Emis Cambodia

[Edilma Howard]

The eMIS demonstrated that it could capture essential data from individual malaria cases at local operational units, while effectively being used for situation and trend analysis at upper-management levels. The system provides evidence-based information that could contribute to the control and containment of resistant parasites. Currently, the eMIS is expanding beyond the Thai-Cambodian project areas to the provinces that lie along the Thai-Myanmar border.

During the last decades, the Greater Mekong Subregion (GMS) has been experiencing the highest level of Plasmodium falciparum resistance to anti-malarial medicines (as monotherapies or in combination) in the world. More recently, evidence of growing P. falciparum resistance to artemisinin and its derivatives has been reported along the Thai-Cambodian border [1, 2]. Artemisinin-based combination therapy (ACT) is the most rapid, reliable and effective treatments to cure patients infected with P. falciparum malaria worldwide. In addition to possibly compromising results in the Asia-Pacific region, growing falciparum resistance to artemisinin derivatives was considered to be a global public health threat, possibly affecting global efforts and investments if no action is taken, with the potential for particularly ill effects in Africa [3]. Moreover, only a few replacement therapies in the latter phases of drug development are in the pipeline. With the serious concern that resistance may spread beyond the Greater Mekong Subregion to affect other regions, the World Health Organization (WHO) has developed and supported a bi-country and multi-partner initiative to contain artemisinin-resistant parasites. The initiative was later consolidated into a global plan for artemisinin-resistance containment in 2011[4]. The multi-pronged containment strategy was based on several elements: (1) stop the survival and spread of resistant parasites, (2) increase monitoring and surveillance to identify new foci rapidly, and provide information for containment and prevention activities, (3) increase access to diagnostics and treatment with ACT to improve patient outcomes and limit opportunities for resistance, (4) invest in anti-malarial drug resistance-related research, and (5) motivate stakeholders at global, regional and national levels to support containment activities [4].

One key objective of the containment operation was to strengthen programme management through close observation and effective coordination with partners, which would enable rapid and high-quality strategy implementation. The main activities were laid out to ensure that all suspected patients had access to reliable diagnostic tools in the target areas, and to ensure all infected patients had access to and use of radical treatments, including gametocidal drugs [5, 6].

The eMIS was primarily designed to digitize malaria data generated from peripheral passive case-detection units and from intensive index-case investigations, to monitor anti-malarial drug compliance, supervise on/off-site tracking of malarial patients under treatment, to ensure strict follow-up, and to detect/report real-time any inadequate clinical or parasitological response to the drug. In addition, disease mapping and spatial analysis were incorporated into the system to increase the performance of rapid response teams in implementation areas. Moreover, although the eMIS was specifically developed to contain P. falciparum cases, it also records infection information on all other species, and the case-management routines and work activities of malaria-control programmes.

In the case-registration module, the data captured for passive and active case detection (including basic demographics) of both infected and non-infected cases were entered into the eMIS. Details of case investigations and treatments provided, as shown in Figure 2, were captured for all documented infected cases. In addition, particularly for P. falciparum-infected cases, attempts have been made to capture and assess drug compliance on days 1, 2, and 3. Case P. falciparum and Plasmodium vivax cases were followed up routinely, to record temperature, symptoms, and blood-draw, for monitoring treatment outcomes and parasite clearance. Blood smears were collected at registration and during clinic or home follow-up visits for microscopic and PCR analysis; however, not all smears were analysed by PCR or utilized for routine malaria surveillance.

eMIS access and operational modules were integrated into the routine work performed by malaria and public-health personnel. All patient-management activities, and the database containing information associated with the described activities above, which formed part of the eMIS, utilized strict security and were used only by authorized personnel in charge of patient case-management. Similar to data captured within the original paper-based reporting system, the eMIS has maintained the same crucial data integrity and confidentiality. No written informed consent forms were signed by patients who visited the malaria clinics, since the activities were considered routine programmatic malaria procedures and interventions. However, the malaria staff informed all patients verbally and asked them to return to the clinic or agree to home visits, to be conducted as part of their scheduled 28-day follow-up. Data extracted from the eMIS database were secondary data with no identification linked to any individual patient. The authors requested official permission from the Ministry of Public Health (Director of the BVBD) to extract these unlinked digital data for further analysis as part of the joint BIOPHICS-MOPH collaboration. The protocol for this methodology was reviewed and approved by the Ethics Committee of the Faculty of Tropical Medicine, Mahidol University.

Since the eMIS was meant to be used as part of the routine programmatic work of the national malaria-prevention and -control programme, its core functionalities purposively maintained the original vertical reporting system whilst adding specific data-entry procedures for entering individual case detection and investigation information directly into the system. The follow-up information recorded during the home visit was captured online and offline by smart phones provided to malaria and healthcare staff. The data were then transmitted automatically to the system, or synchronized later if cell-phone use was not possible in a follow-up area. With near real-time entry of data and transmission for individual case deection and investigation (from day 0) case follow-up visits into the system, authorized staff at all levels, from local units to BVBD, had the opportunity to gather, review and critically assess the malaria situation in their own areas of responsibility and elsewhere each day. These features and automatic procedures made it much simpler to aggregate data from different types of reports and from different operational units up to the highest level of decision-making. Routine reports of aggregated data with traceable records were able to be generated whenever required. For purposes of data-quality control, especially in the early phase of implementation, the malaria staff maintained, cross-checked, and reconciled the eMIS data captured with those collected from the original paper-based system. The data-completion rates and data quality of the paper-based mechanism were compared with the eMIS, and presented at meetings of management-level malaria-control personnel; there was evidence of incomplete and missing data, as well as data inconsistencies, but the situation improved as the staff became more experienced. It should be noted that, in the early phase of eMIS implementation, data collection and reporting from both routine paper-based and implementation-phase electronic-based systems were done by trained malaria personnel working for the existing national vertical malaria-control programme. The paper-based mechanisms were then progressively phased out in the project areas.

The eMIS offered customized motion graphs and reports, which could be generated based on near-real-time digitized databases. It allowed authorized malaria staff to access, and assess, the malaria situation and trends anywhere in the project area in a timely manner. Graphs and reports can be specifically customized according to the skills and needs of field personnel, location and time. Peripheral operational units and upper management levels can get access to data and generate reports within their BVBD assigned roles and responsibilities. This feature assisted supervising malaria staff in acting upon occurring cases in their localities of responsibility, strengthening the performance of individual case management (under Direct Observed Treatment, DOT) and individual follow-up by allowing staff to take remedial measures and appropriate action in a timely manner.

Employing GIS technology, the motion spatial and temporal presentations within eMIS were utilized by staff to identify and locate follow-up cases, and to assess temporal and spatial situations within their areas of responsibility. Figure 6 shows some examples of GIS presentations in the system. As shown in Figure 6 (a), P. falciparum -infected cases (Thais and non-Thais) in the seven provinces were scattered mostly along the border villages. There were more absolute cases in the northeastern provinces, probably due to the larger population size. Figure 6 (b) shows cases mapped at the household level, where local malaria staff performed home visits. Information acquired from individual follow-ups can be displayed for each case investigated. The GIS could also be used by malaria health staff to identify areas targeted for home visits. Dates of appointment were automatically generated to process individual case investigations and to plan subsequent control measures if needed. From self-reported information gathered during case investigations, the location where patients were most likely infected was mapped, as shown in Figure 6(c). This feature had the potential to update prevention and control measures in problematic locations. It should be noted, however, that the potential location of infection was based on self-reporting during atypical case investigation processes.

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