Background: The junction of telemedicine home monitoring with multifaceted disease management programs seems nowadays a promising direction to combine the need for an intensive approach to deal with diabetes and the pressure to contain the costs of the interventions. Several projects in the European Union and the United States are implementing information technology-based services for diabetes management using a comprehensive approach. Within these systems, the role of tools for data analysis and automatic reminder generation seems crucial to deal with the information overload that may result from large home monitoring programs. The objective of this study was to describe the automatic reminder generation system and the summary indicators used in a clinical center within the telemedicine project M2DM, funded by the European Commission, and to show their usage during a 7-month on-field testing period. Methods: M 2DM is a multi-access service for management of patients with diabetes. The basic functionality of the technical service includes a Web-based electronic medical record and messaging system, a computer telephony integration service, a smart-modem located at home, and a set of specialized software modules for automated data analysis. The information flow is regulated by a software scheduler, called the Organizer, that, on the basis of the knowledge on the health care organization, is able to automatically send e-mails and alerts notifications as well as to commit activities to software agents, such as data analysis. Thanks to this system, it was possible to define an automatic reminder system, which relies on a data analysis tool and on a number of technologies for communication. Within the M2DM system, we have also defined and implemented a number of indexes able to summarize the patients' day-by-day metabolic control. In particular, we have defined the global risk index (GRI) of developing microangiopathic complications. Results: The system for generating automatic alarms and reminders coupled with the indexes for evaluating the patients' metabolic control has been used for 7 months at the Fondazione Salvatore Maugeri (FSM) in Pavia, Italy. Twenty-two patients (43 ± 16 years old, 12 men and 10 women) have been involved; six dropped out from the study. The average number of monthly automatic messages was 29.44 ± 9.83, i.e., about 1.8 messages per patient per month. The number of monthly alarm reminders generated by the system was 16.44 ± 4.39, so that the number of alarms per patient was about 1. The number of messages sent by patients and physicians during the project was about 13 per month. The GRI analysis shows, during the last trimester, a slight improvement of the performance of the FSM clinic, with a decrease in the percentage of badly controlled values from 33% to 27%. Finally, we found the presence of a linear increasing correlation between the mean GRI values and the number of alarms generated by the system. Conclusions: A telemedicine system may incorporate features that make it a suitable technological backbone for implementing a disease management program. The availability of data analysis tools, automated messaging system, and summary indicators of the effectiveness of the health care program may help in defining efficient clinical interventions.
ASJC Scopus subject areas
- Medicine (miscellaneous)
- Clinical Biochemistry
- Endocrinology, Diabetes and Metabolism