HL7 V3 Research Articles

Challenges and Lessons Learned in Mapping HL7 v2 Data to openEHR: Insights from UKSH Medical Data Integration Center.

This paper explores the challenges and lessons learned during the mapping of HL7 v2 messages structured using custom schema to openEHR for the Medical Data Integration Center (MeDIC) of the University Hospital, Schleswig-Holstein (UKSH). Missing timestamps in observations, missing units of measurement, inconsistencies in decimal separators and unexpected datatypes were identified as critical inconsistencies in this process. These anomalies highlight the difficulty of automating the transformation of HL7 v2 data to any standard, particularly openEHR, using off-the-shelf tools. Addressing these anomalies is crucial for enhancing data interoperability, supporting evidence-based research, and optimizing clinical decision-making. Implementing proper data quality measures and governance will unlock the potential of integrated clinical data, empowering clinicians and researchers and fostering a robust healthcare ecosystem.

Structured Data Retrieval and Analysis of HL7 v2 Messages with Elasticsearch.

The era of the electronic health record (EHR) requires lots of semantic interoperability for data sharing and reusability. We select HL7 v2 messages as the most common structured data type in hospital information systems, to investigate the plausibility of using Elasticsearch (ES) as a healthcare search engine and data analytics tool. Due to the facts, Elasticsearch can be integrated as a powerful searchable database for practical healthcare applications, to analyze structured healthcare data from various locations. It allows easy and efficient searching for complex query tasks.

Initial Experience of 10 Imaging Vendors with the IHE SHARAZONE: a New Multivendor Peer-to-Peer Test Service for DICOM Objects.

Alignment of DICOM (Digital Imaging and Communications in Medicine) capabilities among vendors is crucial to improve interoperability in the healthcare industry and advance medical imaging 2. However, a sustainable model for sharing DICOM samples is not available. To address this issue, Integrating the Healthcare Enterprise (IHE) has introduced the IHE SHARAZONE, a continuous cross-vendor DICOM data sharing test service.IHE is a highly regarded organization known for profiling standards such as DICOM, HL7 v2 (Health Level Seven, version 2), HL7 CDA (Clinical Document Architecture), and HL7 FHIR (Fast Healthcare Interoperability Resources) into practical solutions for clinical practice. The primary goal of the IHE SHARAZONE is to provide a reliable and consistent cross-vendor DICOM data sharing system.To evaluate its effectiveness, a 5-month pilot was conducted with ten imaging vendors. The pilot concluded with a participant survey, which yielded valuable insights into the initial experience with the IHE SHARAZONE. These findings can inform future improvements and developments to this important service.

A Framework for Automatic Clustering of EHR Messages Using a Spatial Clustering Approach.

Although Health Level Seven (HL 7) message standards (v2, v3, Clinical Document Architecture (CDA)) have been commonly adopted, there are still issues associated with them, especially the semantic interoperability issues and lack of support for smart devices (e.g., smartphones, fitness trackers, and smartwatches), etc. In addition, healthcare organizations in many countries are still using proprietary electronic health record (EHR) message formats, making it challenging to convert to other data formats-particularly the latest HL7 Fast Health Interoperability Resources (FHIR) data standard. The FHIR is based on modern web technologies such as HTTP, XML, and JSON and would be capable of overcoming the shortcomings of the previous standards and supporting modern smart devices. Therefore, the FHIR standard could help the healthcare industry to avail the latest technologies benefits and improve data interoperability. The data representation and mapping from the legacy data standards (i.e., HL7 v2 and EHR) to the FHIR is necessary for the healthcare sector. However, direct data mapping or conversion from the traditional data standards to the FHIR data standard is challenging because of the nature and formats of the data. Therefore, in this article, we propose a framework that aims to convert proprietary EHR messages into the HL7 v2 format and apply an unsupervised clustering approach using the DBSCAN (density-based spatial clustering of applications with noise) algorithm to automatically group a variety of these HL7 v2 messages regardless of their semantic origins. The proposed framework's implementation lays the groundwork to provide a generic mapping model with multi-point and multi-format data conversion input into the FHIR. Our experimental results show the proposed framework's ability to automatically cluster various HL7 v2 message formats and provide analytic insight behind them.

Towards Unified Data Exchange Formats for Reporting Molecular Drug Susceptibility Testing.

