New technologies, such as online networking tools, offer innovative ways to engage patients in their diabetes care. Second Life (SL) is one such virtual world that allows patients to interact in a 3D environment with peers and healthcare providers. This article presents a framework that demonstrates how applications within SL can be constructed to meet the needs of patients with diabetes, allowing them to attend group visits, learn more about lifestyle changes, and foster a sense of support and emotional well-being. This experiential approach to education may prove more engaging, and therefore successful, than existing strategies. Addressing concerns relating to privacy and liability is a necessary first step to engage providers in this new approach to patient care.
The growing availability of continuous data from medical devices in diabetes management makes it crucial to define novel information technology architectures for efficient data storage, data transmission, and data visualization. The new paradigm of care demands the sharing of information in interoperable systems as the only way to support patient care in a continuum of care scenario. The technological platforms should support all the services required by the actors involved in the care process, located in different scenarios and managing diverse information for different purposes. This article presents basic criteria for defining flexible and adaptive architectures that are capable of interoperating with external systems, and integrating medical devices and decision support tools to extract all the relevant knowledge to support diabetes care.
Data mining is the process of selecting, exploring, and modeling large amounts of data to discover unknown patterns or relationships useful to the data analyst. This article describes applications of data mining for the analysis of blood glucose and diabetes mellitus data. The diabetes management context is particularly well suited to a data mining approach. The availability of electronic health records and monitoring facilities, including telemedicine programs, is leading to accumulating huge data sets that are accessible to physicians, practitioners, and health care decision makers. Moreover, because diabetes is a lifelong disease, even data available for an individual patient may be massive and difficult to interpret. Finally, the capability of interpreting blood glucose readings is important not only in diabetes monitoring but also when monitoring patients in intensive care units. This article describes and illustrates work that has been carried out in our institutions in two areas in which data mining has a significant potential utility to researchers and clinical practitioners: analysis of (i) blood glucose home monitoring data of diabetes mellitus patients and (ii) blood glucose monitoring data from hospitalized intensive care unit patients.
Current computerized reminder and decision support systems intended to improve diabetes care have had a limited effect on clinical outcomes. Increasing pressures on health care networks to meet standards of diabetes care have created an environment where information technology systems for diabetes management are often created under duress, appended to existing clinical systems, and poorly integrated into the existing workflow. After defining the components of diabetes disease management, the authors present an eight-step conceptual framework to guide the development of more effective diabetes information technology systems for translating clinical information into clinical action.
Self-care is essential in chronic disease management; however, adherence to self-care plans is often far from optimal. Advances in technology can facilitate self-management of chronic disease through patient empowerment and timely feedback. The Confidant system is a novel wireless remote patient monitoring and response system, centered around mobile phone technology, that translates scientifically supported knowledge for chronic disease management into action by providing easily followed daily coaching using the patient's own data. Daily provision of interactive, informative messages removes the burdens of recall, record keeping, decision making, scheduling, and data analysis. A pilot-controlled clinical trial evaluated the feasibility and efficacy of the Confidant system in the management of type 2 diabetes in 15 patients utilizing the cell-phone technology and 15 individuals in a control group (standard type 2 diabetes care). The study demonstrated improved levels of glycosylated hemoglobin, positive changes in diabetes management self-efficacy, and diabetes self-care activities among intervention group patients. A larger trial is now in development to demonstrate the clinical benefit of using the Confidant system among type 2 diabetic patients. This article describes the novel technology and applications of the Confidant system.
In this issue of Journal of Diabetes Science and Technology, the intervention described by D. Katz, “Novel Interactive Cell-Phone Technology for Health Enhancement,” uses cell phones to provide the rapid communication necessary for the support of intensive management of diabetes. Mobile technology is widely accepted in today's society and can be an effective tool for this cause. There have been numerous interventions using various communication tools, including cell phones, to manage chronic disease, which all propose that improved communication and feedback to patients would improve health status. Dr. Katz has taken the next step by giving semiautomated, real-time, immediate feedback on each data point all transmitted by cell phone.