Interoperability Standards Research Articles

Open Ecosystem Through Secure Plug and Play Interoperability: An Overview.

Interoperability is a critical enabler for integrated Personalized Diabetes Management (iPDM), automated insulin delivery (AID), and the digital transformation of healthcare in general. However, manufacturers still create closed ecosystems (ie, solutions designed to work end-to-end minimizing collaboration with other organizations) with proprietary interfaces because of various interoperability challenges. Therefore, the aim of this article is to provide an overview of how to achieve organizational interoperability in an open ecosystem (ie, solutions designed to integrate different organizations via interoperability standards) for diabetes management. The proposed interoperability design approach called Secure Plug and Play Interoperability (SPPI) supports building and using interoperable system elements in an open ecosystem. Secure Plug and Play Interoperability enables interoperability over the entire system life cycle with its reference architecture, secure interoperability standards, and organizational capabilities. These standards were developed with participation from healthcare providers, regulatory authorities, payers, academia, and manufacturers. Publicly available information provides examples of implementation support and practical usage. Organizational interoperability in an open ecosystem can be achieved through organizational capabilities and a selection of secure interoperability standards. ISO/IEEE 11073, Bluetooth profiles, and HL7 FHIR with test specifications, test tools, software development kits, and quality assurance programs represent a coordinated selection suitable for building an open ecosystem. Practical usage is demonstrated with real-world solutions that build on these standards. Secure Plug and Play Interoperability facilitates the end-to-end integration of devices, digital products, and services from partners in an open ecosystem. Moreover, even a single manufacturer, who provides all system elements of a solution, can use and benefit from SPPI.

ENABLING DATA PORTABILITY AND INTEROPERABILITY UNDER INDONESIA'S DATA PROTECTION LAW

The Indonesian parliament ratified the Personal Data Protection (PDP) Law in October 2022, introducing the Right to Data Portability (RtDP) in Article 13. This concept enables seamless information transfer, enhances personal control, and fosters innovation in the digital economy. This study analyzed data portability provisions under the PDP Law and drew insights from the EU and UK's experiences. Findings showed that data portability under the PDP Law, similar to the GDPR, fell short due to the absence of standardized guidelines, interoperability architectures, and non-mandatory compatibility policies. Prioritizing Open APIs for interoperability was crucial. Effective public-private collaboration was key in establishing sector-specific and cross-sector interoperability standards aligned with PDP Law regulations

EyeMatics: An Ophthalmology Use Case Within the German Medical Informatics Initiative.

The EyeMatics project, embedded as a clinical use case in Germany's Medical Informatics Initiative, is a large digital health initiative in ophthalmology. The objective is to improve the understanding of the treatment effects of intravitreal injections, the most frequent procedure to treat eye diseases. To achieve this, valuable patient data will be meaningfully integrated and visualized from different IT systems and hospital sites. EyeMatics emphasizes a governance framework that actively involves patient representatives, strictly implements interoperability standards, and employs artificial intelligence methods to extract biomarkers from tabular and clinical data as well as raw retinal scans. In this perspective paper, we delineate the strategies for user-centered implementation and health care-based evaluation in a multisite observational technology study.

Lunar distress communications: Interoperability, frequencies, and harmful interference, which normative model for the artemis accords?

