HL7 Domain Analysis Model for Nutrition Care

The HL7 Domain Analysis Model: Nutrition Care, Release 3 Standard (December 2022-2024) outlines a comprehensive framework for implementing and standardizing nutrition care processes in healthcare environments. Developed by Health Level Seven International (HL7) in collaboration with the Academy of Nutrition and Dietetics, this document focuses on enhancing the integration and interoperability of nutrition-related data within Electronic Health Records (EHRs) and other health information systems.

The model builds on the Nutrition Care Process (NCP), which standardizes the steps of Nutrition Assessment, Diagnosis, Intervention, and Monitoring/Evaluation to ensure consistent and high-quality nutrition care. This framework emphasizes patient-centered care, quality improvement, and the effective communication of nutrition orders and assessments across multidisciplinary healthcare teams.

The HL7 Domain Analysis Model elaborates on the specific workflows and data elements necessary for effective documentation, providing practical use cases such as diet ordering, food allergy management, and tailored nutrition interventions.

Logical Model for Nutrition Care Records

This page adapts the HL7 Domain Analysis Model (DAM) for Nutrition Care, and provides a Logical Model for the Nutrition Care Process (NCP), which serves as a technology-agnostic common reference , designed to be adaptable to specific implementation requirements while highlighting where terminology bindings to SNOMED CT can be applied. By outlining essential entities, such as Patient , Practitioner/Dietitian , Assessment , Diagnosis , Intervention , and Monitoring/Evaluation , and their relationships, this model aims to support consistent and organized documentation across the entire care process, provided it is implemented correctly.

The Nutrition Care Records Model outlines a comprehensive framework for managing nutrition care, highlighting key entities' roles and interactions to support patient-centered outcomes.

• Patient is the central entity, representing the individual who receives nutrition care. The patient is linked to various elements of the care process, including nutrition assessments, diet orders, and monitoring and evaluation activities.

• Dietitian plays a pivotal role throughout the care process. Dietitians perform nutrition assessments, establish nutrition diagnoses, implement appropriate interventions, develop care plans, and monitor the patient’s progress. They ensure that the nutrition care provided aligns with evidence-based practices and patient-specific needs.

  • The DAM utilizes the term “Practitioner” per HL7. This aligns with and helps to also be more inclusive of the NDTR (Nutrition Dietetic Technician, Registered) role in the United States.

The provided ER (Entity-Relationship) diagram for Nutrition Care Records illustrates the relationships between key entities involved in nutrition care and how they interact at the data storage level. It is important to note that this diagram does not represent a clinical workflow. Instead, it demonstrates how data collected during a clinical workflow can be structured and associated within a database. This model has been developed as part of this guide to highlight the key entities relevant to nutrition care and to indicate where the SNOMED CT NCPT reference set can be utilized.

These following bindings ensure that the FHIR resources effectively capture nutrition diagnosis information using standardized SNOMED CT terminology, promoting interoperability and accurate data exchange across healthcare systems.

A well-defined information model and appropriate terminology bindings are essential to accurately document the NCP within healthcare systems using SNOMED CT. The information model provides a structured framework for organizing data related to nutrition assessment, diagnosis, intervention, and monitoring. Terminology bindings link this data to standardized SNOMED CT concepts, promoting consistent communication and interoperability across healthcare settings. This approach ensures clear and precise documentation, facilitates data sharing, and supports high-quality, patient-centered nutrition care.

To clarify how the NCP can be implemented in clinical information systems and supported by SNOMED CT, a Logical Model for the NCP is presented. This model serves as a technology-agnostic common reference information model, adaptable to specific implementation needs, and highlights points where terminology bindings to SNOMED CT can be effectively applied.

By establishing these models and bindings, healthcare organizations can achieve precise data recording and effective data use.

In recent years, the integration of HL7® FHIR® with SNOMED CT has gained popularity. Given its wide acceptance and capabilities, HL7 FHIR is the preferred information model in this implementation guide. The following sections provide recommended strategies for integrating SNOMED CT with HL7 FHIR to document the NCP within electronic health records (EHRs).

