Eos and OMOCL: Towards a seamless integration of openEHR records into the OMOP Common Data Model.

BACKGROUND: The reuse of data from electronic health records (EHRs) for research purposes promises to improve the data foundation for clinical trials and may even support to enable them. Nevertheless, EHRs are characterized by both, heterogeneous structure and semantics. To standardize this data for research, the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standard has recently seen an increase in use. However, the conversion of these EHRs into the OMOP CDM requires complex and resource intensive Extract Transform and Load (ETL) processes. This hampers the reuse of clinical data for research. To solve the issues of heterogeneity of EHRs and the lack of semantic precision on the care site, the openEHR standard has recently seen wider adoption. A standardized process to integrate openEHR records into the CDM potentially lowers the barriers of making EHRs accessible for research. Yet, a comprehensive approach about the integration of openEHR records into the OMOP CDM has not yet been made. METHODS: We analyzed both standards and compared their models to identify possible mappings. Based on this, we defined the necessary processes to transform openEHR records into CDM tables. We also discuss the limitation of openEHR with its unspecific demographics model and propose two possible solutions. RESULTS: We developed the OMOP Conversion Language (OMOCL) which enabled us to define a declarative openEHR archetype-to-CDM mapping language. Using OMOCL, it was possible to define a set of mappings. As a proof-of-concept, we implemented the Eos tool, which uses the OMOCL-files to successfully automatize the ETL from real-world and sample EHRs into the OMOP CDM. DISCUSSION: Both Eos and OMOCL provide a way to define generic mappings for an integration of openEHR records into OMOP. Thus, it represents a significant step towards achieving interoperability between the clinical and the research data domains. However, the transformation of openEHR data into the less expressive OMOP CDM leads to a loss of semantics.

The COVID-19 Data Exchange Platform of the German University Medicine.

COVID-19 has challenged the healthcare systems worldwide. To quickly identify successful diagnostic and therapeutic approaches large data sharing approaches are inevitable. Though organizational clinical data are abundant, many of them are available only in isolated silos and largely inaccessible to external researchers. To overcome and tackle this challenge the university medicine network (comprising all 36 German university hospitals) has been founded in April 2020 to coordinate COVID-19 action plans, diagnostic and therapeutic strategies and collaborative research activities. 13 projects were initiated from which the CODEX project, aiming at the development of a Germany-wide Covid-19 Data Exchange Platform, is presented in this publication. We illustrate the conceptual design, the stepwise development and deployment, first results and the current status.

openEHR-to-FHIR: Converting openEHR Compositions to Fast Healthcare Interoperability Resources (FHIR) for the German Corona Consensus Dataset (GECCO).

The German Corona Consensus (GECCO) established a uniform dataset in FHIR format for exchanging and sharing interoperable COVID-19 patient specific data between health information systems (HIS) for universities. For sharing the COVID-19 information with other locations that use openEHR, the data are to be converted in FHIR format. In this paper, we introduce our solution through a web-tool named "openEHR-to-FHIR" that converts compositions from an openEHR repository and stores in their respective GECCO FHIR profiles. The tool provides a REST web service for ad hoc conversion of openEHR compositions to FHIR profiles.

A Report on Archetype Modelling in a Nationwide Data Infrastructure Project.

BACKGROUND: The nationwide data infrastructure project HiGHmed strives for achieving semantic interoperability through the use of openEHR archetypes. Therefore, a knowledge governance framework defining collaborative modelling processes has been established. For long-sustained success and the creation of high-quality archetypes, continuous monitoring is vital. OBJECTIVES: To present an update on archetype modelling and governance framework establishment in HiGHmed. METHODS: Qualitative and quantitative analyses of the progress in establishing modelling groups, roles and users, realizing modelling workflows, and modelling archetypes. RESULTS: Currently, 25 modellers and 17 domain experts are participating. 79 archetypes have been identified, from which 69 are pre-existing and internationally published; completion rates of review rounds are satisfying but improvable. CONCLUSIONS: The governance framework is valuable to make the activities manageable and to accelerate modelling. Combined with highly engaged data stewards and clinicians, a reasonable number of archetypes have already been developed.