A new space era begins with the Artemis Accords. These will allow the return of humans to the Moon. The starting point of this historic period was marked by the signing of this international agreement on October 13, 2020. Eight States are at the origin of these accords: the United States of America, Australia, Canada, Italy, Japan, Luxembourg, the United Arab Emirates, and the United Kingdom. Since then, thirteen other governments – including France – have joined this international space program led by NASA. Artemis will require the implementation of a new communication architecture called “LunaNet”, encompassing the search and rescue service known as “LunaSAR”. Therefore, like on Earth, on the Moon, search and rescue of people in distress will require the interoperability of international communications. From a legal point of view, the Artemis Accords are based on existing space law, particularly the 1967 Outer Space Treaty. According to this, Lunar missions shall be conducted for peaceful purposes. Transparency in the implementation of international partnerships is another key principle of this space program. From this, at the operational level, interoperability of the systems based on existing or future standards naturally follows. Beyond the technical or commercial aspects, what takes precedence over all other considerations is the safety of the astronauts working for the completion of the Artemis program. Thus, generally, the possible assistance brought to the astronauts in distress is foreseen in the United Nations treaties and principles on outer space. Regarding the implementation of the Artemis program, personnel will operate on board a spacecraft, a space station, or from the surface of the Moon. This is why NASA plans to implement the Astronaut's Lunar Lifeline, known as Lunar Search and Rescue or LunaSAR. Integrated with the LunaNet system, this system will assist workers in distress. In this study, therefore, we will focus on standards for communications interoperability, in the context of search and rescue of persons in distress. To do so, we will examine the Artemis program through the lens of satellite-assisted Earth search and rescue principles and techniques. In particular, we will focus on the COSPAS-SARSAT alerting service and the International Aeronautical and Maritime Search and Rescue (IAMSAR) Manual. In this context, issues such as, for example, the implementation of the Treaty on Principles Governing the Activities of States in the Exploration and Use of Outer Space, including the Moon and Other Celestial Bodies of 1967, the Agreement on the Rescue of Astronauts, the Return of Astronauts and the Return of Objects Launched into Outer Space of 1968 and the Agreement Governing the Activities of States on the Moon and Other Celestial Bodies of 1979 as well as the protection of SAR frequencies and potential harmful interference will be addressed.

Vaccine Certificates Must Go Digital: An Urgent Call for Better Public Health Outcomes.

From our roles within international public health organizations, we have collectively witnessed the global challenges presented by outdated health information systems, platforms, and applications. The COVID-19 pandemic has clearly exposed the limitations of our current paper-based vaccine certification methods and highlighted the deficiencies of outdated technological platforms that lack interoperability standards, a situation that underscores the critical need for a digital transformation in how we manage and verify immunization records. Digital vaccination certificates are understood to be secure, electronically stored, and easily accessible records that provide verifiable proof of a person's immunization status. The Pan American Health Organization (PAHO) envisions leveraging digital technologies to strengthen health systems, enhance data-driven decision-making, and improve health outcomes. The organization's vision emphasizes the integration of innovative technologies to build resilient and responsive health systems capable of addressing modern public health challenges. In an era of unprecedented technological advancement, our continued reliance on paper-based vaccine certificates is not just anachronistic-it is a significant liability for global public health that impacts the efficiency and effectiveness of our health systems on multiple fronts, limiting our ability to respond to public health crises effectively. With the strategic guidance from its Member States, PAHO has agreed to move toward the digital transformation of the health sector across the entire continent with an initiative that aims to improve health outcomes, ensure equitable access to health services, and enhance the overall efficiency of health systems in the Americas. The roadmap for this digital transformation outlines strategic actions and goals to achieve a connected, efficient, and resilient health sector.

Assessing the Digital Advancement of Public Health Systems Using Indicators Published in Gray Literature: Narrative Review.

