Nutrition screening process for patients in an acute public hospital servicing an elderly, culturally diverse population

Malnutrition screening tool use in a New Zealand hospital: Reliability and rates of malnutrition screening on admission

AIMS

This research aimed to assess the rate and reliability of routine nurse-completed malnutrition screening and report the prevalence of malnutrition risk on admission to Christchurch Hospital.

METHODS

Student dietitians administered the Malnutrition Screening Tool to patients in three speciality wards within 48 h of admission. Student dietitians' Malnutrition Screening Tool scores were compared against documented nurse-completed Malnutrition Screening Tool scores. Data were analysed using descriptive statistics, Fisher's exact test, and Cohen's kappa tests (interrater reliability ⱪ). A p-value <0.05 was considered statistically significant.

RESULTS

Student dietitians, using the Malnutrition Screening Tool, screened 360 (96%) of 377 eligible patients while nurses screened 332 (88%) patients. Student dietitians and nurses screened 119 patients (33%) and 63 patients (18%) respectively at risk of malnutrition. There was fair agreement (ⱪ = 0.311) in Malnutrition Screening Tool total scores between nurses and student dietitians. There was a significant difference in the proportion of patients screened at risk of malnutrition between nurses and student dietitians (p < 0.0001).

CONCLUSION

Malnutrition risk remains high in acute care settings. Nurses were less likely to screen patients as at risk of malnutrition than student dietitians. Regular support and training in using Malnutrition Screening Tool may help improve the rate and reliability of routine malnutrition screening.

What do we know about frailty in the acute care setting? A scoping review

Background

The ability of acute care providers to cope with the influx of frail older patients is increasingly stressed, and changes need to be made to improve care provided to older adults. Our purpose was to conduct a scoping review to map and synthesize the literature addressing frailty in the acute care setting in order to understand how to tackle this challenge. We also aimed to highlight the current gaps in frailty research.

Methods

This scoping review included original research articles with acutely-ill Emergency Medical Services (EMS) or hospitalized older patients who were identified as frail by the authors. We searched Medline, CINAHL, Embase, PsycINFO, Eric, and Cochrane from January 2000 to September 2015.

Results

Our database search initially resulted in 8658 articles and 617 were eligible. In 67% of the articles the authors identified their participants as frail but did not report on how they measured frailty. Among the 204 articles that did measure frailty, the most common disciplines were geriatrics (14%), emergency department (14%), and general medicine (11%). In total, 89 measures were used. This included 13 established tools, used in 51% of the articles, and 35 non-frailty tools, used in 24% of the articles. The most commonly used tools were the Clinical Frailty Scale, the Frailty Index, and the Frailty Phenotype (12% each). Most often (44%) researchers used frailty tools to predict adverse health outcomes. In 74% of the cases frailty predicted the outcome examined, typically mortality and length of stay.

Conclusions

Most studies (83%) were conducted in non-geriatric disciplines and two thirds of the articles identified participants as frail without measuring frailty. There was great variability in tools used and more recently published studies were more likely to use established frailty tools. Overall, frailty appears to be a good predictor of adverse health outcomes. For frailty to be implemented in clinical practice frailty tools should help formulate the care plan and improve shared decision making. How this will happen has yet to be determined.

Electronic supplementary material

The online version of this article (10.1186/s12877-018-0823-2) contains supplementary material, which is available to authorized users.

The Indigenous Australian Malnutrition Project: the burden and impact of malnutrition in Aboriginal Australian and Torres Strait Islander hospital inpatients, and validation of a malnutrition screening tool for use in hospitals-study rationale and protocol

BACKGROUND

Malnutrition is associated with adverse outcomes for hospital inpatients and is a significant economic burden on hospitals. Malnutrition is frequently under-recognised in this setting and valid screening and early diagnosis are important for timely nutritional management. Aboriginal Australian and/or Torres Strait Islander peoples (Indigenous Australians) are likely to be at increased risk of malnutrition due to their disproportionate burden, pattern and age-distribution of chronic diseases. Despite this increased risk, the burden and impact of malnutrition in Indigenous Australians is poorly understood. Furthermore, a suitable screening tool has not been validated for this vulnerable patient group. The aim of this study is to determine the burden of malnutrition, understand its impact, and validate a malnutrition screening tool for Indigenous Australian inpatients.

METHODS

This project involves cross-sectional, prospective cohort and diagnostic validation methodologies to assess the burden and impact of malnutrition and to validate a malnutrition screening tool. A target of 752 adult Indigenous and non-Indigenous Australian inpatients will be recruited across three different public hospitals in the Northern Territory and far north Queensland of Australia. Cross-sectional data collection will be used to determine the prevalence of malnutrition using the Subjective Global Assessment and to stratify participants based on the International Consensus Guideline Committee malnutrition aetiology-diagnostic framework. Subjects will then be followed prospectively to measure short and long-term health outcomes such as length of hospital stay, in-hospital mortality, 30-day and 6-month readmission rates. Finally, the utility of a new screening tool, the Australian Nutrition Tool, will be assessed against an existing screening tool, the malnutrition screening tool, used in these settings and the malnutrition reference standard, the Subjective Global Assessment.

DISCUSSION

Indigenous Australians continue to experience poorer levels of health than non-Indigenous Australians and issues such as food insecurity, poor diet, and a disproportionate burden of chronic disease play a key contributing role for malnutrition in Indigenous Australians. To improve the health and hospital outcomes of Indigenous and non-Indigenous Australians, it is important that patients are routinely screened using a validated screening tool. It is also imperative that the burden and impact of malnutrition is properly understood, and fully appreciated, so that early and appropriate nutritional management can be provided to this group of hospital patients.

The malnutrition screening tool versus objective measures to detect malnutrition in hip fracture

BACKGROUND

The Malnutrition Screening Tool (MST) is the most commonly used screening tool in Australia. Poor screening tool sensitivity may lead to an under-diagnosis of malnutrition, with potential patient and economic ramifications. The present study aimed to determine whether the MST or anthropometric parameters adequately detect malnutrition in patients who were admitted to a hip fracture unit.

METHODS

Data were analysed for a prospective convenience sample (n = 100). MST screening was independently undertaken by nursing staff and a nutrition assistant. Mid upper arm circumference (MUAC) was measured by a trained nutrition assistant. Nutritional risk [MST score ≥ 2, body mass index (BMI) < 22 kg m(-2) , or MUAC < 25 cm] was compared with malnutrition diagnosed by accredited practicing dietitians using International Classification of Diseases version 10-Australian Modification (ICD10-AM) coding criteria.

RESULTS

Malnutrition prevalence was 37.5% using ICD10-AM criteria. Delirium, dementia or preadmission cognitive impairment was present in 65% of patients. The BMI as a nutrition risk screen was the most valid predictor of malnutrition (sensitivity 75%; specificity 93%; positive predictive value 73%; negative predictive value 84%). Nursing MST screening was the least valid (sensitivity 73%; specificity 55%; positive predictive value 50%; negative predictive value 77%). There was only fair agreement between nursing and nutrition assistant screening using the MST (κ = 0.28).

CONCLUSIONS

In this population with a high prevalence of delirium and dementia, further investigation is warranted into the performance of nutrition screening tools and anthropometric parameters such as BMI. All tools failed to predict a considerable number of patients with malnutrition. This may result in the under-diagnosis and treatment of malnutrition, leading to case-mix funding losses.