Overview

The National Institutes of Health (NIH) is a federally sponsored biomedical research program in the United States. The NIH is made up of 27 separate institutes and centers. The Intramural Research Program's (IRP) programs are embedded in 24 of the NIH Institutes. One of those institutes, the National Library of Medicine (NLM) is the world's largest biomedical library and the SNOMED CT National Release Center for the United States. The NLM curates an extensive collection of medical knowledge in various formats which is used by millions of people around the world. Across the IRP, some of their Principal Investigators (PIs) use SNOMED CT in their research. A selection of the Intramural Research Program's initiatives which relate to SNOMED CT and CDS, are briefly described below.

Value Set Authority Center

The Value Set Authority Center (VSAC), managed by the NLM, is a service designed to maintain and distribute the value sets defined in (eCQMs). Each VSAC value set consists of codes and terms from clinical vocabularies such as SNOMED CT, RxNorm, LOINC and ICD-10-CM . Value sets derived from SNOMED CT are used to support the calculation of data quality measures which in turn provide feedback to clinicians about the quality of care. Note that VSAC is a project administered by NLM, but the actual data quality computations are done at individual healthcare sites.

is an resource which accepts requests for information on diagnoses (problem codes), medications, and lab tests, and returns related information from . The API is available as a web or as a web , which can be integrated with an EHR. MedlinePlus accepts SNOMED CT problem codes as input and provides CDS in the form of targeted information prescription. The example below shows how the Medline Plus Connect request and response are structured. Note that the response includes the title and link of the matched topic and may include synonyms, attribution acknowledgements, and related links.

The requests conform to the . A screen shot of the application's response to a request for information on | Asthma| is provided below:

Some NLM researchers also participate in external projects which utilize SNOMED CT. One such project is . This collaborative uses SNOMED CT to integrate diagnostic data. This semantic data integration is then used by research studies which in some cases serves as input into the authoring of CDS knowledge artifacts.

One of the programs related to OHDSI is (IMEDS), which includes a number of projects led by NIH researchers, such as:

• NIH Investigators

• Ferdinand Dhombres (NIH)

EBMeDS

The Evidence-Based Medicine electronic Decision Support system (EBMeDS) was developed by Duodecim. It is a platform-independent service, which can be integrated with any EHR that uses structured patient data. EBMeDS contains over 40,000 decision support rules which can be used to generate reminders, therapeutic suggestions, order sets and diagnosis-specific links to guideline sets and other online resources. EBMeDS can also be used to automatically populate calculators and forms with patient-specific data, and to generate summary views and dashboards. In addition to real-time use, the EBMeDS decision support rules can also be run as batch scripts on patient populations to generate reports that measure quality and analyze care-gaps. The rules of EBMeDS are based on the data in the EBMG collection, with several 3rd party resources also used for evidence collection.

Using SNOMED CT

EBMeDS receives encoded patient data from EHRs. The coded data pertains to several _ data groups _ including diagnoses, medications, vaccinations, investigation results, surgical procedures, and risk factors (such as smoking). Although multiple coding systems are supported, only SNOMED CT and the Read code system are accepted for all data groups. Within EBMeDS, all codes are mapped to internal aliases. For example, for the concept _ serum or plasma creatinine _ includes codes from 10 different coding systems. Duodecim is expecting to derive additional benefits from using SNOMED CT when more EHRs are able to provide SNOMED CT encoded records as outputs.

Deployments

At present, EBMeDS is used mainly in Finland. Duodecim is planning to offer a cloud-based centralized EBMeDS service in the near future, but currently the application is integrated into the local EHR environments. Belgium has a national license for EBMeDS as part of the EBMPracticeNet implementation in Belgium. Several pilots and scientific studies are being performed in Italy, Denmark, Estonia, the United States and the UK.

This section describes a range of organizations that have used SNOMED CT for clinical decision support. The organizations that have contributed to this review include:

• EBMPracticeNet

• Kaiser Permanente

Overview

The Department of Biomedical Informatics at the University of Utah is an internationally recognized leader in both research and education in the field of medical informatics. The university has been a major contributor to the development of health information standards and open source initiatives, many of which have been leveraged in their own solutions, including their clinical decision support systems.