Revealing the full potential of digital public health (DiPH) systems requires a wide-ranging tool to assess their maturity and readiness for emerging technologies. Although a variety of indices exist to assess digital health systems, questions arise about the inclusion of indicators of information and communications technology maturity and readiness, digital (health) literacy, and interest in DiPH tools by the society and workforce, as well as the maturity of the legal framework and the readiness of digitalized health systems. Existing tools frequently target one of these domains while overlooking the others. In addition, no review has yet holistically investigated the available national DiPH system maturity and readiness indicators using a multidisciplinary lens. We used a narrative review to map the landscape of DiPH system maturity and readiness indicators published in the gray literature. As original indicators were not published in scientific databases, we applied predefined search strings to the DuckDuckGo and Google search engines for 11 countries from all continents that had reached level 4 of 5 in the latest Global Digital Health Monitor evaluation. In addition, we searched the literature published by 19 international organizations for maturity and readiness indicators concerning DiPH. Of the 1484 identified references, 137 were included, and they yielded 15,806 indicators. We deemed 286 indicators from 90 references relevant for DiPH system maturity and readiness assessments. The majority of these indicators (133/286, 46.5%) had legal relevance (targeting big data and artificial intelligence regulation, cybersecurity, national DiPH strategies, or health data governance), and the smallest number of indicators (37/286, 12.9%) were related to social domains (focusing on internet use and access, digital literacy and digital health literacy, or the use of DiPH tools, smartphones, and computers). Another 14.3% (41/286) of indicators analyzed the information and communications technology infrastructure (such as workforce, electricity, internet, and smartphone availability or interoperability standards). The remaining 26.2% (75/286) of indicators described the degree to which DiPH was applied (including health data architecture, storage, and access; the implementation of DiPH interventions; or the existence of interventions promoting health literacy and digital inclusion). Our work is the first to conduct a multidisciplinary analysis of the gray literature on DiPH maturity and readiness assessments. Although new methods for systematically researching gray literature are needed, our study holds the potential to develop more comprehensive tools for DiPH system assessments. We contributed toward a more holistic understanding of DiPH. Further examination is required to analyze the suitability and applicability of all identified indicators in diverse health care settings. By developing a standardized method to assess DiPH system maturity and readiness, we aim to foster informed decision-making among health care planners and practitioners to improve resource distribution and continue to drive innovation in health care delivery.

Electronic health records and data exchange in the WHO European region: A subregional analysis of achievements, challenges, and prospects

Electronic health record (EHR) systems are powerful tools that enhance healthcare quality. They improve efficiency, enable data exchange, and ensure authorized access to patient information. In 2022, the World Health Organization Regional Office for Europe (WHO EURO) conducted a survey to assess the digital health capabilities of the 53 Member States. This article provides a sub-regional analysis of the status of EHR systems and major barriers to their implementation, their readiness for information sharing, and the access and re-use of EHR data.Generally, EHR implementation and national data exchange are at an advanced stage in the region, though achievements and challenges vary across subregions. While more Member States in the Eastern, Western, and Southern Europe subregions reported having centralized national EHR systems, the situation is more diverse in Northern Europe and the Asian subregions, where both centralized and decentralized EHR systems are in use. Significant barriers to EHR implementation, including funding, technical capacity, competing priorities, and lack of interoperability standards are frequently cited, while others like demand, knowledge or acceptance challenges are not reported as significant. Significant barriers were reported the most by the Central Asia subregion, while barriers had least significance in Western Europe. Five out of the six subregions reported a wide adoption of national strategies and have dedicated agencies to ensure interoperability and secure data exchange. However, only 29 Member States have established legal requirements for healthcare providers to adopt EHR systems that conform to national standards for both clinical terminology and electronic messaging, with this being most notable in Western, Eastern, and Northern Europe, and the lowest percentage of Member States in Central Asia. All Member States of the six sub regions have passed privacy and data protection legislation. The use of EHR data is widely regulated, with only five remaining Member States of WHO Europe to develop EHR legislation distributed across subregions (Southern Europe, Western and Central Asia).Looking ahead, Member States are encouraged to define national legislation governing EHR systems and their use, while ensuring the interconnectivity of the local and regional EHR systems. Sustainable funding should be allocated to the development and maintenance of these systems. Efforts should also focus on creating comprehensive roadmaps for the full implementation of health data standards, addressing interoperability at local and regional levels, and developing quality management systems for testing and certification. Additionally, monitoring and evaluation should be conducted to assess whether EHRs are contributing to national health objectives. Finally, engaging patients and intersectoral partners will be key to developing a more patient-centered approach, ensuring that EHR systems meet patient needs and expectations.

