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. The project will 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 formalisation of clinical guidelines, therefore on the best available clinical evidence, yet it is personalised 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 personalised medicine.
Traditional clinical decision-support systems (DSS) are targeted toward care providers and see their role as providing decision-support at the point of care during patient – care-provider encounters. Until recently, patients were considered as having a very passive role as the DSS interacted only with the care provider who, in turn, was taking the patient's history, physical exam, and ordering laboratory and radiology tests, procedures, and referrals.
In the 21st century and the Internet era, patients no longer wish to have such passive role in their healthcare. With the accessibility of information in general, and healthcare information in particular, patients are more aware of their health and of possible ways to manage their health. They wish to play more active roles in their healthcare, to have access to their health records, and to choose and control who will provide their care and who could access their private information for that purpose. Patients and care providers alike want to assure that the care provided would be of the highest quality, based on up-to-date clinical evidence and cost-effective. Furthermore, they wish that they could be cared for whenever their health state requires attention no matter where they are at that time. Thus, patients need to be empowered with respect to flexibility in their actions, as well as control over the measurement and use of their own data.
Based on this motivation, we envision a knowledge-based patient guidance system (PGS) that securely interacts with the patient and his/her care provides, delivers health-related recommendations and enables access to the patient's health data, whenever a need arises, from any place, and in a user-friendly way using web and Smartphone interfaces.
The MobiGuide addresses the following EU priorities: increasing patient safety, ubiquitous secure access to health care, patient empowerment, developing a common platform for healthcare services and European competitiveness.
Description of target users and groups
Target users include: healthcare providers, patients with chronic illnesses, etc. Patients are the biggest group of end users and final beneficiaries in MobiGuide Project. The overall objective of the project is to create a scalable, secure, ubiquitously accessible, and user-friendly mobile solution for designing, deploying, and maintaining Patient Guidance Systems based on clinical guidelines and personal health records, that provide personalised evidence-based clinical recommendations, increase the patients' satisfaction and compliance to evidence-based clinical guidelines, and reduce risk to patients and healthcare costs.
Therefore, according to the aforementioned objective and the current development of the project, we can identify two types of patients who will use the MobiGuide project in 2015:
- Chronic patients with atrial fibrillation.
- Pregnant women with gestational diabetes and potentially also hypertensive disorders.
In addition, patients from the Diabetics patient organization partner ADC will evaluate the system. We envision that after the end of the project, with further development, MobiGuide could be used for other types of chronic diseases.
Official caregivers will use the platform as a follow-up tool on patient care plans and health states, as well as a knowledge acquisition tool for personalising care plans to patients, and as an intelligent data analysis tool for discovering clinical data patterns in individual patients. This group for the course of the project consists of:
- Physicians specialising in atrial fibrillation and gestational diabetes and hypertension in pregnancy: cardiologists and endocrinologists.
- Other formal caregivers: Nurses and dieticians.
Technical support personnel, although not end-users per se, are important figures, since they are the ones giving support when any technical problems occur for the other target groups.
Another group of users are the knowledge engineering team who create the knowledge base for the Mobiguide patient guidance system.
Description of the way to implement the initiative
The MobiGuide team envisions a knowledge-based patient guidance system (PGS) that securely interacts with the patient and his/her care provides, delivers health-related recommendations and enables access to the patient's health data, whenever a need arises, from any place, and in a user-friendly way using web and Smartphone interfaces. The recommendations delivered will be based on evidence-based clinical guidelines that are formally represented and are executed according to the patient's clinical data.
The clinical data will be semantically integrated into a Personal Health Record (PHR) that persistently will store the patient's life-long data from hospital and care centre's electronic medical records (EMRs), as well as physiological data that will be acquired using body-wearable and portable monitoring devices at non-clinically controlled environments, additional personal information that will be acquired through a vocal interface over the Smartphone, and events and temporal abstractions of patient data delivered by the PGS.
The project team includes world-class researchers in all of the key technical areas needed for this research, including medical informatics experts on clinical-guideline based DSSs, which represent guidelines as Computer-Interpretable Guidelines (CIGs) – a representation format that enables their execution by the DSS, Body Area Networks (BANs) of body worn mobile sensors and handheld devices that support tele-monitoring of patients, data integration, health ICT standards, privacy and security, intelligent data analysis and visualisation, as well as clinical experts on the domains to which the PGS system would be applied: cardiology and women's health.
During the project, MobiGuide will be used in Italy to help patients with cardiac arrhythmias and in Spain to help patients with diabetes and hypertension.
The project will deliver innovations in several technical areas which are needed to support the MobiGuide advanced intelligent medical services, including mobile and wireless sensor networks and collaborative distributed systems, all working together to keep patients safe and well whilst allowing them to be out and about enjoying a normal life.
MobiGuide is using standards for communication between Mobiguide components and for the logical structure of the Patient Health Record (PHR). For the latter, we are using the HL7 vMR standard, openEHR, and CEN 13606. More information can be found online.Technology choice: Standards-based technology, Mainly (or only) open standards
Main results, benefits and impacts
It is expected that home monitoring, and mobile monitoring in general, will increase patient safety and result in better maintenance of health and hence better health outcomes. A patient in better health should need fewer hospitalisations, which will also result in great cost savings for the healthcare system. However, as the project is still ongoing (July 2013) and stakeholders have not yet started using it, there are no concrete results, benefits and impacts to report yet.
Track record of sharing
The project is in its second of 4 years so most of the sharing has been using publications and presentations at conferences (see MobiGuide’s website) and colloquia, Facebook, project web page, and meetings with collaborators from industry.
The project is still ongoing and patients have not yet started using it, so there are no lessons learnt yet.Scope: International