With the rapid development of new advanced molecular detection methods, identification of new genetic mutations conferring pathogen resistance to an ever-growing variety of antimicrobial substances will generate massive genomic datasets for public health and clinical laboratories. Keeping up with specialized standard coding for these immense datasets will be extremely challenging. This challenge prompted our effort to create a common molecular resistance Logical Observation Identifiers Names and Codes (LOINC) panel that can be used to report any identified antimicrobial resistance pattern. To develop and utilize a common molecular resistance LOINC panel for molecular drug susceptibility testing (DST) data exchange in the U.S. National Tuberculosis Surveillance System using California Department of Public Health (CDPH) and New York State Department of Health as pilot sites. We developed an interface and mapped incoming molecular DST data to the common molecular resistance LOINC panel using Health Level Seven (HL7) v2.5.1 Electronic Laboratory Reporting (ELR) message specifications through the Orion Health™ Rhapsody Integration Engine v6.3.1. Both pilot sites were able to process and upload/import the standardized HL7 v2.5.1 ELR messages into their respective systems; albeit CDPH identified areas for system improvements and has focused efforts to streamline the message importation process. Specifically, CDPH is enhancing their system to better capture parent-child elements and ensure that the data collected can be accessed seamlessly by the U.S. Centers for Disease Control and Prevention. The common molecular resistance LOINC panel is designed to be generalizable across other resistance genes and ideally also applicable to other disease domains. The study demonstrates that it is possible to exchange molecular DST data across the continuum of disparate healthcare information systems in integrated public health environments using the common molecular resistance LOINC panel.

Version-Compatible HL7 Parser Based on Object-Oriented Design

International standards for the exchange of healthcare information, known as Health Level Seven (HL7), were developed for the interoperability of healthcare information systems. Because of HL7’s complex structure and syntax, HL7 messages are processed by computer software. HL7 defines that, when the version is updated, it should be compatible with the previous version. However, most of the HL7 interface software that is currently in development does not consider the version compatibility of HL7 messages. Instead, a separate conversion software module has been used to handle the version compatibility of HL7 messages for the healthcare information system. However, such a method is inefficient, because it requires several hours and incurs a huge cost. Therefore, in this study, an HL7 parser was developed that not only supports backward compatibility with older versions in accordance with the version compatibility definition of the HL7 V2 messages but also guarantees forward compatibility with newer versions to enhance its utilization. The developed parser was used to test conversion between different versions of HL7 V2 messages which were created to transmit information from one healthcare device to another. Through this test, the usefulness of the developed parser was verified.

Informatics External Quality Assurance (IEQA) Down Under: evaluation of a pilot implementation

AbstractExternal quality assurance (EQA) provides ongoing evaluation to verify that laboratory medicine results conform to quality standards expected for patient care. While attention has focused predominantly on test accuracy, the diagnostic phases, consisting of pre- and post-laboratory phases of testing, have thus far lagged in the development of an appropriate diagnostic-phase EQA program. One of the challenges faced by Australian EQA has been a lack of standardisation or “harmonisation” resulting from variations in reporting between different laboratory medicine providers. This may introduce interpretation errors and misunderstanding of results by clinicians, resulting in a threat to patient safety. While initiatives such as the Australian Pathology Information, Terminology and Units Standardisation (PITUS) program have produced Standards for Pathology Informatics in Australia (SPIA), conformity to these requires regular monitoring to maintain integrity of data between sending (laboratory medicine providers) and receiving (physicians, MyHealth Record, registries) organisations’ systems. The PITUS 16 Informatics EQA (IEQA) Project together with the Royal College of Pathologists of Australasia Quality Assurance Programs (RCPAQAP) has created a system to perform quality assurance on the electronic laboratory message when the laboratory sends a result back to the EQA provider. The purpose of this study was to perform a small scale pilot implementation of an IEQA protocol, which was performed to test the suitability of the system to check compliance of existing Health Level-7 (HL7 v2.4) reporting standards localised and constrained by the RCPA SPIA. Here, we present key milestones from the implementation, including: (1) software development, (2) installation, and verification of the system and communication services, (3) implementation of the IEQA program and compliance testing of the received HL7 v2.4 report messages, (4) compilation of a draft Informatics Program Survey Report for each laboratory and (5) review consisting of presentation of a report showing the compliance checking tool to each participating laboratory.