Enhancing data standards to advance translation in spinal cord injury

Data standards are available for spinal cord injury (SCI). The International SCI Data Sets were created in 2002 and there are currently 27 freely available. In 2014 the National Institute of Neurological Disorders and Stroke developed clinical common data elements to promote clinical data sharing in SCI. The objective of this paper is to provide an overview of SCI data standards, describe learnings from the traumatic brain injury (TBI) field using data to enhance research and care, and discuss future opportunities in SCI. Given the complexity of SCI, frameworks such as a systems medicine approach and Big Data perspective have been advanced. Implementation of these frameworks require multi-modal data and a shift towards open science and principles such as requiring data to be FAIR (Findable, Accessible, Interoperable and Reusable). Advanced analytics such as artificial intelligence require data to be interoperable so data can be exchanged among different technology systems and software applications. The TBI field has multiple ongoing initiatives to promote sharing and data reuse for both pre-clinical and clinical studies, which is an opportunity for the SCI field given these injuries can often occur concomitantly. The adoption of interoperable standards, data sharing, open science, and the use of advanced analytics in SCI is needed to facilitate translation in research and care. It is critical that people with lived experience are engaged to ensure data are relevant and enhances quality of life.

A new AI-assisted data standard accelerates interoperability in biomedical research.

In this paper, we leveraged Large Language Models(LLMs) to accelerate data wrangling and automate labor-intensive aspects of data discovery and harmonization. This work promotes interoperability standards and enhances data discovery, facilitating AI-readiness in biomedical science with the generation of Common Data Elements (CDEs) as key to harmonizing multiple datasets. Thirty-one studies, various ontologies, and medical coding systems served as source material to create CDEs from which available metadata and context was sent as an API request to 4th-generation OpenAI GPT models to populate each metadata field. A human-in-the-loop (HITL) approach was used to assess quality and accuracy of the generated CDEs. To regulate CDE generation, we employed ElasticSearch and HITL to avoid duplicate CDEs and instead, added them as potential aliases for existing CDEs. The generated CDEs are foundational to assess the interoperability potential of datasets by determining how many data set column headers can be correctly mapped to CDEs as well as quantifying compliance with permissible values and data types. Subject matter experts reviewed generated CDEs and determined that 94.0% of generated metadata fields did not require manual revisions. Data tables from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Global Parkinson's Genetic Program (GP2) were used as test cases for interoperability assessments. Column headers from all test cases were successfully mapped to generated CDEs at a rate of 32.4% via elastic search.The interoperability score, a metric for dataset compatibility to CDEs and other connected datasets, based on relevant criteria such as data field completeness and compliance with common harmonization standards averaged 53.8 out of 100 for test cases. With this project, we aim to automate the most tedious aspects of data harmonization, enhancing efficiency and scalability in biomedical research while decreasing activation energy for federated research.

Digitalisation level, strategies and interoperable standards in the nursing care sector in Germany and in international contexts: a study protocol for a systematic review

IntroductionThe nursing care sector faces significant challenges due to an ageing population and a concurrent increase in demand for care services. Digitalisation can be one way of overcoming these challenges...

The status of health information systems and digital transformation in the European Region

Abstract Although there have been investments in health information systems (HIS) and digitalization, WHO/Europe’s work with Member States (MS) shows that much can be improved still. Typically, there is a strong focus on data collection, but less on analysis and knowledge translation, resulting in available data not being optimally used to support decision making. Standards for data exchange and interoperability have not yet been fully implemented. Efforts are underway to train healthcare professionals, yet only half of MS have developed policies for digital health literacy. Fewer still have implemented a comprehensive digital inclusion plan, leaving disadvantaged populations at risk of falling behind. In line with the traditionally strong focus on HIS strengthening in WHO’s work, the European Programme of Work 2020-2025 (EPW) emphasises the need for MS to improve and modernise their HIS to ensure that decisions are data driven. One of the EPW flagship initiatives is Empowerment through Digital Health, promoting the leveraging and scaling up of digital transformation for better health. The Regional digital health action plan for the WHO European Region 2023-2030 outlines the strategic actions needed to achieve this, while fully respecting the values of equity, solidarity and human rights. Collaboration with MS and international partners is vital in this work. WHO/Europe has established several MS-driven health information networks in the past, most notably the European Health Information Initiative (the EHII). The EHII in 2023 has made a restart in the form of the European Health Information Network (HIN). The HIN will guide the work under the EU-funded action ‘Supporting Member States in the WHO European Region in strengthening health information systems and boosting health data governance’, which will be implemented by WHO/Europe. This strong European Commission and WHO/Europe partnership will be a main catalyst for HIS improvement in the Region the coming years.

