The Malnutrition Care Score quality measure is available for reporting in the CMS Inpatient Quality Reporting Program.
Once your existing workflow is well understood by team members, compare the recommended best practices for malnutrition care to your existing workflow. Assessing where there are differences or gaps will identify specific areas to target for improvement. The recommended clinical workflow and related best practices presented in this section are based on clinical guidance documents from professional societies and research results at leading hospitals
Example: Evaluate whether templates used for patient intake include fields for recording results of a nutrition screening. If these documents are separate from the intake EHR workflow, it creates an additional step for nurses and may decrease the likelihood that nutrition screening is captured in the patient record. How could this improvement opportunity be addressed through your initiative?
You do not need to implement improvements for every component of the recommended malnutrition care workflow at once. Once you have implemented one improvement, you can use your learnings to tackle the other components in an organized fashion.
| Birmingham Nutrition Risk (BNR) |
| Malnutrition Screening Tool (MST) |
| Malnutrition Universal Screening Tool (MUST) |
| Mini Nutrition Assessment (MNA) |
| Nutrition Risk Classification (NRC) |
| Nutritional Risk Index (NRI) |
| Nutrition Risk Assessment (NRS-2022) |
| Short Nutrition Assessment Questionnaire (SNAQ) |
Project: Elevating the Importance of Malnutrition Screening on the Surgical Unit
Objective of this Plan-Do-Study-Act cycle: Test an intervention to improve rates of completion of malnutrition screening using a validated tool for all admitted adult patients.
Questions: What is the biggest reason that malnutrition screening isn’t completed within 24 hours of admission?
Predictions: Educating the nursing staff on the importance of malnutrition screening will improve the rates of completion.
Plan for change: In the baseline data collection and workflow assessment phase, the project team learned that the nurses on the surgical unit did not realize that completing the malnutrition screening was a required component of the admissions process. Further, the project team member from that unit reported that staff members were not aware that completion of the screening was the trigger in the EHR to automatically consult a dietician for a full nutrition assessment. This project will test the success of a nursing unit-based in-service educating the nursing teams on the importance of completing the malnutrition screening in the EHR upon admission to a unit.
Carry out the change: Develop education & training materials and train each nursing unit educator on the materials.
Complete analysis of data
Verify predictions
Identify actions
Patient Population
Surgery, geriatric, oncology, renal.
Nutrition Assessment Parameters
Includes medical history (weight, intake, GI symptoms, functional capacity) and physical examination.
Criteria for Risk of Malnutrition
Categorizes patients as:
More Info
Subjective Global Assessment (SGA)
Patient Population
Oncology, renal, stroke.
Nutrition Assessment Parameters
Includes medical history (weight, intake, GI symptoms, functional capacity) and physical examination.
Criteria for Risk of Malnutrition
Categorizes patients as:
Also provides a numerical score for triaging. Global categories assessed as per SGA.
More Info
Patient Generated Subjective Global Assessment (PG-SGA)
Patient Population
Adult, elderly, pediatric.
Nutrition Assessment Parameters
Criteria for Risk of Malnutrition
Used for comprehensive assessment especially for micronutrients as the SGA does not assess micronutrients. Incorporate the assessment of fat and muscle loss.
More Info
Project: Increase efficiency of the RDN workflow.
Objective of this PDSA cycle: Analysis of assessment completion data showed that some patients with short lengths of stay were being discharged prior to the completion of the nutrition assessment. The objective of this cycle is to provide RDNs with better information on the patients needing a nutrition assessment so that they can prioritize which patients to see first to ensure all patients needing an assessment receive one prior to discharge.
Questions: 1. Does providing RDNs with better, more timely information about the patients who need an assessment improve the efficiency of their workflow? 2. What are the key data points needed for RDNs to triage and assess?
Predictions: Creating a report identifying key patient data that RDNs can run at the beginning of their shift will result in fewer patients discharged prior to the completion of a nutrition assessment.
Plan for change: Who, what, when, where
Collaborate with representatives from the RDN team and the hospital IT team to design the report and process.