Informatics External Quality Assurance (IEQA) Down Under: evaluation of a pilot implementation

External quality assurance (EQA) provides ongoing evaluation to verify that laboratory medicine results conform to quality standards expected for patient care. While attention has focused predominantly on test accuracy, the diagnostic phases, consisting of pre- and post-laboratory phases of testing, have thus far lagged in the development of an appropriate diagnostic-phase EQA program. One of the challenges faced by Australian EQA has been a lack of standardisation or “harmonisation” resulting from variations in reporting between different laboratory medicine providers. This may introduce interpretation errors and misunderstanding of results by clinicians, resulting in a threat to patient safety. While initiatives such as the Australian Pathology Information, Terminology and Units Standardisation (PITUS) program have produced Standards for Pathology Informatics in Australia (SPIA), conformity to these requires regular monitoring to maintain integrity of data between sending (laboratory medicine providers) and receiving (physicians, MyHealth Record, registries) organisations’ systems. The PITUS 16 Informatics EQA (IEQA) Project together with the Royal College of Pathologists of Australasia Quality Assurance Programs (RCPAQAP) has created a system to perform quality assurance on the electronic laboratory message when the laboratory sends a result back to the EQA provider. The purpose of this study was to perform a small scale pilot implementation of an IEQA protocol, which was performed to test the suitability of the system to check compliance of existing Health Level-7 (HL7 v2.4) reporting standards localised and constrained by the RCPA SPIA. Here, we present key milestones from the implementation, including: (1) software development, (2) installation, and verification of the system and communication services, (3) implementation of the IEQA program and compliance testing of the received HL7 v2.4 report messages, (4) compilation of a draft Informatics Program Survey Report for each laboratory and (5) review consisting of presentation of a report showing the compliance checking tool to each participating laboratory.

Querying clinical data in HL7 RIM based relational model with morph-RDB

BackgroundSemantic interoperability is essential when carrying out post-genomic clinical trials where several institutions collaborate, since researchers and developers need to have an integrated view and access to heterogeneous data sources. One possible approach to accommodate this need is to use RDB2RDF systems that provide RDF datasets as the unified view. These RDF datasets may be materialized and stored in a triple store, or transformed into RDF in real time, as virtual RDF data sources. Our previous efforts involved materialized RDF datasets, hence losing data freshness.ResultsIn this paper we present a solution that uses an ontology based on the HL7 v3 Reference Information Model and a set of R2RML mappings that relate this ontology to an underlying relational database implementation, and where morph-RDB is used to expose a virtual, non-materialized SPARQL endpoint over the data.ConclusionsBy applying a set of optimization techniques on the SPARQL-to-SQL query translation algorithm, we can now issue SPARQL queries to the underlying relational data with generally acceptable performance.

Real-Time or Near Real-Time Persisting Daily Healthcare Data Into HDFS and ElasticSearch Index Inside a Big Data Platform

Mayo Clinic (MC) healthcare generates a large number of HL7 V2 messages—0.7–1.1 million on weekends and 1.7–2.2 million on business days at present. With multiple RDBMS-based systems, such a large volume of HL7 messages still cannot be real-time or near-real-time stored, analyzed, and retrieved for enterprise-level clinic and nonclinic usage. To determine if Big Data technology coupled with ElasticSearch technology can satisfy MC daily healthcare needs for HL7 message processing, a BigData platform was developed to contain two identical Hadoop clusters (TDH1.3.2 version)—each containing an ElasticSearch cluster and instances of a storm topology—MayoTopology for processing HL7 messages on MC ESB queues into an ElasticSearch index and the HDFS. The implemented BigData platform can process 62 ± 4 million HL7 messages per day while the ElasticSearch index can provide ultrafast free-text searching at a speed level of 0.2-s per query on an index containing a dataset of 25 million HL7-derived-JSON-documents. The results suggest that the implemented BigData platform exceeds MC enterprise-level patient-care needs.