Standards, Architectures, Techniques

As a major contributor to the development of the OpenCDS collaborative, the University of Utah has been able use the architecture from OpenCDS to provide a service-based approach to their CDSS and clinical quality measurement efforts. As part of this effort, they have made use of HL7 International’s Decision Support Service (DSS). The University also played a key role in the development of OpenInfobutton, an opensource web service and reference implementation of HL7's infobutton standard. Infobuttons are context-sensitive links, which can be embedded in EHR systems as buttons or tabs. OpenInfobutton was funded by the US Veterans Health Administration (VHA) and developed by researchers at the VHA, Duke University, and the University of Utah.

Using SNOMED CT

SNOMED CT value sets are used to map to clinical concepts referenced in the University's CDS rules. SNOMED CT value sets are also used to configure patient problem lists in OpenInfobutton. Since the Infobutton standard uses SNOMED CT for problem lists, SNOMED CT concept identifiers are embedded in the requests and responses between the EHR and OpenInfobutton architecture, as shown in the figure below.

The University has benefited from using a standardized clinical reference terminology which can be used across clinical domains. By using SNOMED CT in OpenInfobutton, the University has improved the interoperability between EHR systems and knowledge resources, by providing more efficient access to the indexed knowledge content.

EBMPracticeNet is a consortium of Belgian organizations whose mission is to develop a national online knowledge base of clinical practice guidelines based on evidence-based medicine (EBM). The project is funded by RIZIV-INAMI, the Belgian national health insurer. The consortium acknowledges that clinical decision support systems play a vital role in the implementation of evidence-based medicine. EBMPracticeNet is very active in the development, evaluation, and distribution of evidence based CDS knowledge, mainly for use in primary care settings. Their users include family physicians, nurses, physical therapists, occupational therapists, pharmacists, speech therapists, patients, and eventually dentists. Clinicians will access the system through their EHRs with an (called "EvidenceLinker") which links coded diagnoses to relevant guidelines on the platform. The consortium is in the process of conducting an analysis to compare several terminologies to gauge which may be best suited for using encoded health records from a primary care setting with CDS services. An early version of the analysis report has identified SNOMED CT as the terminology with the most comprehensive coverage and best suited to unambiguously describe the concept.

The EBMPracticeNet consortium hosts a platform of clinical practice guidelines. Seventy five of these are from Belgium, and an additional 1000 international guidelines have been developed by , the Finnish developers of EBM guidelines. The knowledge resources from Duodecim have been translated from its language of origin into both Dutch and French, and localized for Belgium using a variant of the framework. Currently all guidelines are accessible through the EHR using the EvidenceLinker, which suggests relevant guidelines based on the coded diagnosis. The EvidenceLinker currently uses ICPC-2 codes for this linkage. Additionally, EBMPracticeNet uses Duodecim’s as the engine in their clinical decision support system, which is currently in the pilot phase. A depiction of the architecture is shown below.

This section describes a number of commercial products that use SNOMED CT to support their clinical decision support systems. The vendors that have contributed to this review include:

• Duodecim

• First Databank

Overview

Kaiser Permanente (KP) has a long history with SNOMED CT, dating back to the 1990s when they collaborated with the College of American Pathologists (CAP) on the development of SNOMED RT (Reference Terminology). KP was also one of the first healthcare organizations to implement a SNOMED CT enabled health record (EHR). KP HealthConnect (KPHC), Kaiser Permanente's enterprise electronic medical record, was developed by Epic and hosts the records of over 10 million patients. KPHC uses a set of clinician and patient friendly terminologies, collectively known as the Convergent Medical Terminology (CMT), with SNOMED CT as its core reference terminology. KP has made their contributions to SNOMED CT available to the broader community by donating CMT to SNOMED International and the US National Library of Medicine (NLM).

KP HealthConnect

KP loads SNOMED CT in its native RF2 format into the HealthConnect EMR system. The EMR "Chart Search" functionality can execute a global search for diagnoses, procedures, and laboratory results against a given patient. All patient encounters that match the resulting criteria are displayed to the clinician. This provides a global summary of all encounters which relate to a given condition. This function takes advantage of the hierarchical structure of SNOMED CT. KP also maps the "clinician friendly" terms used in the EMR to SNOMED CT to meet and Health Information Exchange reporting requirements.