Implementation Challenges of Building Information Modelling (BIM) in Small to Medium-Sized Enterprises (SMEs) Participating in Public Projects in Qatar

This research investigates the implementation challenges of Building Information Modelling (BIM) in Small to Medium-Sized Enterprises (SMEs) participating in public projects, with a focus on the construction industry in Qatar. Through a combination of literature review, surveys, and interviews, the study identifies key obstacles such as interoperability issues, financial constraints, organisational and cultural resistance, and the lack of comprehensive training programs. The literature highlights the fragmented nature of construction projects and the potential of BIM to improve efficiency through enhanced data handling and collaboration. However, SMEs often struggle with the high initial costs of software and hardware, as well as the need for extensive training to bridge the skill gap. Interviews with industry professionals reveal that while mandatory BIM integration in public projects drives adoption, it also exacerbates these challenges for SMEs, which may lack the necessary resources and expertise. Survey findings indicate that contractors frequently encounter issues with understanding and implementing BIM and meeting the government body standards, suggesting a need for better training and support. The study also emphasises the importance of strategic incremental adoption, where SMEs gradually integrate BIM into their processes, starting with low-level implementation in privately funded projects. The research concludes that while BIM offers significant benefits for the construction industry, its successful adoption requires targeted support for SMEs. This includes financial incentives, improved interoperability standards, comprehensive training programs, and strategic change management approaches. Addressing these challenges will enable SMEs to fully leverage BIM's potential, enhancing project efficiency and competitiveness in the construction sector.

Standards for Data Space Building Blocks

Data spaces are conceptualised as a trusted and secure distributed data ecosystem through which to exchange resources in the Web. Several efforts define guidance toward data space implementation, such as reference architectures and frameworks. As yet, the proposed data space solutions do not provide common and mature implementation options yet, and this gap between concept and implementation risks confusing users and developers. However, well-recognised organisations have been developing solutions and standards that address interoperability and good data exchange practices for decades, especially in the domain of geospatial information and remote sensing. Therefore, this paper compares the available solutions, providing the mapping and integration of the proposed blueprints to available interoperable standards. This concrete mapping, followed by a discussion with experts, results in a proposal of integrated reference data space building blocks, and an overview of the related standards and solutions. It is designed to support the effective practical implementation of data spaces and to guide future solution developments. This work can form the base for effective collaboration among different organisations, clearly identifying their scopes. A key role is apparent for standards and use cases from the remote sensing and geospatial domains, which have achieved wide adoption and maturity over the past years.

DATA SECURITY IN IOT DEVICES AND SENSOR NETWORKS FOR ROBUST THREAT DETECTION AND PRIVACY PROTECTION

The rapid proliferation of Internet of Things (IoT) devices and sensor networks has revolutionized various industries by enhancing automation, connectivity, and operational efficiency. However, these advancements have also introduced significant security challenges due to the resource constraints and decentralized nature of IoT environments. This paper provides a systematic review of IoT security solutions, focusing on encryption techniques, authentication protocols, and machine learning-based anomaly detection methods. A total of 55 peer-reviewed articles were analyzed following the PRISMA guidelines. The findings reveal that while lightweight cryptographic algorithms, such as elliptic curve cryptography (ECC), offer robust security with low energy consumption, scalability across large IoT networks remains a challenge. Blockchain-based authentication has emerged as a promising decentralized solution, but issues related to energy consumption and latency hinder its widespread adoption. Machine learning techniques have shown high accuracy in detecting threats in real-time, but their resource-intensive nature limits their application in low-power IoT devices. This review underscores the need for multi-layered, integrated security frameworks and highlights gaps in research on quantum-resistant cryptography and interoperable security standards. Future research must focus on developing scalable, energy-efficient security solutions to ensure data integrity and privacy in expanding IoT ecosystems.