Other information modeling solutions, such as openEHR, may provide useful archetypes. However, they are not included in this version of the guide due to the lack of widely recognized international models in this area. As progress continues, future updates to the guide may include these frameworks.

Nutrition Intervention Data and Associated FHIR Resources

Nutrition Intervention involves planning and implementing actions to address the nutrition diagnosis.

Several FHIR resources can be used to document these interventions:

• NutritionOrder Resource : Documents detailed nutrition care plans and orders.

• NutritionProduct Resource: Documents foods, fluids and oral nutrition supplements provided to the patient.

• Procedure Resource : Records specific nutrition-related procedures and interventions.

• CarePlan Resource : Provides a comprehensive plan of care that includes nutrition interventions.

This example demonstrates how the NutritionOrder resource can be used to document and manage dietary requirements, restrictions, and preferences for a patient. It illustrates a comprehensive cardiac diet order for an inpatient, including specific instructions, nutrient modifications, and food exclusions.

Key features highlighted in this example:

• Diet Type: Includes a low sodium diet and fluid-restricted diet to address cardiac health needs.

• Nutrient Specifications: Details on limiting sodium intake to 2 grams per day and fluids to 1500 milliliters per day.

• Allergies and Exclusions: Accounts for patient-specific allergies (e.g., cashew nuts) and excludes related food items.

• Personalization:

This example is based on the official and showcases how NutritionOrder supports structured, interoperable dietary management in healthcare.

For more examples and detailed use cases, refer to the and .

Nutrition Monitoring and Evaluation involve tracking the patient's progress and the outcomes of nutrition interventions.

Nutrition Monitoring and Evaluation

Nutrition Monitoring and Evaluation involve tracking the patient's progress and the outcomes of nutrition interventions.

Nutrition Monitoring and Evaluation Data and Associated FHIR Resources

FHIR resources used for this purpose include:

• Observation Resource : Continues to be crucial for ongoing measurements and assessments.

• NutritionIntake Resource : Details about the consumption of foods (i.e., solid and/or liquid), supplements, enteral nutrition, and infant formula.

• NutritionProduct Resource: Identification of a food (i.e., solid and/or liquid) product provided to patients.

• Goal Resource : Tracks specific nutrition-related goals and their outcomes.

• Condition Resource : Updated to reflect changes in the patient’s condition as a result of interventions.

• CarePlan Resource : Monitors and evaluates the overall care plan, adjusting interventions as needed.

This section summarizes the key entities and attributes defined in the Logical Model and indicates where SNOMED CT concepts can be used to represent values.

Patient

Resources and Terminology Bindings

The Nutrition Care Process Terminology (NCPT) can be effectively represented using HL7 FHIR (Health Level 7 Fast Healthcare Interoperability Resources), a standardized framework for healthcare data exchange that ensures consistent and interoperable documentation across various healthcare systems. Notably, standardized documentation of nutrition care using SNOMED CT is a crucial preliminary step, as structured data is more readily exchanged with the HL7 FHIR standard.

The key components of the NCPT; Assessment, Diagnosis, Intervention, and Monitoring and Evaluation map to specific FHIR resources as follows:

• Nutrition Assessment : The Observation, NutritionOrder, NutritionProduct, NutritionIntake, Condition, and ClinicalImpression resources capture dietary habits, anthropometric measurements, and test results, offering a comprehensive view of the patient’s nutritional status.

• Nutrition Diagnosis: The Condition resource represents nutrition diagnoses, including specific problems, etiologies, and related signs and symptoms.

• Nutrition Intervention: The NutritionOrder , NutritionProduct , Procedure , and CarePlan resources document detailed nutrition care plans, specific interventions, and strategies for managing nutrition-related issues.

• Nutrition Monitoring and Evaluation: The Observation , Goal , Condition , and CarePlan resources are used to track ongoing measurements, monitor progress toward goals, update condition statuses, and review and adjust care plans as needed.

