Mobile Community Reporting

Using DHIS2 Java clients for Malaria community reporting in Zambia

The DHIS Mobile clients are deployed in several projects where data is collected from the local community to support and monitor health interventions. One long standing and successful deployment has been driven by a Malaria program run by the National Malaria Control Center in Zambia. The system is used for mobile reporting from health workers at health clinics and voluntary community health workers in the villages, with each of the two user groups reporting on key data that is relevant for their tasks and responsibilities. The project uses the DHIS Mobile Java clients for aggregate reporting, connected to a national DHIS2 instance that is also available for other projects and programs to share. The project supplies low cost mobile phones and prepaid SIM cards for health workers to report with, and the client uses mobile data (GPRS) to send information to the DHIS2 server.

The community health workers (CHW) are volunteers chosen by their local community, often a village health committee, to support their villages on health issues and provide support for the health staff at clinics. The CHW and clinic staff work closely to achieve the project goals and improve the overall health situation in each area. CHW in Zambia is a heterogeneous group as some have had their role for more than 20 years while others have been newly recruited. Similarly, some have participated in a whole range of health related programmes and initiatives and received training accordingly, while others have received very limited training. The CHWs enrolled by the malaria program have been selected according to their level of activity in their local community as perceived by clinic staff, local village health committees or district officials and have received appropriate training to perform programme specific tasks of rapid diagnostic testing, provision of malaria treatment and mobile reporting.

In this malaria program, staff at the clinics report weekly on a small, but carefully chosen data set including number of tests done, number of positive tests, number of people given malaria treatment and stock information. This data is used to monitor the malaria situation in the region, direct more specific interventions and to distribute stocks effectively.

The program operates in areas with relatively low Malaria prevalence, and the aim is to eradicate Malaria from these areas completely. When a clinic or a CHW identifies a positive case, the community health worker visits the home of the patient to test people living in the neighbourhood. The CHW has been provided with rapid diagnostic tests and malaria medication, and can dispense medication and provide information immediately to those who test positive. The community health worker reports monthly on how many tests were performed and how many tested positive. In some cases people will also contact the CHW directly for tests without going to the clinic, or the CHWs may choose to contact people they know are sick.

Malaria is a disease with marked seasonal variations and where timeliness of data is important to act quickly and effectively. Mobile reporting from the community and facility level going directly into national databases is a powerful way to provide such rapid propagation of information, the project has also worked closely with the districts, province and National level to ensure that these are not bypassed in the information flow.

Within each facility catchment area, which has from 5-10 community health workers associated with it, one of the health workers is designated as the ‘Data Community Health Worker’ (DCHW) and is given the responsibility for reporting data into DHIS2 using a Java-enabled mobile phone. This DCHW receives reports from the other CHWs on a monthly basis. This concentrates the training effort for data entry to a smaller group of DCHW and creates a cluster of data collectors around one reporter.

An incentive scheme is in place to give airtime to the community health workers when they report timely data. When the community health worker reports, the DCHW is given a small sum for doing the reporting work and the originating CHW is given a larger sum for providing the data. This money is transferred as airtime to the mobile subscriptions of the community health workers.

Only the Data CHW is given a mobile phone at the beginning of the project, but by reporting timely data consistently over a period of time, the other CHWs in the cluster are able to work towards a cheaper non-Java phone. They use this phone and the credits earned as a work tool, which also makes it easier for clinic staff to reach individual health workers to alert them of malaria cases to respond actively to.

The project has worked with various feedback features to help health workers better understand and use their own data, but the most important learning from the project is a high focus on improving data quality and data collection. One important way of providing feedback to health workers is a monthly meeting where reports generated by DHIS2 are reviewed and discussed in detail. The DHIS Mobile team is working with the project to look for ways of supporting all parts of the information cycle, including data collection, processing, presentation and data use.

The Malaria control project in Zambia gives an interesting example of data collection that is closely tied to a local context and local action. Community health workers move out to test malaria cases in their villages, and the reporting is closely linked to what they find and how they work to improve the local malaria situation. The National Malaria Control Center working with local implementers has done a tremendous job of implementing a successful DHIS Mobile solution, adapting it to their local needs and processes.

Despite the suite of DHIS-Mobile solutions being a relatively new extension to the traditionally PC and web based DHIS2, its swift adoption by many outreached initiatives has been fuelled by the widespread adoption of DHIS2 as a national HMIS backbone. DHIS2 serves as the national HMIS backbone in Zambia as in many other countries. In order to comply with the national HMIS strategy and facilitate easy data sharing with the Ministry of Health and other interested parties the National Malaria Control Center (NMCC) in Zambia chose to adopt DHIS-Mobile for their malaria specific outreached data gathering. Despite the NMCC’s awareness of other reliable open source mobile data collection solutions their interest towards compliance with the national HMIS strategy and the comprehensive features of the DHIS2 backbone informed their decision to leverage DHIS-Mobile for their mobile reporting and CHW feedback needs. DHIS2 provides the necessary features for a program to collect their specific data, but also supports a national strategy of collecting and sharing data between different programs and projects. All that is required to share raw data, generated reports, graphs, maps and interpretations with collaboration partners is a web browser, login credentials and well defined information access rights.

Acknowledgements

We would like to thank the Zambian Ministry of Health and Ministry of Community Development and Mother and Child Health, the National Malaria Control Center, MACEPA, Path, Akros and Jason Pickering for providing rich information about this project, and their continued feedback on how to improve the DHIS2 software. The project has been implemented locally in Zambia with very little support from the University of Oslo, demonstrating the importance and success of local capacity to roll out such systems. We would also like to thank the individual health staff in districts, at health clinics and community health workers for using the system and giving valuable feedback. The program is now institutionalized to the extent that district health staff have taken ownership and provide training and very competent support to their areas. The high level of competence at all staff levels in the program is very impressive. Their input has helped us develop important features that now are being used by other projects worldwide.

Authors: Lars Kristian Roland, Terje Sanner, Petter Nilsen and Kristin Braa, University of Oslo.