HiGHmed - An Open Platform Approach to Enhance Care and Research across Institutional Boundaries.

INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. HiGHmed brings together 24 partners from academia and industry, aiming at improvements in care provision, biomedical research and epidemiology. By establishing a shared information governance framework, data integration centers and an open platform architecture in cooperation with independent healthcare providers, the meaningful reuse of data will be facilitated. Complementary, HiGHmed integrates a total of seven Medical Informatics curricula to develop collaborative structures and processes to train medical informatics professionals, physicians and researchers in new forms of data analytics. GOVERNANCE AND POLICIES: We describe governance structures and policies that have proven effective during the conceptual phase. These were further adapted to take into account the specific needs of the development and networking phase, such as roll-out, carerelated aspects and our focus on curricula development in Medical Inform atics. ARCHITECTURAL FRAMEWORK AND METHODOLOGY: To address the challenges of organizational, technical and semantic interoperability, a concept for a scalable platform architecture, the HiGHmed Platform, was developed. We outline the basic principles and design goals of the open platform approach as well as the roles of standards and specifications such as IHE XDS, openEHR, SNOMED CT and HL7 FHIR. A shared governance framework provides the semantic artifacts which are needed to establish semantic interoperability. USE CASES: Three use cases in the fields of oncology, cardiology and infection control will demonstrate the capabilities of the HiGHmed approach. Each of the use cases entails diverse challenges in terms of data protection, privacy and security, including clinical use of genome sequencing data (oncology), continuous longitudinal monitoring of physical activity (cardiology) and cross-site analysis of patient movement data (infection control). DISCUSSION: Besides the need for a shared governance framework and a technical infrastructure, backing from clinical leaders is a crucial factor. Moreover, firm and sustainable commitment by participating organizations to collaborate in further development of their information system architectures is needed. Other challenges including topics such as data quality, privacy regulations, and patient consent will be addressed throughout the project.

An interoperable clinical decision-support system for early detection of SIRS in pediatric intensive care using openEHR.

BACKGROUND: Clinical decision-support systems (CDSS) are designed to solve knowledge-intensive tasks for supporting decision-making processes. Although many approaches for designing CDSS have been proposed, due to high implementation costs, as well as the lack of interoperability features, current solutions are not well-established across different institutions. Recently, the use of standardized formalisms for knowledge representation as terminologies as well as the integration of semantically enriched clinical information models, as openEHR Archetypes, and their reuse within CDSS are theoretically considered as key factors for reusable CDSS. OBJECTIVE: We aim at developing and evaluating an openEHR based approach to achieve interoperability in CDSS by designing and implementing an exemplary system for automated systemic inflammatory response syndrome (SIRS) detection in pediatric intensive care. METHODS: We designed an interoperable concept, which enables an easy integration of the CDSS across different institutions, by using openEHR Archetypes, terminology bindings and the Archetype Query Language (AQL). The practicability of the approach was tested by (1) implementing a prototype, which is based on an openEHR based data repository of the Hannover Medical School (HaMSTR), and (2) conducting a first pilot study. RESULTS: We successfully designed and implemented a CDSS with interoperable knowledge bases and interfaces by reusing internationally agreed-upon Archetypes, incorporating LOINC terminology and creating AQL queries, which allowed retrieving dynamic facts in a standardized and unambiguous form. The technical capabilities of the system were evaluated by testing the prototype on 16 randomly selected patients with 129 days of stay, and comparing the results with the assessment of clinical experts (leading to a sensitivity of 1.00, a specificity of 0.94 and a Cohen's kappa of 0.92). CONCLUSIONS: We found the use of openEHR Archetypes and AQL a feasible approach to bridge the interoperability gap between local infrastructures and CDSS. The designed concept was successfully transferred into a clinically evaluated openEHR based CDSS. To the authors' knowledge, this is the first openEHR based CDSS, which is technically reliable and capable in a real context, and facilitates clinical decision-support for a complex task. Further activities will comprise enrichments of the knowledge base, the reasoning processes and cross-institutional evaluations.