In the context of HL7 FHIR and SNOMED CT, terminology binding defines how clinical data elements are represented within FHIR resources. Each data element in a FHIR resource is linked to a specific value set, which dictates the permissible SNOMED CT codes or concepts for that element.

For example, when recording a patient’s condition in a FHIR resource, the “code” field is bound to a specific SNOMED CT code that accurately represents the condition. This standardized approach ensures that healthcare providers and systems use consistent terminology to describe clinical information across different platforms and contexts.

By adhering to these value sets, FHIR enables precise data exchange and a shared understanding of clinical data elements, enhancing interoperability, supporting efficient healthcare delivery, and contributing to improved patient outcomes.

The following pages will provide detailed recommendations for terminology bindings between relevant FHIR resources and SNOMED CT value sets, specifically as they apply to representing the Nutrition Care Process Terminology (NCPT). Each section will outline the application of specific FHIR resources and bindings to support different NCPT components.

HL7 FHIR is a modern standard designed to facilitate the exchange of healthcare information electronically. The standard defines resources, i.e. data formats, that can be used to represent data elements in a systematic way across the healthcare continuum.

• Consistency : With standardized resources and robust semantics, FHIR ensures uniformity in healthcare data representation. This consistency supports accurate data exchange and enables healthcare providers to make informed decisions based on reliable information, ultimately enhancing patient care quality.

• Modularity : FHIR’s flexible architecture allows its resources to be used independently or in combination to meet specific healthcare needs. This modular approach supports adaptability across diverse healthcare contexts, enabling tailored solutions without overhauling entire systems.

• Interoperability : FHIR facilitates seamless data exchange between different healthcare systems and applications, enhancing communication and collaboration among healthcare providers. By standardizing data formats and protocols such as RESTful APIs and JSON/XML, FHIR promotes interoperability, improving patient care coordination and information sharing.

HL7 FHIR plays a crucial role in linking healthcare data with standard terminologies, including SNOMED CT. By integrating FHIR with terminologies like SNOMED CT, a more precise and standardized documentation and communication of clinical information can be achieved. This linkage enhances interoperability by enabling seamless exchange of structured clinical data, supporting accurate clinical decision-making, and promoting continuity of care for patients across various healthcare settings.

Together, FHIR and SNOMED CT facilitate a unified approach to healthcare information management, benefiting both vendors, healthcare providers and patients.

Nutrition Assessment involves collecting and analyzing data to identify nutrition-related issues.

Nutrition Assessment Data and Associated FHIR Resources

Several FHIR resources can represent different aspects of the assessment:

Nutrition Diagnosis identifies specific nutrition problems that can be addressed through interventions.

Nutrition Diagnosis Data and Associated FHIR Resources

The FHIR Condition resource is primarily used to represent nutrition diagnoses. It captures the nutrition diagnosis using structured data.

• Problem : Represented by the condition code, often using SNOMED CT codes.

• Etiology : Captured in the details or extensions of the Condition resource.

• Signs/Symptoms : Documented as evidence within the Condition resource, referencing relevant Observation resources.

Clinical scenario

This scenario involves a 55-year-old patient with a history of Type 2 diabetes mellitus, managed with medications and lifestyle adjustments. Recent symptoms include unintended weight loss, weakness, and swelling in the lower limbs. Clinical evaluation reveals signs of weight loss and muscle wasting, indicating possible malnutrition exacerbated by chronic diabetes management.

Using FHIR resources, healthcare providers document these findings to support a structured approach to diagnosis and treatment planning.

• The Condition Resource represents the nutrition diagnosis (Malnutrition) using a SNOMED CT code.

  • The evidence section of the Condition resource includes:

    • Etiology : Physiologic–Metabolic; Underlying chronic illness (Type 2 diabetes mellitus) as another Condition resource.

This resource represents the diagnosis of the nutritional disorder (malnutrition).

This resource represents the underlying chronic condition contributing to the nutritional disorder.

