Design and Adoption of a FHIR IG to Support a Telemonitoring Environment in Gatekeeper Project.
Roberta GazzarataCatherine ChronakiFrancesco RicciardiFrancesco GiulianiPaolo ZampognaroFranco MercalliCarlo AlloccaEugenio GaetaGiuseppe FicoGiorgio CangioliPublished in: Studies in health technology and informatics (2023)
Telemedicine can provide benefits in patient affected by chronic diseases or elderly citizens as part of standard routine care supported by digital health. The GATEKEEPER (GK) Project was financed to create a vendor independent platform to be adopted in medical practice and to demonstrate its effect, benefit value, and scalability in 8 connected medical use cases with some independent pilots. This paper, after a description of the GK platform architecture, is focused on the creation of a FHIR (Fast Healthcare Interoperability Resource) IG (Implementation Guide) and its adoption in specific use cases. The final aim is to combine conventional data, collected in the hospital, with unconventional data, coming from wearable devices, to exploit artificial intelligence (AI) models designed to evaluate the effectiveness of a new parsimonious risk prediction model for Type 2 diabetes (T2D).
Keyphrases
- healthcare
- artificial intelligence
- electronic health record
- big data
- quality improvement
- type diabetes
- machine learning
- deep learning
- adverse drug
- high throughput
- systematic review
- randomized controlled trial
- primary care
- case report
- cardiovascular disease
- middle aged
- insulin resistance
- clinical practice
- glycemic control
- public health
- chronic pain
- heart rate
- risk assessment
- affordable care act
- data analysis
- weight loss
- adipose tissue