Imagine a smart home health assistant that connects any medical device to a doctor's computer. Instead of waiting for a crisis, it uses AI to spot tiny warning signs in a patient's health and alerts the clinic before things get bad. It's like having a 24/7 digital nurse that knows exactly when to call for help and when the patient is doing fine.
Healthcare systems cannot keep up with chronic disease monitoring because medical devices don't talk to electronic health records. This leads to missed high-risk patients and wasted resources on low-risk ones.
An AI-powered remote patient monitoring platform with a smart alarm system and an interoperable architecture for EHR integration.
If you are a clinic dealing with high readmission rates for heart failure — this project developed an AI-powered RPM platform that reduces total visits by 40%. This allows staff to focus on high-risk patients while avoiding unnecessary resource use for low-risk ones.
If you are a device maker dealing with fragmented data silos — this project developed an interoperable software architecture that collects data from any given device and integrates it into Electronic Health Records (EHRs). This makes your hardware more attractive to hospitals by ensuring seamless data flow.
If you are an insurer dealing with the €196 billion annual cost of heart failure in Europe — this project developed a smart alarm system for early intervention. This can save hundreds of euros per patient annually by preventing expensive emergency hospitalizations.
Based on available project data, the platform is expected to save up to hundreds of euros per patient annually by reducing hospitalizations.
Yes, the project specifically designed a software architecture for scalability and interoperability to create a model of care across Europe.
Based on available project data, the project is led by FOLLOWHEALTH SL, but specific licensing terms are not detailed in the summary.
The project conducted the VAL-HIC interventional trial to support the MDR Class IIa certification process.
The platform is designed to be interoperable, enabling the collection of data from any medical device and direct integration into Electronic Health Records (EHRs).
The project is lean and highly focused, consisting of a single Spanish SME (FOLLOWHEALTH SL). This 100% industry ratio suggests a strong commercial drive and a streamlined decision-making process, avoiding the complexities of large academic consortia.
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