Value sets are an integral part of terminology management services at Kaiser Permanente. Value set identification, development, deployment, and maintenance is performed using a custom tool developed within KP. This "Subset Management" tool utilizes the native ontological structure of SNOMED CT and adds KPHC local terminology as additional artifacts within the terminology model. The formal concept definitions of SNOMED CT are used to define and generate the required value sets. The "CMT Query" tool also uses the hierarchy of SNOMED CT and description logic reasoning to identify value sets of clinician friendly terms used in patient clinical encounters. These value sets are also used within KPHC to drive business intelligence (including CDS), support workflow, and enable data reporting and analytics. As shown in the screen shot below, the queries used to define value sets leverage SNOMED CT defining relationships, such as those using the attributes 363698007 | Finding site| and 116676008 | Associated morphology|.

KP uses the native functions provided by Epic to define and maintain CDS rules. This accounts for all criteria used in the rules, such as inclusions and exclusions. A screen shot of the tool used to define these criteria is shown below.

Clinical decision support at Kaiser Permanente leverages the value sets developed by their CMT team. For example, a CDS rule which uses value sets associated with 195967001 | Asthma| and 33252009 | beta-blocker| drugs is used to trigger an alert when specific conditions are met in the patient encounter, diagnosis, or problem list. The diagram below shows the associated value sets used in this rule.

As discussed in this guide, SNOMED CT is increasingly being used in clinical decision support (CDS) systems to support healthcare providers in making well informed clinical decisions.

This appendix presents two sets of case studies, which demonstrate the use (or planned use) of SNOMED CT in clinical decision support systems.

• Organizational Case Studies describes a range of organizations that use SNOMED CT for clinical decision support;

• Vendor Case Studies describes a number of commercial products that use SNOMED CT to enable clinical decision support.

Overview

First DataBank (FDB) were in the first wave of suppliers to recognize the potential of SNOMED CT and begin to integrate support for SNOMED CT into their existing clinical decision support solutions. Their primary use of SNOMED CT in the patient's electronic health record (EHR) is to detect safety issues arising from certain combinations of medications, diagnoses and drug adverse reaction histories. In 2006 FDB introduced support for products and packs encoded using the NHS SNOMED CT UK Drug Extension. In the following year FDB launched new modules within the Multilex drug knowledge base supporting Drug-Condition Checking and Drug Sensitivity (Allergy) checking for the SNOMED CT EHR.

System vendors implementing Multilex decision support within SNOMED CT-enabled medical record applications include CSC (Lorenzo system), EPIC and JAC in secondary care, and CSE Servelec (RiO system) in community/mental health. Currently only pre-coordinated expressions are supported by the live Multilex SNOMED CT based decision support solutions.

Drug-Condition Contraindication Checks

The contraindications module alerts the clinician when a medication proposed to treat a disorder is incompatible with another of the patient's disorders or clinical states. For example a beta blocker like propranolol might be prescribed to treat someone with high blood pressure. However if that patient also has asthma, their asthma might significantly worsen or a dangerous acute attack might be produced by the drug.

Thousands of such drug-condition contraindications exist and nearly all medications have at least one. Without point of care decision support, the clinician must rely on memory or search reference sources for each drug prescribed. Also there is a risk that a contraindicating condition may be in the record but unknown to the prescribing clinician.

In a SNOMED CT enabled EHR, both the drugs (e.g. 318353009 | propranolol hydrochloride 40mg tablet| ) and the conditions (e.g. 370219009 | moderate asthma| ) are encoded.

Internally FDB maintain their own local ontology representing only those conditions relevant to prescribing decision support (e.g. asthma, gastric ulcer, heart disease, pregnancy). The items in this ontology are linked to SNOMED CT codes as required to support this (contraindication checking) use case. These SNOMED CT links range from the obvious, such as linking 195967001 | asthma| to FDB's 'asthma', to the more subtle, such as linking 447413000 | drainage of amniotic fluid using ultrasound guidance| to FDB's 'pregnancy'.