Clinical Knowledge Governance Framework for Nationwide Data Infrastructure Projects.

BACKGROUND: The availability of semantically-enriched and interoperable clinical information models is crucial for reusing once collected data across institutions like aspired in the German HiGHmed project. Funded by the Federal Ministry of Education and Research, this nationwide data infrastructure project adopts the openEHR approach for semantic modelling. Here, strong governance is required to define high-quality and reusable models. OBJECTIVES: Design of a clinical knowledge governance framework for openEHR modelling in cross-institutional settings like HiGHmed. METHODS: Analysis of successful practices from international projects, published ideas on archetype governance and own modelling experiences as well as modelling of BPMN processes. RESULTS: We designed a framework by presenting archetype variations, roles and responsibilities, IT support and modelling workflows. CONCLUSION: Our framework has great potential to make the openEHR modelling efforts manageable. Because practical experiences are rare, prospectively our work will be predestinated to evaluate the benefits of such structured governance approaches.

On Teaching International Courses on Health Information Systems. Lessons Learned during 16 Years of Frank - van Swieten Lectures on Strategic Information Management in Health Information Systems.

BACKGROUND: Health information systems (HIS) are one of the most important areas for biomedical and health informatics. In order to professionally deal with HIS well-educated informaticians are needed. Because of these reasons, in 2001 an international course has been established: The Frank - van Swieten Lectures on Strategic Information Management of Health Information Systems. OBJECTIVES: Reporting about the Frank - van Swieten Lectures and about our students' feedback on this course during the last 16 years. Summarizing our lessons learned and making recommendations for such international courses on HIS. METHODS: The basic concept of the Frank - van Swieten lectures is to teach the theoretical background in local lectures, to organize practical exercises on modelling sub-information systems of the respective local HIS and finally to conduct Joint Three Days as an international meeting were the resulting models are introduced and compared. RESULTS: During the last 16 years, the Universities of Amsterdam, Braunschweig, Heidelberg/Heilbronn, Leipzig as well as UMIT were involved in running this course. Overall, 517 students from these universities participated. Our students' feedback was clearly positive. The Joint Three Days of the Frank - van Swieten Lectures, where at the end of the course all students can meet, turned out to be an important component of this course. Based on the last 16 years, we recommend common teaching materials, agreement on equivalent clinical areas for the exercises, support of group building of international student groups, motivation of using a collaboration platform, ensuring quality management of the course, addressing different levels of knowledge of the students, and ensuring sufficient funding for joint activities. CONCLUSIONS: Although associated with considerable additional efforts, we can clearly recommend establishing such international courses on HIS, such as the Frank - van Swieten Lectures.

Modelling of Operative Report Documents for Data Integration into an openEHR-Based Enterprise Data Warehouse.

In order to integrate operative report documents from two operating room management systems into a data warehouse, we investigated the application of the two-level modelling approach of openEHR to create a shared data model. Based on the systems' analyses, a template consisting of 13 archetypes has been developed. Of these 13 archetypes, 3 have been obtained from the international archetype repository of the openEHR foundation. The remaining 10 archetypes have been newly created. The template was evaluated by an application system expert and through conducting a first test mapping of real-world data from one of the systems. The evaluation showed that by using the two-level modelling approach of openEHR, we succeeded to represent an integrated and shared information model for operative report documents. More research is needed to learn about the limitations of this approach in other data integration scenarios.

Automated population of an i2b2 clinical data warehouse from an openEHR-based data repository.

