Digital Health 2016
Mobile-based clinical decision support system for cardiovascular disease risk management in resource-poor settings
Arvind Raghu, Praveen Devarsetty, David Peiris, Lionel Tarassenko and Gari Clifford
Cardiovascular disease (CVD) continues to be the leading cause of mortality worldwide and over 80% of CVD related deaths occur in low- and middle- income countries. We present SMARThealth, a mobile-based clinical decision support system (CDSS) for assessing and managing a patient’s 10-year risk of developing CVD. The CDSS incorporated user centered design and an agile development approach to make it suitable for use by primary care doctors and health workers in rural India. By leveraging open-source telemedicine frameworks such as the open medical record system (OpenMRS) and Sanamobile, the CDSS allowed standardisation and interoperability of the platform. The system was recently deployed in 54 villages and screened 62254 people for high CVD risk in rural India. We illustrate the application of mobile analytics to derive statistical metrics that can constitute a basis for improving quality and efficiency of screening by rural health workers. The CDSS is now being evaluated for clinical impact and effectiveness in the form of a 2 –year cluster randomised controlled trial and if found effective, it can lead to enhanced CVD risk detection and management for millions of people in India.
Mobile-based clinical decision support system for cardiovascular disease risk management in resource-poor settings
Arvind Raghu, Praveen Devarsetty, David Peiris, Lionel Tarassenko and Gari Clifford
Cardiovascular disease (CVD) continues to be the leading cause of mortality worldwide and over 80% of CVD related deaths occur in low- and middle- income countries. We present SMARThealth, a mobile-based clinical decision support system (CDSS) for assessing and managing a patient’s 10-year risk of developing CVD. The CDSS incorporated user centered design and an agile development approach to make it suitable for use by primary care doctors and health workers in rural India. By leveraging open-source telemedicine frameworks such as the open medical record system (OpenMRS) and Sanamobile, the CDSS allowed standardisation and interoperability of the platform. The system was recently deployed in 54 villages and screened 62254 people for high CVD risk in rural India. We illustrate the application of mobile analytics to derive statistical metrics that can constitute a basis for improving quality and efficiency of screening by rural health workers. The CDSS is now being evaluated for clinical impact and effectiveness in the form of a 2 –year cluster randomised controlled trial and if found effective, it can lead to enhanced CVD risk detection and management for millions of people in India.