282 FHIR-related articles (latest first)
The Ministry of Health and Welfare (MOHW) announced the successful construction of an 'Inter-Hospital FHIR Data Platform' and held a presentation to showcase its results. This system aims to significantly enhance electronic health record data exchange capabilities by converting original medical records into the internationally standardized FHIR format.
Hon Hai (2317) and Industrial Research Institute (ITRI), through the 'HiMEDt' alliance, showcased advancements at a major medical tech expo in Taiwan. Key announcements included clinical results for the nursing robot 'Nurabot,' alongside next-generation HIS systems utilizing FHIR standards and advanced telemedicine solutions.
ๆๅคง็ ้ขใฏใๅ้จใฎๅฏไธใฎใAIๅฝฑ้ฟๆง็ ็ฉถไธญๅฟใใจใใฆใๅฉฆ็็ปๅใจๅ็้ใซ้ขใใๅๆนๅใฎ็ ็ฉถๆๆใๆ็คบใใใใใใฏใAIๆ่กใๆดป็จใใ่จๅบใใๅฅไฟๅถๅบฆใธใฎไพกๅคๅต้ ใ็ฎๆใๅใ็ตใฟใฎไธ็ฐใงใใใ
The National Health Insurance Administration (NHIA) held a 'Cancer Treatment Digital Governance Seminar' as part of the 'Healthy Taiwan' initiative, aiming to improve quality and digitize cancer care in Taiwan. The effort involves implementing the international standard FHIR format to streamline drug review and enable early access to medication for patients.
At the '2025 Taiwan Medical Technology Exhibition,' Farun will showcase a new era of smart healthcare using AI and 5G. By integrating telemedicine, Cloud HIS, FHIR data exchange, etc., it aims to achieve comprehensive care for all age groups, from acute care to elderly long-term care.
The Director of the National Health Insurance announced at a 'Digital Governance for Cancer Treatment' seminar that using FHIR format for pre-screening cancer drugs can significantly shorten the process, reducing the typical 1โ2 week wait time to as little as one day. This is expected to allow patients faster access to necessary medications.
According to the Director of the National Health Insurance, implementing the international standard FHIR format has drastically reduced the pre-screening time for cancer drugs from 1โ2 weeks to just one day. This is expected to allow patients to access necessary medications much faster.
CCMUH was selected as one of the 'Taiwan AI Impact Research Centers,' aiming to contribute to the southern AI ecosystem and national health insurance system. The hospital presented empirical results, ranging from breast cancer imaging to chemotherapy dosage adjustment, accelerating smart healthcare initiatives.
The National Health Insurance Administration (NHIA) is promoting 'cancer digital governance,' transitioning the pre-approval process for anti-cancer drugs from paper-based to digital starting this year. This change significantly reduces the drug waiting period from a typical 7โ14 days to just one day.
The National Health Insurance Administration (NHIA) announced progress in digital governance for cancer treatment, focusing on three areas: information integration, connecting holistic care processes, and data interoperability. Efforts include adopting the FHIR standard and building large databases to improve data exchange and quality.
The National Health Insurance Administration (NHIA) held a 'Digital Governance Seminar on Cancer Treatment.' According to Director Chen Liang-yu, the pre-approval review time for cancer drugs, which previously took 1โ2 weeks, can now be significantly reduced to just one day through the adoption of FHIR format. This allows patients to start drug treatment much sooner.
The Director of the National Health Insurance Administration announced that digital transformation in cancer treatment has progressed, introducing the international standard FHIR format for drug pre-screening. This is expected to reduce the drug approval process time from previously 1โ2 weeks to just one day at participating facilities.
ๆ็็ทๅ็ ้ขใฏใ่ก็็ฆๅฉ้จไธปๅฐใฎใๅฅๅบทๅฐๆนพๆทฑ่่จ็ซใใฎไธ็ฐใจใใฆใใๆ็ๅท่กไธญๅฟใใ้่จญใใใใใใซใใใAIๆ่กใใใธใฟใซๅใๅฐๅ ฅใใๆบๆ งๅป็ใจๅฐๅ้ฃๆบใซใใๅ ๆฌ็ใชๅฅๅบท็ฎก็ไฝๅถใๆง็ฏใใใ
This course is designed for CMIO students in medical informatics. It aims to help participants distinguish between syntactic and semantic interoperability at the data level. Key topics include FHIR resources, RESTful APIs, and how SNOMED CT provides computable meaning.
The Ministry of Health (MOH) launched the 'Taiwan Smart Healthcare School' to train specialized talent capable of leading hospital digital transformation. The program aims to cultivate Clinical Medical Information Officers (CMIOs), who possess both clinical knowledge and IT expertise.
Qualys SSL Labs conducted an SSL security test on a specific FHIR-related server (hapi.fhir.tw). The report shows multiple IP addresses with statuses like 'In progress' or 'Pending,' indicating that the detailed security evaluation results are not yet finalized.
The Ministry of Health and Welfare (MOHW) in Taiwan announced plans, as part of the 'Taiwan Medical Information Standard Platform,' to integrate electronic medical records across major hospitals nationwide within two years. This initiative aims to standardize medical information and improve accessibility.
On October 24th, Biomedica successfully passed two international interoperability testsโDICOM SWF and FHIR MHDโat the Asia-Pacific IHE Connectathon 2025 held in Tokyo. This demonstrates the company's system integration capability and adherence to international standards, showing that Taiwan is highly advanced in AI medical imaging and smart healthcare information interoperability.
The Ministry of Health and Welfare's Information Department announced that to solidify Taiwan's smart healthcare foundation, it has set three key governance priorities: Data Governance, AI Governance, and Cybersecurity Governance. This includes ensuring data interoperability through the adoption of international standards like FHIR and SNOMED CT, and establishing frameworks for responsible AI implementation and management.
The New National Hospital of Taipei Medical University implemented the 'CKM Glyco-Renal-Cardio Integrated Care System,' achieving results like improved blood sugar control. However, it highlights that systemic issuesโsuch as insurance coverage remaining focused on 'single disease/single department' and unclear AI responsibilityโare the true challenges.