Graphnet has recently launched myCareCentric Epilepsy - an integrated care solution that enables patients and care teams to manage epilepsy more effectively.
Epilepsy is a condition that affects the brain and can cause repeated seizures. Around 600,000 people in the UK are diagnosed with epilepsy and patients often have to visit hospital many times for tests and consultant appointments to discuss and amend their treatment.
myCareCentric Epilepsy aims to improve the treatment and quality of lives of those with epilepsy by combining the latest in wearable technologies, shared care records, machine learning and data analysis tools to allow greater information gathering and sharing between patients and care teams.
myCareCentric Epilepsy supports new models of care which are more responsive to the needs of the individual. At the same time, the new clinical pathways, coupled with real-time pre-emptive interventions, will help reduce the costs of care and improve the treatment of the condition.
How it works
• Bringing together all patient information (held by the GP, by the acute Trust and by any other parts of the care community) into a single record so it can be shared throughout the community. This is achieved using Graphnet’s CareCentric shared record solution.
• Adding full healthcare data & lifestyle capture via wearable devices (in this case the Microsoft Band), other connectable health monitors, and smartphones. The app captures data such as sleep patterns, exercise, heart rate, temperature and galvanic skin response.
• Presenting clinicians with the information in a single dashboard view, accessible via the web or mobile applications, so they can review and decide on the most appropriate next steps.
• Allowing clinicians and patients to interact directly and in real time, with huge benefits for patient care and support as well as efficiency. This is done through the myCareCentric patient portal.
• Detecting seizures using machine learning (in this case the Microsoft Azure platform). Seizures are tracked and monitored. The pattern and frequency of events is visible to the clinical team in real-time. Analysis of this data using machine learning could help individuals identify increased risk of seizures.
• Alerts notify medical staff and family when a seizure has occurred, and professional advice can be given directly back to the patient through the app. Clinical teams can be notified when one of their patients presents for an unscheduled admission, providing prompt advice and guidance which could reduce length of stay, improve outcomes or avoid an unnecessary admission.
The Epilepsy Care Alliance has utilised a number of Microsoft products as part of its solution. Patients will wear a Microsoft Band to record data such as sleep patterns, exercise, heart rate and temperature. This information will be used alongside a log of when seizures occur and a patient’s medical records to build up the individual’s condition. Over time, Microsoft Azure – the company’s cloud computing service – could potentially “learn” when someone is about to have a seizure and warn them before it happens.
Access to information from GPs, hospitals, community care and social care with a single log in
Access to care documents, letters, appointments, images, results, care plans and care pathways
Patients can view and update records using smartphones, tablets and personal computers. Supports IOS, Android, Microsoft Surface and a web interface for desktops
Supports improved communication between patients and professionals - Secure messaging and notifications - Uploading of documents, photos and videos - Sharing health diaries - Patients self-record information such as blood pressure, blood sugar, weight - Alerts notifying medical staff when a seizure has occurred, and professional advice can be given directly back to the patient. - Wearable devices to capture further healthcare and lifestyle data such as sleep patterns, exercise, heart rate, temperature and galvanic skin response.
Electronic delivery of key information including: - Appointment reminders and confirmations including locations, maps etc - Guidance - explaining a particular illness or procedure - Clinical information (e.g. medical letters, diagnostic results)
Detecting seizures using machine learning. Seizures are tracked and monitored. The pattern and frequency of events is visible to the clinical team in real-time. Analysis of this data using machine learning could help individuals identify increased risk of seizures.