Here is a JSON representation of a condition resource detailing a chronic illness, Diabetes mellitus type 2:

This resource uses standard coding systems to describe the clinical and verification statuses, as well as the specific type of diabetes being documented.

This is referenced in the evidence section of the Condition resource, and referencing a condition or observation resource.

This resource documents the presence of unintentional weight loss.

Details:

• Resource Type: Observation

• ID: unintentional-weight-loss

• Status: Final

• Category: Clinical

The following JSON represents an HL7 FHIR Observation for the symptom "Muscle Wasting":

This resource indicates a clinical observation related to the presence of muscle atrophy (disorder) for a patient. The valueBoolean attribute confirms the observation is true.

Linking the Resources

• The Condition Resource for Nutritional Disorder references:

• The Condition Resource for Type 2 Diabetes Mellitus in its evidence.detail array to represent the etiology.

• The Observation Resources for unintentional weight loss and muscle atrophy to represent signs/symptoms.

• All resources reference the same patient (Patient/example) for proper linkage and context.

Adapting Clinical Guidelines to Local Contexts

Implementing the NCPT reference set and following the recommendations in this guide do not require adherence to any specific clinical guidelines. Instead, this guide is designed to support flexible application, allowing nutrition assessments, interventions, and care plans to be tailored to the diverse practices, standards, and needs found across healthcare settings. Clinical guidelines and care protocols are inherently context-dependent, and practices may vary across different organizations, regions, and countries. As such, this guide does not prescribe or recommend any particular clinical guidelines, recognizing that suitable approaches may differ based on local and organizational requirements.

Role of Clinical Guidelines in Supporting Optimal Care

Clinical guidelines , also known as “clinical practice guidelines,” are “statements that provide recommendations intended to optimize patient care, informed by a systematic review of evidence and an evaluation of the benefits and risks of alternative care options.” Developed and implemented according to internationally recognized standards, clinical guidelines play an important role in:

• Reducing unwarranted practice variation by providing evidence-based recommendations

• Facilitating the integration of research into practice by guiding clinicians in evidence-based decision-making

• Enhancing healthcare quality and safety by supporting consistent standards of care

Clinical guidelines serve multiple purposes, including helping healthcare professionals deliver optimal care, establishing standards for evaluating clinical practices, and supporting patient education and informed decision-making. They can influence care outcomes positively when effectively disseminated and integrated into clinical processes.

In the delivery of nutrition and dietetics care specifically, standardized terminology facilitates the ongoing application of evidence-based practice guidelines in practice. Aggregated structured electronic health care record data is the backbone for tracking outcomes on various levels: at the service, the organization, the regional, national, and international levels. Outcomes research helps justify nutrition and dietetics position statements, related professional standards of practice, and decisions (eg funding, staffing, reimbursement or political and/or financial level decision-making depending on the country and healthcare environment). The (The Academy of Nutrition and Dietetics Health Informatics Infrastructure) platform (log in required) contains a digital NCP template that dietitians use to document nutrition care care data which is then aggregated and analyzed for outcomes tracking. Translational research helps validate and or further fine tune evidence-based practice guidelines. Expected care plans (ECPs) are bundles of NCPT terms that have been identified as representing the application of a specific recommendation in a guideline. Several professional and scientific organizations internationally are invested in generating timely nutrition and dietetics evidence-based practice guidelines that progress scientific clinical knowledge and care delivery.

Completing the Evidence-Based Practice Cycle: Linking Research with Practice

This guide supports the adoption and implementation of the NCPT reference set by providing general recommendations that can be adapted to a variety of settings. However, it does not establish specific clinical guidelines, nor does it dictate how the NCPT should be integrated within particular clinical protocols. Organizations are encouraged to interpret and apply the NCPT reference set in ways that are responsive to their unique operational contexts, existing guidelines, and local practices.

By emphasizing flexibility, this guide aims to empower healthcare organizations to utilize the NCPT reference set effectively, in alignment with their own best practices and patient care standards.