Hospital menu assessment tool

Full-text downloads: since deposited on 22 Sep More statistics Home Browse research About. Contribution to Journal Journal Article. Hannan-Jones, Mary orcid. This work is covered by copyright. These two values represent the energy and protein contents for soft texture food lower value and normal texture food higher value. Observers simply select the pictures that best represent the amount of food consumed. Additionally, the PDAT comprises eight possible combinations of menu items.

The food weighing method was used as a gold standard. The leftovers grams of each individual food item remaining on the plate were then subtracted from the standard portion provided to each patient. Health care staff consisting of eight dietitians, seven nurses, and 22 serving assistants were recruited through total sampling and trained to estimate the food intake of patients using the PDAT.

Additionally, the selection criteria for patients were a adult patients from a nonintensive care department and b not fasting or abstaining from oral food intake. The exclusion criteria were patients receiving only enteral or parenteral nutrition.

Health care staff were asked to estimate the intakes using the PDAT tool for plate waste for breakfast and lunch meals of two to three patients per day, for a total of 5 to 6 days.

Energy and protein intakes were estimated by the staff using the known energy and protein content of the meals, included as a ready reckoner in the PDAT. Accordingly, inter-rater reliability among dietitians, nurses, and serving assistants was measured from these observations.

The estimation of intake from the different observers using PDAT was then compared to the data obtained by the food weighing method as the gold standard. Food weighing was conducted by the researcher after the assessment using PDAT was completed, by using an electronic kitchen scale 2 kg capacity scale weighed to the nearest 0.

The energy calculation from comparing two groups indicated that a minimum sample size of 50 meals was required in order to detect a mean difference in dietary energy intake between the test method and reference method of 52 kcal given the within group standard deviation [SD] kcal. Pearson correlation was performed to assess the association of nutrient intake between two methods of food intake assessment.

A paired t -test was used to compare the differences in mean nutrient intakes between the two methods. The agreement level between the weight method and the PDAT was calculated as agreement beyond chance using the kappa statistic.

The sensitivity and specificity were calculated with regard to the clinical use of the PDAT targeting its capacity to identify the patients who have inadequate food intake, and who may be considered at risk of malnutrition. These values were then assessed to represent relevant quantities of food not consumed with potential negative clinical consequences. Sensitivity is the percentage of patients who have inadequate food intake and identified as being at risk by the PDAT, while specificity is the percentage of patients who have adequate food intake identified as not at risk of malnutrition by the PDAT.

An analysis of the area under the curve of receiver operating characteristic ROC was performed to determine the accuracy of the PDAT, which was able to identify whether the patients were at risk or not at risk of malnutrition. Furthermore, an inter-rater reliability analysis of estimated nutrient intake using PDAT among health care staff was obtained using intraclass correlation coefficient.

Likewise, differences in macronutrient intake assessed by health care staff of different backgrounds were tested by the analysis of variance ANOVA test. The majority of both health care staff and patients were females More than half of the patients Table 4 illustrates the accuracy of the PDAT in estimating the six consumption levels of patient food intake.

Essentially, there were some differences in the accuracy of the PDAT relative to food characteristics. Accuracy of macronutrient intakes estimated by the PDAT in comparison with food weighing. Health care staff estimates of percentage food consumed by patients compared to food weighing method. However, the sensitivity for this kind of food was high, and was as much as Furthermore, the ROC curves for all types of dishes were more than 0.

There was good consensus for the estimation of nutrient intake using PDAT among the health care staff from different backgrounds, with an intraclass correlation coefficient of 0. The health care staff did not tend to overestimate consumption; however, for protein, carbohydrate, and fat, the health care staff tended to marginally underestimate consumption, in comparison to the actual weight nutrient intake of patients.

Values of sensitivity and specificity of PDAT according to different levels of plate waste food weighing. Inter-rater reliability analysis of estimated nutrient intake using PDAT among health care staff and comparison with food weighing. However, Palmer et al 14 have found poor correlations in energy intake between a ready reckoner food chart and weighed food intake in breakfast and lunch meals in a sample of 15 patients over 43 intake days.

It appears that PDAT may provide a valid estimation of macronutrient intake with fair accuracy and could be useful for the monitoring of dietary intake. Both PDAT and food weighing also displayed a very close consensus beyond chance k for staple food, animal source protein, and non-animal source protein. Non-animal source protein resulted in the least consensus but was still above the clinically reasonable validity limit of 0.

This may be due to the fact that dishes such as bean curd and tempe are often prepared and cooked in a way that changes its original portion and consistency. Low consensus among dietary intake estimation methods for specific dishes was also reported by Scognamiglio et al 22 who discovered a consensus of as low as 0. In addition, these tools will help staff proactively identify and correct regulatory issues to improve compliance and as well as decrease the number and length of surveys and cited deficiencies.

These checklists are being distributed solely for informational purposes and are not intended to serve as an interpretation to the regulations. Public Health Nutrition. Developing a valid meal assessment tool for hospital patients. Taste, temperature, and presentation predict satisfaction with foodservices in a Canadian continuing-care hospital. OBJECTIVE To identify food, service, and patient variables associated with high satisfaction with foodservices in a continuing-care hospital that serves, primarily, geriatric patients and patients … Expand.

A systematic review of hospital foodservice patient satisfaction studies. Journal of the Academy of Nutrition and Dietetics.

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