ACHEGAMED is an unsupervised real-time patient monitoring system, with the goal of decreasing the exam and diagnosis time of the most prevalent diseases in today's healthcare services. We developed, as a component of ACHEGAMED, a system for storing a wide range of biomedical parameters as ISO 13606 extracts. The system is able to detect clinical alarms in those parameters and communicate them, if needed, to the appropriate medical staff. Although a component of ACHEGAMED, it can be integrated in other systems in a semantic interoperable way thanks to the ISO 13606 standard, allowing the continuity of patient care.
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Life (Basel)
September 2024
Department of Internal Medicine, Bellvitge University Hospital, Hospitalet de Llobregat, 08907 Barcelona, Spain.
This study aims to develop and apply multistate models to estimate, forecast, and manage hospital length of stay during the COVID-19 epidemic without using any external packages. Data from Bellvitge University Hospital in Barcelona, Spain, were analyzed, involving 2285 hospitalized COVID-19 patients with moderate to severe conditions. The implemented multistate model includes transition probabilities and risk rates calculated from transitions between defined states, such as admission, ICU transfer, discharge, and death.
View Article and Find Full Text PDFInt J Med Inform
November 2024
CRS4: Center for Advanced Studies, Research and Development in Sardinia, Pula, Italy.
Stud Health Technol Inform
August 2024
Norwegian Centre for E-health Research, Tromsø, Norway.
The Valkyrie project aims to develop a demonstration Federated Electronic Health Record for the use of mental health practitioners in Norway. Information for the record is drawn from existing records in Source Systems operating across primary and secondary care. Recording of information in any such system, in response to a healthcare event, triggers the generation of an Encrypted Token, containing summary metadata about the event, clinical coding indicating its clinical context and a locator that can be used to retrieve the full record of the event from the original Source System.
View Article and Find Full Text PDFStud Health Technol Inform
January 2024
This paper describes the implementation of tools to support multiple language variants of the clinical information models that are used to define a model-driven EHR system. Beyond that, it describes how a complete EHR system can be created with multiple language variants, using the example of an EHR for clinical management of patients in a Fracture Liaison Service. A clinical information model, represented as ontology, was developed in the English language.
View Article and Find Full Text PDFJ Med Internet Res
December 2023
Data Science Unit, Hospital Universitario 12 de Octubre, Madrid, Spain.
In order to maximize the value of electronic health records (EHRs) for both health care and secondary use, it is necessary for the data to be interoperable and reusable without loss of the original meaning and context, in accordance with the findable, accessible, interoperable, and reusable (FAIR) principles. To achieve this, it is essential for health data platforms to incorporate standards that facilitate addressing needs such as formal modeling of clinical knowledge (health domain concepts) as well as the harmonized persistence, query, and exchange of data across different information systems and organizations. However, the selection of these specifications has not been consistent across the different health data initiatives, often applying standards to address needs for which they were not originally designed.
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