Can OpenEHR, ISO 13606, and HL7 FHIR work together? An agnostic perspective for the selection and application of EHR standards in Spain.

Due to the heterogeneity of Electronic Health Record (EHR) standards, decision-making teams, who are not experts in health information, express confusion in selecting and applying these resources in their data platforms. Therefore, a group of experts has analyzed the strengths and weaknesses regarding the design, modeling capabilities, flexibility, and implemented resources of three relevant standards based on Detailed Clinical Models: OpenEHR, ISO 13606, and HL7 FHIR. Thus, it was concluded that: (1) they are useful for the purposes for which they have been designed and present deficiencies in those for which they have not been designed; (2) they are functionally compatible in platforms and health data methodologies developed from an independent perspective of the standards; and (3) they are conceptually and technically compatible with each other, so the choice of one or the other does not have a high impact as long as it starts from the one richer in modeling capabilities and flexibility.

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

This study focuses on the problem of reusing electronic health record (EHR) data for research purposes. Although EHRs offer promise for improving the database for clinical trials, their heterogeneous structure and semantics make standardisation difficult. To overcome this difficulty, the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) has gained popularity as a standard for standardising research data. However, converting EHRs to OMOP's CDM requires complex and costly processes, limiting their reuse for research. To address the heterogeneity of EHRs and the lack of semantic precision at the point of care, the openEHR standard has been widely adopted. However, a comprehensive approach to integrate openEHR records into OMOP's CDM has not been developed.

Contextualizing adverse events of special interest to characterize baseline incidence rates in 24 million COVID-19 patients across 26 databases: a multinational retrospective cohort study.

A multinational cohort study analysed the incidence of adverse events of special interest (AESI) following COVID-19 infection and compared them with historical rates in the general population. Primary care, electronic health records and insurance claims data were collected from multiple databases between January 2017 and May 2022. Sixteen pre-specified AESIs were identified, including acute myocardial infarction, anaphylaxis, stroke, thrombosis and myocarditis, among others.

Structured radiology report integrated with quantitative imaging biomarkers and qualitative scoring systems

The article presents a structured reporting system in radiology based on web templates to mitigate the limitations of traditional structured reporting. The system uses validators and logical rules to avoid reporting errors and allows for the automatic calculation of qualitative radiology values and scores. It includes quantitative imaging biomarker information and easily integrates with PACS/RIS systems. The system also supports multiple languages and has 24 structured report templates in use at 37 hospitals and healthcare institutions. A specific use case of the SR template is the prostate cancer report that includes the PI-RADS 2.1 scoring system and imaging biomarkers.

Can openEHR, ISO 13606 and HL7 FHIR work together?

Our experts David Moner Cano, Diego Boscá Tomás, and Alberto Maldonado together with Miguel Pedrera Jiménez, Noelia García Barrio, Santiago Frid, Raimundo Lozano Rubí, Dipak Kalra, Thomas Beale, Adolfo Muñoz Carrero and Pablo Serrano Balazote have analyzed the strengths and weaknesses on design, modeling capabilities, flexibility and implemented resources of three relevant standards based on Detailed Clinical Models: openEHR, ISO 13606 and HL7 FHIR to help decision making teams, non-experts in health information, to understand the heterogeneity of Electronic Health Record (EHR) standards.

Definition and validation of SNOMED CT subsets using the expression constraint language

This article describes the development of SNQuery, a platform for defining subsets of clinical concepts from the SNOMED CT terminology using the SNOMED CT Expression Constraint Language (ECL). The platform uses a graph-oriented database to represent SNOMED CT content and methods to simplify and semantically validate ECL expressions to reduce execution time. In addition, the paper presents a method to visualize subsets of the terminology to aid understanding and validation. The goal of the platform is to support the linking of clinical information models to terminologies, which is necessary to achieve semantic interoperability between medical record systems.

A platform for the design and execution of clinical data transformation and reasoning workflows.

The implementation of the conceptual framework is a web platform called CLIN-IK-LINKS, which allows users to create, modify and delete mappings and to define and execute workflows. The platform has been applied in two use cases: semantic publication of clinical laboratory test results and implementation of two colorectal cancer screening protocols.

Archetype modeling methodology

This article presents a methodology for modeling archetypes, which are a way of representing clinical information models in electronic health record (EHR) systems. The methodology consists of five phases: analysis, design, development, validation, and publication, and covers the process, participants, and tools involved in archetype design.