What is the Malnutrition Universal Screening Tool (MUST)?
The Malnutrition Universal Screening Tool (MUST) is a five-step screening tool developed by the British Association for Parenteral and Enteral Nutrition (BAPEN). It is designed to identify adults who are malnourished or at risk of malnutrition and is widely endorsed for use across various care settings, including hospitals, community clinics, and care homes. The tool uses a simple, yet robust, methodology to ensure quick and reliable screening by healthcare professionals.
The Five-Step Process of MUST
- Body Mass Index (BMI) Score: The first step involves calculating the patient's BMI (weight in kg / height in m²). A scoring system is applied based on the BMI value: a score of 0 for BMI > 20 kg/m², 1 for 18.5–20 kg/m², and 2 for BMI < 18.5 kg/m².
- Unplanned Weight Loss Score: The tool assesses the percentage of unplanned weight loss over the past 3–6 months. A score of 0 is for <5% loss, 1 for 5–10% loss, and 2 for >10% loss. This indicates a recent deterioration in nutritional status.
- Acute Disease Effect Score: This step evaluates the impact of an acute illness on nutritional intake. If a patient has an acute disease and has had, or is likely to have, no nutritional intake for more than five days, a score of 2 is added.
- Overall Risk Score: The scores from steps 1, 2, and 3 are added together to determine the overall risk of malnutrition. A total score of 0 indicates low risk, 1 is medium risk, and 2 or more indicates high risk.
- Management Guidelines: Based on the overall risk score, clinicians are guided toward appropriate management protocols, which may include dietary monitoring, nutritional support, or referral to a dietitian.
How Effective is the MUST Tool?
Evidence from numerous studies confirms the effectiveness of the MUST tool, demonstrating its high accuracy and reliability, particularly in hospital settings. It is a well-validated instrument for detecting protein-energy malnutrition and predicting patient outcomes like mortality and length of hospital stay.
Strengths and Predictive Power
- High Diagnostic Accuracy: A 2024 meta-analysis found that MUST showed high accuracy for detecting malnutrition risk in hospitalized adults, with a sensitivity of 0.84 and specificity of 0.85 when compared to the Subjective Global Assessment (SGA). A high sensitivity means it is good at correctly identifying those with malnutrition, and high specificity means it correctly identifies those without it.
- Predictive Validity: Studies have shown that a high MUST score can predict poorer patient outcomes. For instance, research on cardiovascular surgery patients demonstrated that MUST was the most effective tool for predicting a decline in Activities of Daily Living (ADL) post-surgery. Higher MUST scores are also associated with longer hospital stays and increased complications.
- Ease of Use: A major advantage of MUST is its simplicity and speed, making it suitable for routine screening in various healthcare settings, even by non-specialist staff. This has led to a documented increase in dietetic referrals following its implementation.
Limitations and Areas for Improvement
- Potentially Underestimating Risk: Some research suggests that MUST may underestimate malnutrition risk in certain patient groups, especially compared to more comprehensive tools like the Patient-Generated Subjective Global Assessment Short Form (PG-SGA SF). The PG-SGA SF includes additional factors like symptoms affecting intake, which MUST does not. Consequently, a patient might be classified as low risk by MUST but high risk by PG-SGA SF.
- Lower Sensitivity for Frailty: When used to screen for frailty, a multidimensional syndrome, MUST's sensitivity has been found to be low. This is because MUST primarily focuses on nutritional parameters and does not measure other factors of frailty, such as mobility, cognition, and functional capacity.
- Implementation Challenges: Audits reveal that despite the tool's ease of use, it is often underutilized or incorrectly applied due to a lack of proper staff training. Errors can arise from miscalculating BMI, guessing weight loss, or failing to act on a high score.
MUST vs. Other Malnutrition Screening Tools
Several other tools exist for screening malnutrition risk, each with different features and applications. Comparing MUST to these helps contextualize its effectiveness.
Comparison of Common Nutritional Screening Tools
| Feature | MUST | Mini Nutritional Assessment-Short Form (MNA-SF) | Patient-Generated Subjective Global Assessment (PG-SGA SF) |
|---|---|---|---|
| Target Population | Adults across all settings | Primarily elderly patients | Patients with various conditions (especially oncology) |
| Core Components | BMI, Unplanned weight loss, Acute disease effect | Appetite, weight loss, mobility, stress, neuropsychological issues, BMI | Weight history, food intake, symptoms affecting intake (NIS), activities/functioning |
| Key Strengths | Universal applicability, quick and easy to use, strong predictive validity for mortality | Designed specifically for older adults, can be a better predictor of length of stay | Includes risk factors for future malnutrition, potentially higher predictive power for certain outcomes |
| Potential Weaknesses | May underestimate risk in some populations; lower sensitivity for frailty | May not be as universally applicable as MUST; potential for lower specificity | Requires more patient input, potentially more complex to administer routinely |
| Typical Setting | Hospitals, care homes, primary care | Hospitals, geriatric units | Hospitals, oncology clinics |
Key Factors for Maximizing MUST Effectiveness
To ensure the MUST tool is used effectively, healthcare organizations and professionals must focus on improving its application and integration into care pathways. Simply possessing the tool is not enough; its proper and consistent use is what yields results.
- Comprehensive Staff Training: Due to high staff turnover, particularly in nursing, ongoing and regular training is necessary to ensure staff understand how to calculate scores accurately and interpret the results correctly.
- Standardized Documentation: Clear, standardized protocols for documenting MUST scores and previous weight records are crucial to prevent calculation errors and ensure seamless information flow.
- Multidisciplinary Collaboration: Effective malnutrition management requires a team approach involving doctors, nurses, dietitians, and pharmacists. Communication between these teams ensures that high-risk patients receive timely referrals and appropriate intervention.
- Regular Audits and Review: Performing regular audits of MUST tool usage can identify weaknesses in the screening process and highlight areas for further staff education or procedural changes.
For more detailed information on the MUST tool's development and use, see the British Association for Parenteral and Enteral Nutrition (BAPEN) website.
Conclusion
Overall, the MUST tool is effective as a primary nutritional screening tool in adults, offering a quick, easy-to-use, and well-validated method for identifying malnutrition risk across various care settings. Its strength lies in its simplicity and ability to predict significant clinical outcomes like mortality and extended hospital stays. However, it is not a perfect instrument and has limitations, such as potentially overlooking risk in some chronic conditions or frailty and relying heavily on consistent staff training for accurate application. When used correctly alongside strong clinical judgment and comprehensive care protocols, the MUST tool remains an invaluable and cost-effective component of patient nutritional management. For maximum effectiveness, healthcare providers must focus on consistent and accurate implementation through continuous training and multidisciplinary cooperation.