Informatics and Artificial Intelligence-Guided Assessment of the Regulatory and Translational Research Landscape of First-in-Class Oncology Drugs in the United States, 2018-2022.

Cancer drug development remains a critical but challenging process that affects millions of patients and their families. Using biomedical informatics and artificial intelligence (AI) approaches, we assessed the regulatory and translational research landscape defining successful first-in-class drugs for patients with cancer. This is a retrospective observational study of all novel first-in-class drugs approved by the US Food and Drug Administration (FDA) from 2018 to 2022, stratified by cancer versus noncancer drugs. A biomedical informatics pipeline leveraging interoperability standards and ChatGPT performed integration and analysis of public databases provided by the FDA, National Institutes of Health, and WHO. Between 2018 and 2022, the FDA approved a total of 247 novel drugs, of which 107 (43.3%) were first-in-class drugs involving a new biologic target. Of these first-in-class drugs, 30 (28%) treatments were indicated for patients with cancer, including 19 (63.3%) for solid tumors and the remaining 11 (36.7%) for hematologic cancers. A median of 68 publications of basic, clinical, and other relevant translational science preceded successful FDA approval of first-in-class cancer drugs, with oncology-related treatments involving fewer median years of target-based research than therapies not related to cancer (33 v 43 years; P < .05). Overall, 94.4% of first-in-class drugs had at least 25 years of target-related research papers, while 85.5% of first-in-class drugs had at least 10 years of translational research publications. Novel first-in-class cancer treatments are defined by diverse clinical indications, personalized molecular targets, dependence on expedited regulatory pathways, and translational research metrics reflecting this complex landscape. Biomedical informatics and AI provide scalable, data-driven ways to assess and even address important challenges in the drug development pipeline.

A robust algorithm for authenticated health data access via blockchain and cloud computing.

In modern healthcare, providers increasingly use cloud services to store and share electronic medical records. However, traditional cloud hosting, which depends on intermediaries, poses risks to privacy and security, including inadequate control over access, data auditing, and tracking data origins. Additionally, current schemes face significant limitations such as scalability concerns, high computational overhead, practical implementation challenges, and issues with interoperability and data standardization. Unauthorized data access by cloud providers further exacerbates these concerns. Blockchain technology, known for its secure and decentralized nature, offers a solution by enabling secure data auditing in sharing systems. This research integrates blockchain into healthcare for efficient record management. We proposed a blockchain-based method for secure EHR management and integrated Ciphertext-Policy Attribute-Based Encryption (CP-ABE) for fine-grained access control. The proposed algorithm combines blockchain and smart contracts with a cloud-based healthcare Service Management System (SMS) to ensure secure and accessible EHRs. Smart contracts automate key management, encryption, and decryption processes, enhancing data security and integrity. The blockchain ledger authenticates data transactions, while the cloud provides scalability. The SMS manages access requests, enhancing resource allocation and response times. A dual authentication system confirms patient keys before granting data access, with failed attempts leading to access revocation and incident logging. Our analyses show that this algorithm significantly improves the security and efficiency of health data exchanges. By combining blockchain's decentralized structure with the cloud's scalability, this approach significantly improves EHR security protocols in modern healthcare setting.