Advancing HL7 v2 to New Heights: A Platform for Developing Specifications, Test Plans, and Testing Tools

Development of HL7 v2 data exchange interface specifications has long been problematic, plagued with ambiguous and inconsistent requirement specifications. This situation leads to potential misinterpretation by implementers, thus limiting the effectiveness of the specification and creating artificial and unnecessary barriers to interoperability. Likewise, the ability to test implementations effectively for conformance to the specifications is hindered. The current approach of specification development and test plan creation relies on word processing tools, meaning implementers and testers must read and interpret the information in these documents and then translate it into machine-computable requirements and test assertions. This approach is error prone—a better methodology is needed. We present a set of productivity tools in an integrated platform that allow users to define and constrain HL7 v2 specifications and to develop test plans that result in machine-computable artifacts. A testing infrastructure and framework subsequently uses these artifacts to create conformance testing tools automatically. We present and demonstrate the utility of a platform for developing specifications, writing test plans, and creating testing tools. The value proposition of this end-to-end methodology is explained for authors writing HL7 v2 specifications, for developers implementing interfaces, and for testers creating validation tools.

Meaningful clinical communication and Integrated Care in Barcelona. Eight years of experience

Context: Public healthcare system in Catalonia is based on yearly contracts stablished among the Public Healtcare Administration (Catsalut) and the different Healthcare Organizations (HCO). Each one has its own Electronic Patient Record (EPR) system.In 2006 a task force group was committed for a radical redesign of the healthcare in an area of Barcelona with a population on 600.000 inhabitants with a focus on the improvement in the relationship between Primary care (PC) and Specialized Care (SC) for a better integrated care for the population. Once the new model was accepted by all the HCO, an specific workgroup was created to develop a ICT-supported system to interchange meaningful clinical information and enable the continuity of care. Twenty-three centers were involved. They belong to nine different HCO: three hospitals, one SC outpatient clinic and six PC organizations. Initial analysis of the departure situation resulted in a high heterogeneity in relation to the degree of technological investment, development and maturity in the use of EPRs by the professionals. Several ICTs options were considered. The decision was to implement an interchange platform using structured xml files with clinical content based on standadrd HL7 v2.5 messages.Results: The solution got the integrated connection of all the EPRs of the different HCOs in spite of their big differences. Also the project has speed-up the process of investment and maturity in the use of EPR in those HCOs with a worse departure situation. The overall system supports the full information cycle of several clinical processes like the patient referral from PC to SC with all the possible circumstances at each step in the workflow and the return of clinical documentation, the request for specific procedures from PC to SC with the return of the report and the related images if it’s the case, the communication to PC of the admission of a patient at the Emergency ward and the return of the discharge reports, as well as new collaboration processes like the teleconsultation in Dermatology. All the messages are completely generated and fully integrated in all the different EPRs of the nine HCOs.Since January 2010 until December 2015 statistics showed a total of 323360 requests from PC to the SC centers, 577.575 professional integrated care activities done over the patients, 839.779 relevant clinical documents and 91374 images done at the hospitals delivered on time at the point of care accessible by the PC centers. All of these transactions are the result of standardize and improve existing workflows using ICTs. Outstanding results have been the start up of Teledermatology, a new service made possible through ICTs. Quality of the images provided by the PC physicians were good enough in 94,3% of the cases. Delay in the SC answer has been reduced to 1,84 days and avoiding more than a half of the SC visits at the hospital (58,2%).Conclusions: Several management and clinical scores demonstrates the benefits of such implementation in the quality of care of the population covered by the HCOs. The other big achievement has been the standardization of the clinical processes in this area of the Barcelona city.A good Governance model of the different IT departments involved as well as the ICT providers, based upont profesionalism, leadership and transparency, is a key point for the successAt this moment we are in the process to evolve to a bigger platform with the capability to connect all the HCO and centers in Catalonia.

Proposed model for a Romanian register of chronic diseases in children

Background and ObjectivesThe prevalence of chronic diseases at children is increasing due to the progress made in medicine, which radically changed the evolution and the prognostics. Disease registers became important tools to register and monitor the chronic patients in order to asses their needs and improve their care. Disease registers are also very important for adjusting to population needs the actions in the public health field.The main objective for this research is to develop a model for a chronic disease register of children in Romania, taking into account the current situation of chronic diseases’ registration and reporting, the specific requirements for such medical database and the particularities of the information systems in the Romanian healthcare system. MethodsOur study was based on interviews with specialists and Health Ministry representatives, field observations, and analysis of published and unpublished data). ResultsWe developed a platform for a chronic diseases register of children based on open EHR specifications and architecture, which respects the requirements for data security and the particularities of Romania's healthcare system. The model created is functioning on two levels. The first one is local and corresponds to a medical unit, while the second one represents the connection and the communication method within the entire national medical system. In order to achieve the highest level of interoperability at the semantic level, we used, for the communication module of a National Disease Register system, only EN 13606 or HL7 v3 and / or HL7 v3 CDA. ConclusionsThis model is functional and can be applied initially at a clinical level for medical and administrative purposes. Its design allows a future development, integrated with the current informational systems and implemented at regional and national level. This will significantly improve the knowledge that may support good medical practice in this field, will enhance the coherence of data collection and, as a consequence, will impact positevely on the health of children diagnosed with chronic diseases.