Plan for data collection: Who, what, when, where
Carry out the change:
Complete analysis of data
Identify actions
Providers should select appropriate diagnosis codes to document a malnutrition-related diagnosis in patients’ medical records or in the EHR. The table below provides a list of codes providers can use to indicate a patient’s malnutrition status. However, this is not an exhaustive list and users should verify most recent diagnosis codes from available sources. To determine which codes will also satisfy requirements for the Malnutrition Care Score eCQM, see the Academy of Nutrition and Dietetics’s MCS resource webpage.
| 238107002 | Deficiency of macronutrients (disorder) |
| 272588001 | Malnutrition (calorie) |
| 190606006 | Moderate protein energy malnutrition (disorder) |
| 65404009 | Undernutrition – Malnutrition |
| 70241007 | Nutritional deficiency disorder (disorder) |
| 238111008 | Deficiency of micronutrients (disorder) |
| E43 | Unspecified severe protein-calorie malnutrition |
| E44.0 | Moderate protein-calorie malnutrition |
| E46 | Unspecified protein-calorie malnutrition |
| R64 | Cachexia |
Project: Ensure all patients with malnutrition have accurate diagnoses
Objective of this PDSA cycle: Test whether a new process using an EHR communication feature will result in higher rates of malnourished patients receiving a formal malnutrition medical diagnosis.
Question: Will improving communication between care team members result in more consistent documentation of a malnutrition diagnosis for malnourished patients?
Predictions: All patients identified as malnourished will receive a malnutrition diagnosis
Plan for change: Who, what, when, where
The project team will education dieticians on the process change.
Plan for data collection: Who, what, when, where
Carry out the change: Collect data and begin analysis
Complete analysis of data
Verify predictions
Identify actions
The components below should be included in any malnutrition care plan developed by the dietitian. Users may print the table below to serve as a malnutrition care plan template or use the content to develop their own malnutrition care plans.
| Date and time stamp |
| Prioritization and duration based on symptoms and severity |
| Clearly established goals developed in consultation with the patient and/or caregiver |
| Goals and interventions that consider a patient’s individualized recommended dietary intake |
The prescribed treatment/intervention, which may include:
|
| Identification of members of the care team to implement the care plan (e.g., occupational therapy to educate patient on self-feeding tactics) |
| Timeline for patient follow-up, including recommendations for the attending physician regarding post-discharge planning |
*List of recommended malnutrition care plan components provided by the Academy of Nutrition and Dietetics. Recommendations supplemented with findings from Avalere research.
Project: Initiative Hardwiring Malnutrition Care Plans for Implementation
Objective of this PDSA cycle: Test the impact of a change in the EHR configuration to ensure that the malnutrition care plan carries through to orders for patient care.
Questions: Will updating the EHR to remind providers to co-sign RDN orders for nutrition interventions positively impact the rate at which care plans are carried out?
Predictions: Automatically reminding providers to co-sign orders will result in orders flowing through to the task lists and care plans for the appropriate care team members, which will increase the rate at which interventions are carried out.
Plan for change: Who, what, when, where
In conversations with care team members, it was determined that nutrition interventions, though documented in the RDN notes, did not always flow over to the nursing, occupational therapy, or dietary team’s task lists. This change will provide a prompt in the EHR for the attending physician/provider team to co-sign orders from the RDN so that those orders will flow onto those team’s tasks lists.
Plan for data collection: Who, what, when, where
Carry out the change: Collect data and begin analysis
Complete analysis of data
Verify predictions
Identify actions
Project: Improving Malnutrition Handoffs at Transitions in Care
Objective of this PDSA cycle: Test the inclusion of malnutrition-related components in the discharge planning for all patients diagnosed as malnourished
Questions: Will all patients with a malnutrition diagnosis have malnutrition-related recommendations and orders included in their discharge plan?
Predictions: All patients with a malnutrition diagnosis will have malnutrition components included in their discharge plan
Plan for change: Who, what, when, where
Plan for data collection: Who, what, when, where
Carry out the change: Collect data and begin analysis
Complete analysis of data
Verify predictions
Identify actions
For more information, please refer to the clinical guidance documents listed below. They contain the relevant information on the most recent standards of nutrition care:
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