JMIR Medical Informatics

Electronic health records (EHRs) are central to patient-centered care. However, many current EHR systems do not represent, exchange, or reuse genomic findings in structured, interoperable, and clinically actionable forms. Instead, genomic results are often retained in static reports. This limits their use in routine clinical care and clinical decision support. It also restricts their future reinterpretation as scientific knowledge evolves, as well as their reuse for research within appropriate governance frameworks. To support precision and personalized medicine, we advocate that clinically relevant genomic findings should be represented within EHRs as structured, phenotype-linked, interoperable, and versioned data. Raw and intermediate genomic files, however, should remain in appropriately governed laboratory or genomics repositories. This viewpoint is intended for health policymakers, health informatics leaders, EHR developers, research and clinical genomics laboratories, and clinicians involved in implementing genomics into routine care. It is informed by selected published literature and relevant technical standards. It is also informed by operational experience at the Cyprus Institute of Neurology and Genetics and multidisciplinary discussions from the Gen2EHR Implementation Guidelines Workshop conducted within the Extended EHR@EU Data Space and European Health Data Space for Secondary Use @CY initiatives. We examine technical, organizational, clinical, ethical, legal, and governance challenges, including inconsistent reporting formats and unclear clinical responsibility. We propose a staged, workshop-informed implementation pathway for evaluation within the European Health Data Space. The pathway combines Health Level 7 Fast Health Interoperability Resources Genomics Reporting with complementary standards and terminologies. It also includes transitional dual PDF and structured Fast Health Interoperability Resources reporting, governance for access, version control, reinterpretation, and clinical responsibility, as well as multidisciplinary pilot validation in real diagnostic workflows. The clinical effectiveness and transferability of the proposed pathway across European health systems remain to be established.

Cross-domain chest radiograph report generation may produce formally valid reports that are nevertheless repetitive, weakly case-specific, or missing clinically relevant findings. These failures can be missed when evaluation relies on a single language-overlap or clinical-label score.

Therapeutic drug monitoring (TDM) aims to optimize clinical outcomes but is hindered by logistical delays and susceptibility to data errors. Integrating model-informed precision dosing with point-of-care testing, fortified by rule-based validation and alerts, forms a transformative clinical decision support system (CDSS) essential for securing this complex workflow.

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Health AI investment is accelerating across the Gulf Cooperation Council (GCC), yet the region’s health AI research output has never been systematically quantified. National research capacity is a structural precondition for the safe local development and governance of clinical AI, but no scientometric baseline exists for the 6 GCC states.

The development of structured optical character recognition (OCR) systems for Korean medical documents is hindered by strict privacy regulations that limit access to real clinical data. Existing synthetic document frameworks are primarily designed for generic layouts and Western languages, and fail to capture the complex formatting, bilingual terminology, and hierarchical field semantics required for clinical OCR and document-understanding tasks in hospital environments.

Summary care records are digital technologies designed to support information sharing and care coordination across fragmented health and social care systems. However, adoption and use of these technologies can vary across diverse health and care settings, with users using workarounds and other strategies to meet their specific information needs. In Scotland, the Key Information Summary (KIS) has been in use for over 13 years, sharing key patient information from general practitioners (GPs) with other health and care providers for future care planning.

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Pedigree mapping serves as the first step in genetic counseling. Traditional methods relying on manual pedigree drawing and information collection are inefficient and prone to errors.

Clinical temporal relation extraction (CTRE) is essential for reconstructing patient timelines from unstructured electronic health records (EHRs). However, the linguistic complexity of clinical notes and the high cost of expert annotation impede the development of large-scale training corpora. While large language models (LLMs) have transformed general natural language processing, their application to CTRE remains underexplored.