Fri, May 26, 2017
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The aim of the MobiGuide project is to develop an intelligent decision-support system for patients with chronic illnesses.The system accompanies the patients wherever they go and helps them and their care providers in managing their illness, whether they are at home, at work, out and about or travelling abroad on holiday or for business.

The MobiGuide project develops an intelligent decision-support system for patients with chronic illnesses, such as cardiac arrhythmias, diabetes, and high blood pressure. The patients wear sensors that can monitor biosignals (e.g., heart rate, blood pressure); the signals are transmitted to their Smartphone and from there to a powerful "backend" computer. The MobiGuide decision-support tools, which have access also to the patient's' historical clinical data, such as their hospital records, analyse the data, alert the patient about actions that should be taken, ask the patient questions, in the case that additional information is needed, and make recommendations regarding lifestyle changes or contacting care providers. All recommendations regarding therapy are transmitted to the patients' care providers. The recommendations are based on evidence- based, state-of-the-art clinical guidelines. During the project we intend to focus on the clinical conditions: atrial fibrillation, gestational diabetes and gestational hypertension.

When an Internet connection is not available, the patient's lightweight mobile device can still provide some modicum of support, based on the bodily sensors and on the local mobile device's computational capabilities. Thus, decision support is provided to the patients and to their care providers anytime, anywhere.

The MobiGuide system involves a mobile device (a smart phone) together with a set of portable or wearable sensors that the patient can wear or carry with them. The kind of sensors used varies depending on which illness the patient is suffering from. The intelligent application running on the patient's mobile phone communicates with a complex "back end" system consisting of a set of servers performing various advanced artificial intelligence functions in order to provide high quality intelligent guidance services to the patient and his care providers to help manage the patient's conditions, follow their treatment and to allow timely clinical decisions. The analysis concerns signal data, hospital data, abstractions identified in the data and events generated by the decision support system.

The advice of the MobiGuide's decision-support system is based on formalization of clinical guidelines, therefore on the best available clinical evidence, yet it is personalized to the patient's personal circumstances (e.g. does the patient have help at home? Can he afford the recommended treatment? Is he currently on a business trip) and the technological context (e.g. is there mobile phone coverage? If so, is there enough bandwidth? Is the battery getting low on charge?).

Decision support can be provided to patients and care providers anytime, everywhere; when the patient has mobile phone connection to the main DSS and the complete personal health record, but also light-weight DS may be provided by the mobile system when there is no connectivity, based on fragments of guideline logic kept on the Smartphone and interaction with wearable sensor data.

In a nutshell the MobiGuide system will allow healthcare providers to achieve effective guideline implementation in the context of personalized medicine.

The application can be tailored to many different chronic conditions but during the project we focus on three specific illnesses: one cardiological condition and two complications of pregnancy. The first illness is atrial fibrillation, a condition where the patient's heart rhythm is disturbed (one kind of cardiac arrhythmia) causing a fast and erratic heartbeat. Atrial fibrillation occurs mainly in older people but can afflict younger people suffering from certain diseases. Atrial fibrillation increases the risk of blood clots and stroke. The second condition we focus on in the project is gestational diabetes, a type of diabetes that can arise during pregnancy, usually during the second or third trimester. It can carry some risk to both mother and baby. The third condition is hypertension (high blood pressure) during pregnancy. Hypertension in pregnancy (gestational hypertension) involves a significant risk to both mother and baby. It can result in maternal death, and can cause miscarriages, preterm deliveries and low weight babies, and in some circumstances can lead to a serious complication known as eclampsia. Mothers can be left with chronic hypertension and lifelong increased cardiovascular risk.

In these and many other kinds of chronic illnesses the patient's condition, once diagnosed, needs to be monitored carefully. The MobiGuide system can provide monitoring (round the clock if necessary) together with advice and guidance to the patient 24/7 to help them manage their condition, follow their treatment plan and get appropriate help in a medical emergency. The advice and guidance given to the patient by this complex system works in real time and is based on the latest clinical evidence and best practice guidelines. The system also supports joint decision making between the patient, their family and their medical specialists.

 

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On 20th June MobiGuide held a special session in one of the AIME conference workshops: the joint 7th International Workshop on Knowledge Representation for Health Care (KRH4C) and 8th International Workshop on Process-oriented Information Systems in Healthcare (ProHealth).

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