BACKGROUND: Detailed Clinical Model (DCM) approaches have recently seen wider adoption. More specifically, openEHR-based application systems are now used in production in several countries, serving diverse fields of application such as health information exchange, clinical registries and electronic medical record systems. However, approaches to efficiently provide openEHR data to researchers for secondary use have not yet been investigated or established. METHODS: We developed an approach to automatically load openEHR data instances into the open source clinical data warehouse i2b2. We evaluated query capabilities and the performance of this approach in the context of the Hanover Medical School Translational Research Framework (HaMSTR), an openEHR-based data repository. RESULTS: Automated creation of i2b2 ontologies from archetypes and templates and the integration of openEHR data instances from 903 patients of a paediatric intensive care unit has been achieved. In total, it took an average of ∼2527s to create 2.311.624 facts from 141.917 XML documents. Using the imported data, we conducted sample queries to compare the performance with two openEHR systems and to investigate if this representation of data is feasible to support cohort identification and record level data extraction. DISCUSSION: We found the automated population of an i2b2 clinical data warehouse to be a feasible approach to make openEHR data instances available for secondary use. Such an approach can facilitate timely provision of clinical data to researchers. It complements analytics based on the Archetype Query Language by allowing querying on both, legacy clinical data sources and openEHR data instances at the same time and by providing an easy-to-use query interface. However, due to different levels of expressiveness in the data models, not all semantics could be preserved during the ETL process.

Automated Transformation of openEHR Data Instances to OWL.

Standard-based integration and semantic enrichment of clinical data originating from electronic medical records has shown to be critical to enable secondary use. To facilitate the utilization of semantic technologies on clinical data, we introduce a methodology to enable automated transformation of openEHR-based data to Web Ontology Language (OWL) individuals. To test the correctness of the implementation, de-identified data of 229 patients of the pediatric intensive care unit of Hannover Medical School has been transformed into 2.983.436 individuals. Querying of the resulting ontology for symptoms of the systemic inflammatory response syndrome (SIRS) yielded the same result set as a SQL query on an openEHR-based clinical data repository.

Design and implementation of an informed consent process for a standardized health information exchange solution on the example of the lower saxony bank of health.

OBJECTIVE: Multicenter medical treatment requires health related data to be available across institutions. Since health information exchange solutions are emergent, fulfillment of privacy needs, including patients' informed consent, is vital for successful data exchange. METHODS: We designed a software supported consent process for the recently founded Lower Saxony Bank of Health (LSBH) with regard to particularities of German law. To implement the application, web technologies and well-described interfaces to IHE XDS profile components have been used. RESULTS: A two staged process has been developed. A special consent application creates a customized form containing all orally given constraints defined by the patient. The form is printed out and signed by the patient while an electronic policy is created and registered at the LSBH. CONCLUSION: The process completely reflects a conventional informed consent procedure but increases simplicity, clarity and understandability of the consent form. Technical and legal restrictions in Germany create a media split becoming a media crack in some environments. Availability of signature cards could improve the process by making it completely electronic.

Primary care provider's acceptance of health information exchange utilizing IHE XDS.

OBJECTIVE: We assessed primary care providers' perception of a health information exchange system (HIE) based on IHE XDS in the metropolitan area of Braunschweig, Lower Saxony, Germany. DESIGN: An application enabling access to medical documents in an XDS Affinity Domain was developed. We examined usability and factors related to user acceptance. MEASUREMENTS: User perception was probed using system usability scale (SUS) and semi-structured interviews. The framework analysis was used in the review and interpretation of the interview data. RESULTS: The evaluation was performed on 7 participants. The SUS showed an above average usability with a median score of 77.5. Participants submitted suggestions for additional features and improvement of usability. Poor integration of functionality into existing workflows was most frequently criticized. CONCLUSION: We found, that, while usability was well perceived by primary care providers, challenges remain in adoption of XDS based IHE.

Primary care providers' acceptance of health information exchange utilizing IHE XDS.

We assessed primary care providers' perception of a health information exchange system (HIE) based on IHE XDS. The HIE will be part of a regional health network in the metropolitan area of Braunschweig, Lower Saxony, Germany. An application enabling access to medical documents in an XDS Affinity Domain was developed. We examined usability and factors related to user acceptance. User perception was probed using system usability scale (SUS) and semi-structured interviews. The evaluation was performed on 7 participants. The SUS showed an above average usability with a median score of 77.5. During interviews, participants submitted suggestions for additional features and improvement of usability. Poor integration of functionality into existing workflows was most frequently criticized. While usability was well perceived by primary care providers, challenges remain in adoption of XDS based IHE. To speed up document access in time-critical domains, we suggest use of complementary methods, enabling directed communication flows.