a Single Meal.

Authors:  J McCullough; H Keller
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2.  A simple dietary assessment tool to monitor food intake of hospitalized adult patients.

Authors:  Dwi Budiningsari; Suzana Shahar; Zahara Abdul Manaf; Susetyowati Susetyowati
Journal:  J Multidiscip Healthc       Date:  2016-07-26

3.  Evaluation of Pictorial Dietary Assessment Tool for Hospitalized Patients with Diabetes: Cost, Accuracy, and User Satisfaction Analysis.

Authors:  Dwi Budiningsari; Suzana Shahar; Zahara Abdul Manaf; Nor Azlin Mohd Nordin; Susetyowati Susetyowati
Journal:  Nutrients       Date:  2017-12-28       Impact factor: 5.717

4.  Comparing Computerised Dietary Analysis with a Ready Reckoner in a Real World Setting: Is Technology an Improvement?

Authors:  Jessica Paciepnik; Judi Porter
Journal:  Nutrients       Date:  2017-01-31       Impact factor: 5.717

5.  Engaging hospitalised patients in their nutrition care using technology: development of the NUTRI-TEC intervention.

Authors:  Shelley Roberts; Zane Hopper; Wendy Chaboyer; Ruben Gonzalez; Merrilyn Banks; Ben Desbrow; Andrea P Marshall
Journal:  BMC Health Serv Res       Date:  2020-02-27       Impact factor: 2.655

6.  Using Technology to Promote Patient Engagement in Nutrition Care: A Feasibility Study.

Authors:  Shelley Roberts; Wendy Chaboyer; Zane Hopper; Andrea P Marshall
Journal:  Nutrients       Date:  2021-01-22       Impact factor: 5.717

7.  A Cross-Sectional Reproducibility Study of a Standard Camera Sensor Using Artificial Intelligence to Assess Food Items: The FoodIntech Project.

Authors:  Virginie Van Wymelbeke-Delannoy; Charles Juhel; Hugo Bole; Amadou-Khalilou Sow; Charline Guyot; Farah Belbaghdadi; Olivier Brousse; Michel Paindavoine
Journal:  Nutrients       Date:  2022-01-05       Impact factor: 5.717

8.  Accuracy of an Artificial Intelligence-Based Model for Estimating Leftover Liquid Food in Hospitals: Validation Study.

Authors:  Masato Tagi; Mari Tajiri; Yasuhiro Hamada; Yoshifumi Wakata; Xiao Shan; Kazumi Ozaki; Masanori Kubota; Sosuke Amano; Hiroshi Sakaue; Yoshiko Suzuki; Jun Hirose
Journal:  JMIR Form Res       Date:  2022-05-10

9.  Evaluation of an Innovative Method for Calculating Energy Intake of Hospitalized Patients.

Authors:  Sheila Cox Sullivan; Melinda M Bopp; Paula K Roberson; Shelly Lensing; Dennis H Sullivan
Journal:  Nutrients       Date:  2016-09-09       Impact factor: 5.717

  9 in total

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