Abstract A138: Decreasing disparities in inherited cancer syndrome identification through a systems approach, The At-Risk Cancer Genetic Syndrome Identification (ARCAGEN-ID) system

Abstract Three percent of cancers are due to inherited cancer-predisposing syndromes, the most common ones being Hereditary Breast and Ovarian cancer syndrome and Lynch syndrome. Surveillance and preventive measures among diagnosed individuals lead to early detection, prevention of future cancers, and appropriate treatment modalities ultimately resulting in lower cancer mortality. Thus, identifying these individuals through genetic testing is of most importance. While guidelines have been drafted to identify people who need to be ruled out based on personal and family history of cancer, less than 30% of qualifying individuals are currently tested and these numbers are much worse among underserved communities. Lack of awareness, largely due to guideline complexity, has been documented as a critical factor for the low testing rates while clinician’s unconscious bias contributes to disparities. The objective of this project was to increase the identification of individuals at risk, especially among the underserved groups. We hypothesized that this could be accomplished by establishing a mechanism of automatic identification of candidates leveraging the electronic health records (EHR), the ARCAGEN-ID (At-Risk Cancer Genetic Syndrome Identification) system. Methods: An inclusion logic was designed based on 218 rules that evaluate personal and family history of specific cancers and age at diagnosis, relevant to NCCN/ACMG guidelines for genetic testing. Structured data was pulled from discrete fields in the EHR. External data was accessed by enabling the standard interoperability exchange of information system. The system was applied to the wellness registry, a cohort of 1,357,337 patients with an active EHR in our healthcare system. Results: The ARCAGEN-ID system identified 57,628 individuals at-risk (4.25%). Of those, 45,646 (79.2%) had no evidence of prior genetic test, cancer genetics evaluation, or referral. A manual chart review of 559 cases showed an identification accuracy rate of 96.2%. The ARCAGEN-ID identified a lower proportion of self-reported African Americans, Hispanics and Medicaid insured patients than the overall wellness registry (likely reflecting less complete relevant information in the EHR). However, patients in those categories were significantly overrepresented among the ones who were not previously referred for genetic testing. Thus, ARCAGEN-ID significantly increased the identification of individuals from minority groups by 12.7 to 23% in each category. Regarding criteria for inclusion, individuals identified only through ARCAGEN-ID were more likely identified because of family history of cancer only, representing 80.69%. In conclusion, a fully automated system that leverages the EHR was able to multiply by 5 the number of individuals who need to be ruled out for an inherited cancer syndrome while addressing the bias against underserved communities seen under current routine care. Citation Format: Rosa Munoz Xicola, Vinit Singh, Thomas Rafter, Jing Liu, Quiana Brown, Nitu Kashyap, Xavier Llor. Decreasing disparities in inherited cancer syndrome identification through a systems approach, The At-Risk Cancer Genetic Syndrome Identification (ARCAGEN-ID) system [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A138.

PCEtoFHIR: Decomposition of Postcoordinated SNOMED CT Expressions for Storage as HL7 FHIR Resources.

To ensure interoperability, both structural and semantic standards must be followed. For exchanging medical data between information systems, the structural standard FHIR (Fast Healthcare Interoperability Resources) has recently gained popularity. Regarding semantic interoperability, the reference terminology SNOMED Clinical Terms (SNOMED CT), as a semantic standard, allows for postcoordination, offering advantages over many other vocabularies. These postcoordinated expressions (PCEs) make SNOMED CT an expressive and flexible interlingua, allowing for precise coding of medical facts. However, this comes at the cost of increased complexity, as well as challenges in storage and processing. Additionally, the boundary between semantic (terminology) and structural (information model) standards becomes blurred, leading to what is known as the TermInfo problem. Although often viewed critically, the TermInfo overlap can also be explored for its potential benefits, such as enabling flexible transformation of parts of PCEs. In this paper, an alternative solution for storing PCEs is presented, which involves combining them with the FHIR data model. Ultimately, all components of a PCE should be expressible solely through precoordinated concepts that are linked to the appropriate elements of the information model. The approach involves storing PCEs decomposed into their components in alignment with FHIR resources. By utilizing the Web Ontology Language (OWL) to generate an OWL ClassExpression, and combining it with an external reasoner and semantic similarity measures, a precoordinated SNOMED CT concept that most accurately describes the PCE is identified as a Superconcept. In addition, the nonmatching attribute relationships between the Superconcept and the PCE are identified as the "Delta." Once SNOMED CT attributes are manually mapped to FHIR elements, FHIRPath expressions can be defined for both the Superconcept and the Delta, allowing the identified precoordinated codes to be stored within FHIR resources. A web application called PCEtoFHIR was developed to implement this approach. In a validation process with 600 randomly selected precoordinated concepts, the formal correctness of the generated OWL ClassExpressions was verified. Additionally, 33 PCEs were used for two separate validation tests. Based on these validations, it was demonstrated that a previously proposed semantic similarity calculation is suitable for determining the Superconcept. Additionally, the 33 PCEs were used to confirm the correct functioning of the entire approach. Furthermore, the FHIR StructureMaps were reviewed and deemed meaningful by FHIR experts. PCEtoFHIR offers services to decompose PCEs for storage within FHIR resources. When creating structure mappings for specific subdomains of SNOMED CT concepts (eg, allergies) to desired FHIR profiles, the use of SNOMED CT Expression Templates has proven highly effective. Domain experts can create templates with appropriate mappings, which can then be easily reused in a constrained manner by end users.

