Diabetes and hypertension are increasingly common in lifestyle-dependent chronic diseases. They increase the risk substantially of serious cardiovascular events, which have huge costs for society.
Remote self-monitoring of blood pressure and blood glucose has been shown to be effective in supporting the management of these diseases and preventing their exacerbation. In our new approach, we provide automatic guidance for patients and health professionals based on computerized analysis of self-monitoring data. The viability of the approach has been demonstrated in a clinical trial carried out at the Sipoo Primary Health Centre.
Automatic feedback for patients
In our new approach, we included blood glucose, blood pressure, weight, and daily steps as monitored parameters. Meters for these parameters are inexpensive and easy to use, allowing the new care approach to be used also for elderly patients. The patients use VTT’s mobile application – Monica – to upload measurement data to the server system. The data are accessible through the system to nurses and doctors. VTT’s server software automatically analyses the monitoring data uploaded by the patient and generates automatic feedback for both patients and healthcare personnel. The system is based on a rule-based decision support engine that selects the most appropriate feedback messages to be provided in each case.
The feedback specifically aims to be supportive and motivational, encouraging a healthy lifestyle and self-management for the patient. The contents of the feedback messages follow evidence-based care guidelines and the Information-Motivation-Behavioural Skills Model. The health professionals receive alerts based on the monitoring data in cases when the patient needs to be contacted. The new approach potentially frees healthcare resources from routine tasks, enabling the attention of health professionals to be focused on the patients in most need of personal support.
Implementing the technology and assessment of benefits
VTT’s automatic feedback messaging software and the Monica application are modules with open interfaces. We have integrated the modules with a commercial Personal Health Record (PHR) system that is accessible to Sipoo Health Centre customers and personnel. The PHR provides patients with a view on essential personal health data, including their self-measurements, as well as the possibility of carrying out a questionnaire-based Virtual Health Check.
In order to evaluate the benefits of our monitoring approach, we carried out a randomized controlled clinical trial. The trial involved two groups of Type 2 Diabetes patients: intervention patients using the new monitoring technology (performing measurements, receiving feedback messages, accessing health data in the PHR and using the Monica application) and control patients continuing to receive the usual care. A decrease of 0.4% units was observed in the HbA1c value of the intervention group, indicating a statistically significant improvement in blood sugar control. A clear reduction of 2.1 kg in mean weight was also observed. The user satisfaction of the new care model and technology was very high according to the user questionnaire results.
Large-scale deployment of the new care model requires investments by the municipalities in both new technology and care processes. Despite short-term budgetary challenges, these investments are justified. Remote monitoring has been shown to bring benefits to the management of chronic diseases and, according to our study, also a big proportion of patients are compliant with the new care model. The potential of improving the efficiency of healthcare delivery is also high, thanks to the increased automation level of the monitoring process. The need to increase efficiency and quality of healthcare is global. The new monitoring technology components tested in the Sipoo trial are multilingual and expose open interfaces, allowing them to be integrated with other healthcare information systems in Finland and abroad. The technology is also applicable to the care of other chronic diseases.