FDB reviews the relevant SNOMED CT domains (i.e. | Clinical finding|, | Procedure| and | Situation with explicit context| ) for concepts applicable to drug-condition checking. The FDB linking tool uses the SNOMED CT | is a| hierarchy and a SNOMED CT derived transitive closure table to locate and suggest links from the FDB ontology to SNOMED CT concepts. Other SNOMED CT relationships also help find related concepts via the browser but discovery is mainly by clinical knowledge combined with description based searches assisted by the rich synonym content of SNOMED CT.

The sensitivities module alerts the clinician when a proposed drug for a patient is either stated in that patient's record to have caused a previous adverse reaction or when an adverse reaction has occurred to a similar drug and thus likely to elicit a similar adverse response. For example, a patient allergic to penicillin is likely to react to most other drugs containing a β-lactam ring in their molecular structures.

In a similar way to how FDB links SNOMED CT conditions to its own internal ontology, SNOMED CT concepts which suggest allergy or previous adverse reactions to a medication are also linked to an internal FDB ontology for representing medication ingredients. This ontology is designed specifically to support allergic and adverse reaction cross-reactivity.

Overview

The Pharmacy Health Information Technology Collaborative (PHIT Collaborative) is a body of pharmaceutical organizations which operates in the United States and was formed in 2010. As the name suggests, they focus on the pharmacists providing patient care services and assess how information technology can be used to support their processes and workflows. Health information technology standards and clinical terminology are used to promote interoperability and to support their strategy of collecting, documenting, and preparing information for sharing with other service providers. Much of the work the PHIT Collaborative does is guided by the Centers for Medicare & Medicaid Services (CMS) medication therapy management regulations and Meaningful Use (MU) reporting requirements.

Use of SNOMED CT

The PHIT collaborative has been working towards the standardization of clinical pharmacy documentation which includes the use of SNOMED CT to record events such as a 404684003 | Clinical finding|, 71388002 | Procedure|, or 243796009 | Situation with explicit context|. This has resulted in a number of SNOMED CT value sets being published in the National Library of Medicine (NLM) Value Set Authority Center (VSAC), such as the one shown in the figure below.

A major benefit of using SNOMED CT in clinical pharmacy documentation is that SNOMED CT supports the calculation of (eCQMs). This ensures that pharmacists are included in the overall measurement of quality in the US health care system and more recently, outcomes-based payment models.

In addition to improved interoperability and calculation of eCQMs, the standardization of clinical pharmacy documentation can help to enable decision support and the Pharmacy HIT Collaborative is looking at some potential scenarios. One of the central components of pharmacy documentation includes identification of drug therapy problems. Once a medication problem has been identified, a pharmacist can intervene to optimize a patient medication regimen. But in some US jurisdictions, the direction to adjust a medication must come from the prescribing physician. Clinical decision support could be a huge benefit in these cases by acting on the recommendations of a pharmacist. More specifically, CDS could be used to help identify drug therapy issues, to propose actions, and to notify prescribers.

Using clinical decision support in the documentation of medication adverse reactions, allergies, intolerances and interactions could also benefit pharmacists and their patients. For example, SNOMED CT concepts subsumed by 62014003 | Adverse reaction caused by drug| and 272141005 | Severities| could be used to document adverse reactions . When prescribers are managing medication regimens, improved clinical decision support alerts could provide a mechanism to outline the risk of prescribing a medication based on past experience.

Medication outcomes could also be documented using SNOMED CT. For example, SNOMED CT could be used to document the outcomes of a patient who is involved in clinical trials for a new medication. Lack of an adverse reaction may have multiple explanations, including that the patient may not be adherent to the medication due to cost or the inconvenience of frequent administrations. Documenting the reason why a therapy failed could provide useful information for future prescribing events.

Sundhedsplatformen which translates to the health platform, is a jurisdictional electronic health record (EHR) in Denmark with decision support capabilities. The system, provided by Epic, operates in the Capital and Sealand regions of Denmark, which cover a population of approximately 2.6 million people (almost half of the population of Denmark). The system uses SNOMED CT as the basis for its diagnosis-related decision support services. The first clinical rollout of the system was performed in May 2016. When the rollout is complete at the end of 2017, the system will provide services for up to 45,000 clinical users.

