Evaluation of an Android-based mHealth system for population surveillance in developing countries
- Zeshan A Rajput1,2,
- Samuel Mbugua3,
- David Amadi3,
- Viola Chepnǵeno3,
- Jason J Saleem4,5,6,
- Yaw Anokwa7,
- Carl Hartung7,
- Gaetano Borriello7,
- Burke W Mamlin1,2,
- Samson K Ndege3,8,9,
- Martin C Were1,2
- 1Department of Medical Informatics, Regenstrief Institute, Inc, Indianapolis, Indiana, USA
- 2Department of General Internal Medicine and Geriatrics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- 3USAID–Academic Model Providing Access to Health care (USAID–AMPATH) Partnership, Eldoret, Kenya
- 4VA HSR&D Center on Implementing Evidence-Based Practice, Indianapolis, Indiana, USA
- 5Department of Health Services Research, Regenstrief Institute, Inc, Indianapolis, Indiana, USA
- 6Department of Electrical and Computer Engineering, IUPUI, Indianapolis, Indiana, USA
- 7Department of Computer Science and Engineering, University of Washington, Seattle, Washington, USA
- 8Moi University School of Medicine, Eldoret, Kenya
- 9Moi University School of Public Health, Eldoret, Kenya
- Correspondence to Dr Zeshan A Rajput, Department of Medical Informatics, Regenstrief Institute, Health Information and Translational Sciences Building, Suite 2000, 410 West 10th Street, Indianapolis, IN 46202, USA;
- Received 13 July 2011
- Accepted 12 December 2011
- Published Online First 24 February 2012
Objective In parts of the developing world traditionally modeled healthcare systems do not adequately meet the needs of the populace. This can be due to imbalances in both supply and demand—there may be a lack of sufficient healthcare and the population most at need may be unable or unwilling to take advantage of it. Home-based care has emerged as a possible mechanism to bring healthcare to the populace in a cost-effective, useful manner. This study describes the development, implementation, and evaluation of a mobile device-based system to support such services.
Materials and Methods Mobile phones were utilized and a structured survey was implemented to be administered by community health workers using Open Data Kit. This system was used to support screening efforts for a population of two million persons in western Kenya.
Results Users of the system felt it was easy to use and facilitated their work. The system was also more cost effective than pen and paper alternatives.
Discussion This implementation is one of the largest applications of a system utilizing handheld devices for performing clinical care during home visits in a resource-constrained environment. Because the data were immediately available electronically, initial reports could be performed and important trends in data could thus be detected. This allowed adjustments to the programme to be made sooner than might have otherwise been possible.
Conclusion A viable, cost-effective solution at scale has been developed and implemented for collecting electronic data during household visits in a resource-constrained setting.
- Clinical decision support
- data exchange
- developing/using clinical decision support (other than diagnostic) and guideline systems
- developing/using computerized provider order entry
- integration across care settings (inter and intra-enterprise)
- measuring/improving patient safety and reducing medical errors
- mobile devices
- patient facing applications
Part of this work was performed at the Regenstrief Institute, Indianapolis, Indiana, USA.
Funding This project was supported in part by the Abbott Fund and the National Library of Medicine (grant 5T 15 LM007117-14). The project also received funding from the Rockefeller Foundation, the United States President's Emergency Plan for AIDS Relief and from the United States Agency for International Development.
Competing interests None.
Ethics approval The HCT programme was approved by both the Institutional Review Board at Indiana University as well as the Independent Review Commission of Moi University in Kenya.
Provenance and peer review Not commissioned; externally peer reviewed.