Rapidly spreading diseases such as the Chickungunya and H1N1 outbreaks have recently taken a huge toll in countries like Sri Lanka and India. Given the high population densities of both countries, immediate response is critical to arrest the spread of these diseases. While epidemiology units in India and Sri Lanka receive, and respond to, health information in a relatively timely manner, their systems lack real-time data necessary for more efficient and effective responses.
Information and communication technologies (ICTs) have the ability to provide instant data on potential epidemics to hasten the dissemination of appropriate information, reduce response times, and, ultimately, save lives. The Real-Time Biosurveillance Program (RTBP) was launched in India and Sri Lanka to test the potential of using mobile phones in health data collection. In its initial pilot phase, RTBP sought to establish a mobile-based communications system, introduce the computer-based detection system and implement an e-Health-based surveillance and notification system. The systems were evaluated over a one-year period, and learnings from this phase have informed the scale-up phase.
This project, undertaken in partnership with LIRNEasia, the Indian Institute of Technology – Madras (IITM), Carnegie Mellon University’s Auton Lab, the University of Alberta and the International Development Research Centre (IDRC), is unique in that it was the first of its kind to field-test an integrated end-to-end operational system using mobile phones and intelligent software in the area of real-time disease surveillance. It sought to detect outbreak, but also to notify early warnings at the health center level. The data collection leg of RTBP involved government healthcare workers and used advanced detection algorithms such as Spatial-Temporal Scanning, Bayesian Modeling and Multi-Stream Real-Time Monitoring.
Current Epidemic Surveillance and RTBP
At present, the paper-based disease surveillance system in Sri Lanka and India gathers hand-written patient data from regional and community health centers that then undergoes a cumbersome process. These centers then analyze the data to identify potential disease outbreaks. On finding statistically significant trends, the regional offices issue notifications to local authorities, again using paper-based reporting methods. In the case of epidemics, this process takes two-to-three weeks. “Often, most cases are suspected cases, with fewer confirmed cases. Patients with symptoms are asked to go for further tests, and this takes time,” says Project Director Nuwan Waidyanatha. “By the time a good number of confirmed cases are collected, the disease has spread rapidly. From a public health perspective, this is just not good enough. We need to catch it at the out-patient care level, restrict spread to clusters and deliver a cure before it grows into a wider geographical spread.”
RTBP worked with these existing procedures and added ICT-based components. During the pilot project, health center staff collected patient data using mobile phones, in addition to their routine paper-based work. A software application implemented on mobile phones helped collect patient records and transmit them to a central server using commercial cellular data services. Statistical analysis was carried out using advanced software developed by Carnegie Mellon University’s Auton Lab. Regional and local health officials could then access the results as electronic notifications through a variety of devices, including mobile phones.
Over a period of 15 months, more than 130,000 individual patient records were collected in India and more than 330,000 in Sri Lanka. Outcomes of the pilot phase of the project include: development of a Java-based application for collecting patient data using low-cost mobile phones; successful implementation of the Auton Lab’s analytic software and T-Cube Web Interface for analyzing patient records and almost real-time prediction of disease outbreaks; and the adoption and implementation of the Common Alerting Protocol for multi-channel health alerts.
RTBP identified over a dozen instances of potential disease outbreaks with the local health authorities confirming four of them. The project dramatically reduced time taken for outbreak detection and alerting, from the current period of two-to-three weeks to a single day. Importantly, the project also demonstrated how low-cost mobile phones and existing commercial cellular infrastructure and services could be utilized to enable primary health centers to report patient information even as they record them.
The project experience also shed light on some interesting uses for RTBP’s components. The Alerting Protocol was meant for health alert purposes, but it was also being used by health officials to meet other messaging requirements, such as improving efficiency in routine operations. This finding suggested the need for a more general health notification system using mobile phones.
The success of the pilot phase was due, in large part, to using the mobile phone platform rather than computers. Computers at public health centers remain underutilized often because staff are overburdened with work, patients and a plethora of forms and files to manage manually. Primary healthcare staff are not always comfortable with computers, and the short training programs given to familiarize them with computerized systems are inadequate. “The mobile phone is ubiquitous, easy to adapt and, to a large extent, self-maintained,” says Nuwan Waidyanatha. “In smaller towns, there might be issues with Internet connectivity or even computers and their maintenance parts at the primary health centers, but even a small grocery store will have mobile phone charge cards.”
For health workers, the greatest outcome of RTBP was that the results of their work were being noticed. General consensus among health workers was that the paper-based systems mostly gathered dust and, hence, could be delayed or neglected. The project motivated front-line health staff to improve the quality of data collection.
Constraints to Scalability
The pilot project was very successful in integrating ICT-based systems and shortening time to detection of epidemics and dissemination of instructions to staff on the ground. However, scaling it up to cover a wider area such as a region or even at the national level poses some challenges.
The standard mobile phone numeric keypad is not very convenient for digitizing patient records. Health workers found it difficult to use, particularly when entering large numbers of records, resulting in a small percentage of results that can be reconciled.
The T-Cube Web Interface was found to be useful for supporting long-term planning and the allocation of health resources, as well as regional and national health planning. It was found to be helpful in tracking chronic and lifestyle diseases, such as diabetes. Health officials, however, require greater customization of the product as well as rigorous training for appropriate use.
The project team also found that frontline staff were resistant to adopting the ICT-based system, as this work was being expected of them in addition to their paper-based work. Some of their anxiety also stemmed from the fact that they had to change their routine to digitize data in real time, as opposed to the two-to-three day delay that was more the norm. Schemes to incentivize healthcare staff to integrate the technology in their work may need to be part of the scale-up plan.
Overall results of the RTBP were highly encouraging and the project demonstrated significant efficiency gains in disease reporting, outbreak detection, and health alerting. Cost savings of over 35% was observed in both India and Sri Lanka in comparison to existing systems and costs.
Taking RTBP Forward
Health is a state issue in India. Each Indian state draws up a budget every year and prioritizes certain health concerns. These will vary from state-to-state. State government support for such projects is critical, points out Suma Prashant, the Project Manager at IITM’s Rural Technology and Business Incubator: “The Tamil Nadu Government has been very enthusiastic and supportive of RTBP in the state. For scaling up, this project will need similarly committed partners.” Acceptance is another area the team wants to address in its next phase. “Technology has the answers for early detection of epidemics. RTBP delivers strong results in turnaround time to detection and costs, and is good to go,” says Prashant. “Once the cultural aspects are addressed, we see it being effectively adopted.”
The opinions expressed on the Searchlight South Asia site are solely those of the authors and do not necessarily reflect the positions of the Rockefeller Foundation.