One of the design considerations of this system is to capture and store clinical data as structured content ( as opposed to unstructured or free text). This use of structured health data reduces the need for mapping and creates many opportunities including clinical decision support. In terms of terminology, Denmark’s national classification system, called Sundhedsvæsenets Klassifikations System (SKS) , is based on ICD-10 and a range of other classification systems. Traditionally, SKS has been used for statistical aggregation and for billing purposes. Although not designed for clinical use, SKS was selected as the primary classification system for the Sundhedsplatformen project to maintain the legacy requirements associated with billing and classification. There was therefore a need to represent both procedures and diagnoses within SKS.

Terminology

Practice Fusion’s EHR uses the Health Language Enterprise Terminology Management Platform from Wolters Kluwer to support the management of its terminology content. This terminology platform enables Practice Fusion’s patient health records to be encoded using SNOMED CT, ICD-9, ICD-10 and a range of other code systems. Practice Fusion’s EHR uses a physician friendly library of terms, together with mappings to SNOMED CT, ICD-9 and ICD-10, to support the selection of appropriate clinical concepts at the user interface.

Practice Fusion has chosen to make SNOMED CT codes and descriptions available for viewing in the user interface. As shown in the screen shot below, when recording a diagnosis a provider can examine the mappings between the user interface term, ICD-9, ICD-10 and SNOMED CT. This approach has received positive feedback from their users as it provides an additional layer of validation when selecting a concept to record in the patient’s health record. Since 2014, all diagnoses recorded in Practice Fusion’s EHRs have included the associated SNOMED CT codes.

Practice Fusion includes a feature called Clinical Decision Support (CDS) advisories. When a new encounter is entered, the patient's record is processed against a rule engine with specific criteria to determine whether the patient requires a clinical intervention. If the patient requires an intervention, one or more yellow alerts will appear at the top of the encounter. These alerts can be resolved by following an appropriate sequence of events such as ordering a lab test or completing a screening or assessment.

Practice Fusion creates and maintains value sets which include, SNOMED CT concepts to support criteria for their CDS advisories. SNOMED CT codes recorded in the patient’s record are tested for membership in relevant SNOMED CT value sets, to determine which CDS advisories should be triggered. All diagnosis related value sets and some procedural value sets used by their CDS advisories contain SNOMED CT concepts. In addition, Practice Fusion uses SNOMED CT to define their encounter and attribute value sets.The SNOMED CT value sets used by Practice Fusion’s advisories are mostly defined intensionally using SNOMED CT’s hierarchy and (in some cases) SNOMED CT’s defining relationships. This allows the value sets to be easily updated (by re-executing their intensional definition) when a new version of the terminology is adopted. Practice Fusion has found that SNOMED CT’s polyhierarchy provides a significant advantage when defining these value sets, because similar concepts can easily be grouped together by including all descendants of a common supertype.

SNOMED CT is particularly useful for rare diseases, enabling expression of diagnoses requiring a high degree of specificity and which may not be sufficiently defined in ICD. For example, the screen shot below illustrates a CDS advisory that is triggered when clinical markers considered high-risk for 274864009 | Pompe disease|, are detected in the patient’s health record. Using the hierarchy of SNOMED CT, appropriate value sets were defined that help to identify those patients for which a GAA enzyme assay order should be considered to confirm the presence or absence of the diagnosis.

Examples of other advisories that use SNOMED CT value sets in their criteria include:

• Patient requires screening for clinical depression and follow-up plan

• Patient has poor control of hemoglobin A1C and needs a new lab test

• Patient has diabetes and is due for an eye exam

Practice Fusion has also used SNOMED CT to represent procedures for follow up actions, such as assessments and interventions. CDS advisories are often linked to Clinical Quality Measures (CQM) in the Practice Fusion workflow. When a provider fulfills the requirements associated with a specific CDS advisory, they will get credit for fulfilling the requirements of the associated CQM, such as completing a specific assessment. Using SNOMED CT for these assessments facilitates the capture and storage of the associated treatment plans.

Orion Health

Overview

Orion Health currently has four products which leverage SNOMED CT for Clinical Decision Support. These are:

• Global Drug Model (GDM);

• Orion Health Medicines;

• Orion Health Problem List; and

• Clinical Decision Support (CDS) application.

