The eMIS has been evolving over several years with continuous input from end-users, who have provided useful feedback to BIOPHICS to assist in matching the peripheral technical requirements and constraints of local units with the programmatic needs of regional and central management offices. Despite different needs and requests across working units in different malaria-endemic areas of the seven provinces, the system eventually incorporated all concerns with standardized operational practices to generate data across units, therefore reducing double-entries and repetitiveness, and reducing time-consuming effort whilst generating timely, quality cross-checked reports.
During the early phase of system implementation, it took some time for staff to learn to use the system effectively. Several issues arose regarding the management of the hardware and the undeveloped skills of existing staff. While the electronic system evolved, there were physical and psychological effects on staff due to the additional workload as the result of two reporting systems running in parallel (paper- and electronic-based). Several training sessions coupled with progressive improvements to the eMIS, with additional features, increased end-user interest in the new system. This, in turn, allowed BIOPHICS to receive better feedback from, and collaborate more efficiently with, peripheral health staff. Over time, the upper management level at BVBD was also convinced of the added value of a system created to monitor and assess progress made through critical containment interventions with quick remedial actions in their areas of responsibility.
Contributions by the eMIS improved the ability of malaria-surveillance systems to capture data daily from individual malaria patients, almost eliminating the need to collect aggregated monthly data from local operational units. It should be noted, however, that some discrepancies were identified between the original paper-based system and the new electronic-based system in the data reported to upper levels, especially at the beginning of the project when the two systems were still running in parallel. Such findings have been explained as double counting certain papers, data not being digitized at all, or data wrongly introduced to the database. These issues have been progressively addressed by all parties. When cross-checked, consolidated numbers from the eMIS eventually represented the figures reported by the Bureau of Vector-borne Diseases (BVBD), which may differ slightly from the statistics provided by the Bureau of Epidemiology (BOE), which gathers data from additional health sources, such as hospitals. Even though sharing information is a routine practice between the two authorities, with almost all malaria cases being managed free-of-charge by official health facilities (off-the-shelf treatments for malaria are not permitted in Thailand), some patients go directly to official health facilities, clinics, and even hospitals, so they do not get counted on paper, or electronically. This has been an issue with malaria reporting in Thailand over the decades; however, in recent years, the numbers of the two reporting mechanisms have been quite close. It is predicted that a functioning eMIS, which encompasses all healthcare facilities, not just malaria, will further address that issue in the next version of the eMIS.
Individual data recorded in the eMIS can be exported in different formats for further epidemiological analysis. Raw data extracted from the eMIS can then be used to generate reports for authorized staff. Information gathered by the eMIS in 2009–2011 indicated a decline in slide-positivity rate in the 7 provinces from 1.24 to 1.16%. This may be due in part to the intensive early-case-detection and case-management efforts in the containment project. The statistical data collected electronically from each village in each specific jurisdiction, coupled with reclassification for different types of malaria endemicity, make calculating risk by village easier than using the paper-based system.
Several other issues regarding the system implementation require attention. Operational practices were not consistent between different operational units in terms of detection methods, individual follow-up, recording citizenship, occupation, etc. The issues of data integrity and standardization have been discussed elsewhere [8–12]. The collection of more detailed evidence from each operational unit will inform the redesign or fine-tuning of locally-driven prevention and control measures. More comprehensive information will also assist in reallocating resources and efforts to address rapidly evolving situations for each operational unit, which differ from generic, more static measures that are unlikely to deal with disease elimination. The mobile migrant population remained the major concern for the malaria-prevention and -control programme. The system highlighted the high percentage of mobile workers who could not be followed up by malaria staff in the Cambodian border containment area. The case follow-up rate for migrants in the Thai-Cambodian containment area was rather low (as low as 20%) compared with the findings of the Microsoft Research-funded study  piloted in one district on the Thai-Myanmar border, where the malaria follow-up rate was > 80%. Even though the eMIS had similar mobile technology and follow-up module to assist patient tracking as the Microsoft study, the results were different, because most migrants in the latter study were long-term residents of Thailand, and not highly mobile. However, the containment project was implemented in all order districts on the Thai-Cambodian border, where short-stay seasonal migrant workers are numerous; in addition, these areas included migrants from Cambodia seeking healthcare in Thailand. Ensuring that all mobile people, whatever their citizenship, have access to treatment and preventive measures is one of the main containment strategies [14–17]. Therefore, to eliminate artemisinin-resistant strains, more innovative strategies, and the involvement of more key stakeholders (e.g., national and international NGOs working on migrant issues) should be considered. The low follow-up rate among cross-migrant workers along the border could be improved by malaria staff and/or NGOs collaborating with the migrants’ managers or orchard owners. In highly endemic areas, out-of-normal-hour service in malaria clinics may improve minimum required follow-up visits.
Despite these issues, the eMIS’ features, combined with coordinated supervision, have demonstrated the capacity to provide malaria staff and the MOPH/BVBD with quality, quasi-real-time information, allowing them to make accurate decisions on disease control and planning in target areas. The BVBD, backed by BIOPHICS, took advantage of the eMIS system better to monitor the malaria situation in peripheral areas, and could alert local staff to act upon events in a timely manner. The inter-connected modules within the system have shown that the system contributed to an improvement in case management and individual follow up, which in turn helped to improve real-time situation assessment and epidemiological knowledge, and helping to identify the determinants of malaria spread. It also helped malaria workers to identify and track potential resistant parasites more effectively. The outcomes from the eMIS were quite positive, and could potentially be adopted and supported in the national policy to eliminate malaria in Thailand.
The outputs of the eMIS were similar to other information systems developed for malaria prevention and control. The quality of the system’s data has enabled malaria personnel to perform their duties better. The systems developed elsewhere [18–20] were implemented in specific settings, and it was suggested that these systems could be integrated into national malaria control programmes at Ministry level. The eMIS, however, was implemented as part of the routine regional malaria-control programme. This approach was initially planned in the design phase of the eMIS, to assure the robustness and sustainability of the system should it prove effective in malaria-case management and become well-accepted for use as the official malaria information system.
Several GIS applications were developed for case surveillance and vector control (coverage by community-based spraying, insecticide consumption and application rates) and preventive measures (coverage of insecticide-treated nets) [21–24]. The information communication technology (ICT) used in malaria control in Tanzania  suggested ICT could result in easier communication, improved training for doctors, and increased access to information by individuals and groups who are historically unaware of malaria. These information system functionalities are planned for the next version of the eMIS.
A recent review of the research agenda for the monitoring, evaluation and surveillance of malaria, with the end-goal of eradication , suggested that surveillance technologies based on cell-phone or real-time internet web-based reporting, be evaluated, since these new strategies could have major implications for program implementation. An assessment of any delivery system should cover acceptability, feasibility, efficiency, cost-effectiveness, and community engagement. There has been no formal evaluation of the eMIS; however, the system has been imbedded into routine work and appears to have been accepted by system users (based on informal interviews). The main system costs comprised the acquisition and maintenance of system hardware (computer systems and mobile phones), and the employment of new ICT personnel at some operational units. These costs were supported by the containment project initiative under the management of BVBD. However, the project has not yet been evaluated for cost-effectiveness.