The objective of the DPIforINAH project is to take the INAH project to the next level by implementing a hospital EHR data extractor, based on natural language recognition, to feed the INAH data warehouse in OMOP format.
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The project aims to improve the information exchange between general practitioners and hospitals by moving from unstructured free‑text referral letters and result reports to structured, coded clinical communication.
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The project brings together three hospitals, nine residential care centres (WZCs), and the AI vendor Bingli to develop, test, and implement an AI‑based differential diagnostic triage tool tailored to geriatric care.
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Digitalisation of the care pathways for OPAT (outpatient parenteral antimicrobial therapy) and onco@home (home administration of antitumoral therapy).
This enables structured communication—covering symptoms, observations, and vital parameters—from primary care or the patient directly to the hospital.
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This project develops a central medical center for home monitoring of patients at risk of sepsis. Building on UZA’s UZA@home experience, a new transmural care pathway was created using a smartphone app and wearable devices that continuously collect health data. A specialized 24/7 Rapid Response & Telemonitoring Team (RRT²) evaluates these parameters and intervenes when needed.
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This project aimed to integrate innovative, evidence‑based digital technology into psychiatric and psychological care. By introducing blended care pathways, the project accelerated and improved screening of mental health difficulties through online psychodiagnostics, enabled systematic monitoring of treatment progress, and strengthened patient‑centred care via routine process and outcome measurement.
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The Patient‑Friendly Letter project aims to convert medical documents—such as consultation reports and discharge summaries—into language that is understandable for patients. To achieve this, Generative AI is used to reformulate complex medical information into clear, structured, and patient‑oriented text in Dutch, French, and/or English.
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Multidisciplinary introduction of smartglasses in healthcare: The added value of using smartglasses was tested across several use cases, including emergency care, complex wound care, and collaboration between hospitals and home care services. The evaluation was carried out using PREM and PROM analyses for both healthcare professionals and patients.
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ENOrtho represents Belgium's largest multi-hospital digital orthopedic care pathway implementation serving 1,400 patients across six hospitals. This initiative demonstrates that digital health can simultaneously improve clinical outcomes, enhance patient experience, reduce healthcare costs, and
scale across diverse institutional settings. ENOrtho implemented an integrated digital pathway spanning preoperative education, perioperative ERAS protocols, and post-operative remote monitoring through moveUP's cloud platform.
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This project aims to enable scalable and sustainable data reuse within the E17 hospital network by converting locally available clinical data into standardized terminologies (such as SNOMED‑CT, LOINC, ATC) and storing them in FAIR‑compliant FHIR repositories. Local data become accessible through a FHIR station, allowing federated data exchange and analytics within an emerging E17 Data Space.
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This project addresses the current fragmentation and diagnostic complexity in neurodegenerative disorders by developing a cross‑hospital, data‑driven decision support application that unifies patient information and enhances diagnostic accuracy. It builds a large multimodal dataset from several hospitals, ensures interoperability through standards such as FHIR, SNOMED‑CT and DICOM, and develops state‑of‑the‑art machine‑learning models—augmented with explainable AI—to support clinicians in differentiating disorders and identifying the usefulness of additional tests.
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TOTeM (Transmural follow-up of surgical patients through Telemonitoring) is a Data Innovation project focusing on early discharge of surgical patients combined with high‑quality remote clinical monitoring at home. The project aimed to build scalable, structured transmural care pathways that ensure safe follow‑up after surgery through digital tools, clinical dashboards, and interoperable data flows.
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Patient at Home is a Data Innovation project that aims to expand and digitalize hospital‑at‑home (HAD) care in Belgium. The project seeks to enable patients to receive high‑quality clinical follow‑up in the comfort of their own homes, while ensuring safe, coordinated and continuous care across all lines of the healthcare system.
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ERAS@HOME is a Data Innovation project focused on integrated, personalized pre and postoperative care for patients in their home environment. The project builds on the international Enhanced Recovery After Surgery (ERAS) model, which aims to achieve faster, safer, and better recovery through a multimodal perioperative care pathway.
Updated 2026-02-02 10:46:22 +01:00