A Querying Method over RDF-ized Health Level Seven v2.5 Messages Using Life Science Knowledge Resources.

BackgroundHealth level seven version 2.5 (HL7 v2.5) is a widespread messaging standard for information exchange between clinical information systems. By applying Semantic Web technologies for handling HL7 v2.5 messages, it is possible to integrate large-scale clinical data with life science knowledge resources.ObjectiveShowing feasibility of a querying method over large-scale resource description framework (RDF)-ized HL7 v2.5 messages using publicly available drug databases.MethodsWe developed a method to convert HL7 v2.5 messages into the RDF. We also converted five kinds of drug databases into RDF and provided explicit links between the corresponding items among them. With those linked drug data, we then developed a method for query expansion to search the clinical data using semantic information on drug classes along with four types of temporal patterns. For evaluation purpose, medication orders and laboratory test results for a 3-year period at the University of Tokyo Hospital were used, and the query execution times were measured.ResultsApproximately 650 million RDF triples for medication orders and 790 million RDF triples for laboratory test results were converted. Taking three types of query in use cases for detecting adverse events of drugs as an example, we confirmed these queries were represented in SPARQL Protocol and RDF Query Language (SPARQL) using our methods and comparison with conventional query expressions were performed. The measurement results confirm that the query time is feasible and increases logarithmically or linearly with the amount of data and without diverging.ConclusionsThe proposed methods enabled query expressions that separate knowledge resources and clinical data, thereby suggesting the feasibility for improving the usability of clinical data by enhancing the knowledge resources. We also demonstrate that when HL7 v2.5 messages are automatically converted into RDF, searches are still possible through SPARQL without modifying the structure. As such, the proposed method benefits not only our hospitals, but also numerous hospitals that handle HL7 v2.5 messages. Our approach highlights a potential of large-scale data federation techniques to retrieve clinical information, which could be applied as applications of clinical intelligence to improve clinical practices, such as adverse drug event monitoring and cohort selection for a clinical study as well as discovering new knowledge from clinical information.

An Open Source Quality Assurance Tool for HL7 v2 Syndromic Surveillance Messages

This project served as a proof-of-concept for implementing an Open Source, web-based data quality assurance (QA) tool to qualify new sites for reporting syndromic surveillance data electronically to public health via HL7 v2 messages, and for monitoring the ongoing quality of data submissions over time. This was accomplished by leveraging existing validation software from NIST and the user interface component from NYC Citywide Immunization Registry (CIR).

Improved Handling of Synonymous SNOMED CT Concepts used in HL7 Version 3 by the Example of the Von Willebrand Disease

Background: In the context of synonymous concepts, errors and term duplications in SNOMED CT are likely. This a ects in particular clinical ideas with multiple types of display, like the example of the Von Willebrand disease. Objectives: It is required to ensure a common and correct interpretation of medical terms. Thus, it is necessary to distinguish between the clinical ideas of disease, disorder and syndrome in the Von Willebrand context. To perform a critical examination of the associated hierarchical order in SNOMED CT and above that, to follow the given rules of correct terminology binding. Methods: The synonymous concepts problem is ana- lyzed in reference to the Von Willebrand context in the SNOMED CT International Version 31012015. Improve- ments of handling are formulated based on the valid SNOMED CT compositional grammar and the SNOMED CT Editorial Guidelines. Terminology binding is examined regarding the prerequisites given in the Using SNOMED CT in HL7 Version 3 Implementation Guide, Release 1.5 Results: Many Von Willebrand concepts in SNOMED CT are not fully de ned but primitive, which means that their de ning characteristics are not sucient to distigu- ish synonymous meanings. Improved handling of synony- mous concepts is proposed by the installation of a broader grouper concept and an adaption of the SNOMED CT hi- erarchical structure to avoid misinterpretations and dupli- cations. Conclusions: The terminology binding between the SNOMED CT semantics in the Von Willebrand context and HL7 V3 seems technically well described. It has been shown, that the problematic handling of synonymous terms is assigned to hierarchical structure problems out of SNOMED CT.