To allow for multiple customers to be supported worldwide, these products adopt a modular approach to terminology deployment. A customer selects the relevant data loader for their jurisdiction and the experience is customized for their region automatically. When deployed in SNOMED CT member countries, this process involves loading the relevant SNOMED CT National Edition and local medication codes. Drug data is represented using a common model based on SNOMED CT. This enables customers already using SNOMED CT coding to migrate to these products very quickly. Other local medication codes can be translated to the SNOMED CT equivalent representation using integrated mappings. Orion’s Medicines platform provides support for terminologies from the UK, Australia, New Zealand, USA and France, as well as support for other customers with local data sets.

SNOMED CT offers a range of significant benefits to Orion Health’s CDS solutions. SNOMED CT’s relationships and drug class information are used to optimize the drug database during the import process. Orion Health has also developed several algorithms which allow for extremely fast retrieval of medication data, traversal of the medication hierarchy and testing for concept subsumption. These SNOMED CT features are used extensively by the Clinical Decision Support APIs and are therefore a core part of Orion Health’s CDS applications. These products also provide the ability to add new medications that are not predefined in the terminology, such as extemporaneous medications, clinical trial drugs or medications obtained in a different country. New medications can be fully modeled within the GDM concept hierarchy, and assigned a valid SNOMED CT extension identifier using the customer’s assigned namespace.

The Amadeus Clinical Portal as shown in the diagram below provides a single point of access for clinicians to manage patient information. This portal integrates the CDS products mentioned above, including the Medicines and Problem List applications. All Orion Health’s CDS applications expose their data using FHIR’s RESTful APIs. The use of SNOMED CT in these products also facilitates easier translation to standard messaging formats, such as HL7 CDA or other message structures mandated by local jurisdictions.

The Global Drug Model (GDM) enables Orion’s software to be deployed worldwide. This application standardizes and normalizes data sets from many different countries into a single data model. Customers upload their local SNOMED CT edition into GDM via an application that runs inside the Orion Health Clinical Portal. GDM processes the data and then publishes it using HL7 FHIR’s RESTful APIs. The processing performed by GDM makes heavy use of the SNOMED CT defining relationships, as well as discovering data about drug classes that is present in the terminology releases. This application facilitates a number of clinical decision support functions, including duplicate therapy checking and linking to relevant drug monographs. The use of SNOMED CT concepts in the GDM is illustrated in the screenshot shown in the diagram below.

Orion Health Medicines supports an authoritative medication list for each patient, and enables its curation, reconciliation and management. The Medicines application uses the FHIR APIs from GDM to allow the discovery and validation of medications. Patients can also manage their own list of medications via the Orion Health Patient Portal or the Orion Health Engage mobile application.

Orion Health Problem List is a centralized and web-based list of patient problems. It enables healthcare providers to view, create and change clinical information, procedures, psychosocial and cultural issues that may affect the care of the patient, as well as safety and security concerns that may be relevant to medical staff caring for the patient. The Problem List application also integrates with GDM via the FHIR APIs, and enables clinicians to record allergies, adverse reactions and intolerances at the drug class level. The Problem List application is fully integrated with SNOMED CT, with a variety of fields using SNOMED CT subsets.

The Clinical Decision Support (CDS) application is a new product that integrates with the three applications mentioned above, as well as other third party decision support applications. The CDS application provides APIs to support duplicate drug therapy checking, drug allergy checking, links to drug monographs and additional drug information, and grouping of similar medications based on a common ingredient or therapeutic moiety.

For example, when new medications are added to a patient’s medication list, they are automatically screened against the current list of medications for that patient using the CDS Duplicate Therapy API. This check ensures that the clinician is advised of existing medications with the same ingredients. Clinicians viewing medications are able to access drug monographs and any other additional information listed against a medication. The medication list is also screened using the CDS Drug Allergy API, which presents a warning if a drug allergy or intolerance to a particular medication or drug class is detected. These checks use data traversal algorithms that were developed by Orion Health for fast traversal of the SNOMED CT concept hierarchy and defining relationships. The warnings have been specifically designed to minimize alert fatigue. The Orion Health Problem List application is shown below in the diagram below with an adverse reaction alert.