2024 HRS perspective on advancing workflows for CIED remote monitoring

Cardiac implantable electronic devices (CIEDs) generate substantial data, often stored in image or PDF formats. Remote monitoring, now an integral component of patient care, places considerable administrative burdens on clinicians and staff, in large part due to the challenge of integrating these data seamlessly into electronic health records (EHRs). Since 2006, the Heart Rhythm Society, in collaboration with the CIED industry, has led an initiative to establish a unified standard nomenclature. This effort has harmonized terminology, aligning diverse terms with single terms approved by the Institute of Electrical and Electronics Engineers. With this foundational work complete, attention now turns to developing technical standards for interoperability, which would enable the smooth communication of CIED data between information technology systems used in clinical practice. In this manuscript, by leveraging Health Level 7 Fast Healthcare Interoperability Resources, we present a roadmap for the technical committee to guide this endeavor. We identify critical data exchange points between remote transceivers, EHRs, and third-party platforms commonly used for CIED patient data management. Our objective is to establish bidirectional communication among these resources, ensuring the accuracy, timeliness, and accessibility of clinical data for clinicians. We also anticipate substantial benefits for both clinical research and administrative efficiency through the implementation of this interoperability framework.

Validation of an acute respiratory infection phenotyping algorithm to support robust computerised medical record-based respiratory sentinel surveillance, England, 2023.

IntroductionRespiratory sentinel surveillance systems leveraging computerised medical records (CMR) use phenotyping algorithms to identify cases of interest, such as acute respiratory infection (ARI). The Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC) is the English primary care-based sentinel surveillance network.AimThis study describes and validates the RSC's new ARI phenotyping algorithm.MethodsWe developed the phenotyping algorithm using a framework aligned with international interoperability standards. We validated our algorithm by comparing ARI events identified during the 2022/23 influenza season in England through use of both old and new algorithms. We compared clinical codes commonly used for recording ARI.ResultsThe new algorithm identified an additional 860,039 cases and excluded 52,258, resulting in a net increase of 807,781 cases (33.84%) of ARI compared to the old algorithm, with totals of 3,194,224 cases versus 2,386,443 cases. Of the 860,039 newly identified cases, the majority (63.7%) were due to identification of symptom codes suggestive of an ARI diagnosis not detected by the old algorithm. The 52,258 cases incorrectly identified by the old algorithm were due to inadvertent identification of chronic, recurrent, non-infectious and other non-ARI disease.ConclusionWe developed a new ARI phenotyping algorithm that more accurately identifies cases of ARI from the CMR. This will benefit public health by providing more accurate surveillance reports to public health authorities. This new algorithm can serve as a blueprint for other CMR-based surveillance systems wishing to develop similar phenotyping algorithms.