HL7 v2+: The Future of HL7 Version 2?

Background: HL7 version 2.x is the most popular and most propagated data exchange standard in the world. It is mature and adopted by several IHE Technical Frame- works. Nevertheless it has some weaknesses especially in the way it is documented. Several conformance constructs (optionality/usage and repetitions) are still under discus- sion although the meaning is unambiguous and clear. The deadline for HL7 v2.9 proposals is over and the next ballot is in preparation for May 2016. Objectives: Therefore the question arises what will come next? HL7 v2.10? HL7 International is in favor of dis- tributing new releases every year, so that this is a good opportunity to update the representation and documenta- tion of HL7 v2.x while maintaining backward compatibility for running interfaces. Methods: A semantic analysis of the conformance con- structs being used by HL7 v2.x allows for developing tran- sition matrices so that the new representation can be au- tomatically generated in large parts. Of course, a new separation into domains require manual support. Results: This paper demonstrates the new representation form rendered out of the HL7 Comprehensive Database. Conclusions: Harmonizing HL7 v2.x with other standards in the way it is represented simpli es implementation and therefore supports interoperability among applications.

Development of a Multi-Agent m-Health Application Based on Various Protocols for Chronic Disease Self-Management

The purpose of this study was to develop and evaluate a mobile health application (Self-Management mobile Personal Health Record: "SmPHR") to ensure the interoperability of various personal health devices (PHDs) and electronic medical record systems (EMRs) for continuous self-management of chronic disease patients. The SmPHR was developed for Android 4.0.3, and implemented according to the optimized standard protocol for each interface of healthcare services adopted by the Continua Health Alliance (CHA). That is, the Personal Area Network (PAN) interface between the application and PHD implements ISO/IEEE 11073-20,601, 10,404, 10,407, 10,415, 10,417, and Bluetooth Health Device Profile (HDP), and EMRs with a wide area network (WAN) interface implement HL7 V2.6; the Health Record Network (HRN) interface implements Continuity of Care Document (CCD) and Continuity of Care Record (CCR). Also, for SmPHR, we evaluated the transmission error rate between the interface using four PHDs and personal health record systems (PHRs) from previous research, with 611 users and elderly people after receiving institutional review board (IRB) approval. In the evaluation, the PAN interface showed 15 (2.4 %) errors, and the WAN and HRN interface showed 13 (2.1 %) errors in a total of 611 transmission attempts. Also, we received opinions regarding SmPHR from 15 healthcare professionals who took part in the clinical trial. Thus, SmPHR can be provided as an interconnected PHR mobile health service to patients, allowing 'plug and play' of PHDs and EMRs through various standard protocols.

Towards Standardized Patient Data Exchange: Integrating a FHIR Based API for the Open Medical Record System.

Interoperability is essential to address limitations caused by the ad hoc implementation of clinical information systems and the distributed nature of modern medical care. The HL7 V2 and V3 standards have played a significant role in ensuring interoperability for healthcare. FHIR is a next generation standard created to address fundamental limitations in HL7 V2 and V3. FHIR is particularly relevant to OpenMRS, an Open Source Medical Record System widely used across emerging economies. FHIR has the potential to allow OpenMRS to move away from a bespoke, application specific API to a standards based API. We describe efforts to design and implement a FHIR based API for the OpenMRS platform. Lessons learned from this effort were used to define long term plans to transition from the legacy OpenMRS API to a FHIR based API that greatly reduces the learning curve for developers and helps enhance adhernce to standards.

Combining Archetypes with Fast Health Interoperability Resources in Future-proof Health Information Systems.

Messaging standards, and specifically HL7 v2, are heavily used for the communication and interoperability of Health Information Systems. HL7 FHIR was created as an evolution of the messaging standards to achieve semantic interoperability. FHIR is somehow similar to other approaches like the dual model methodology as both are based on the precise modeling of clinical information. In this paper, we demonstrate how we can apply the dual model methodology to standards like FHIR. We show the usefulness of this approach for data transformation between FHIR and other specifications such as HL7 CDA, EN ISO 13606, and openEHR. We also discuss the advantages and disadvantages of defining archetypes over FHIR, and the consequences and outcomes of this approach. Finally, we exemplify this approach by creating a testing data server that supports both FHIR resources and archetypes.