Improving the Routine HMIS in Nigeria through Mobile Technology for Community Data Collection
By Ime ASANGANSI et-al:
Decision makers in many developing countries lack the required data needed for evidence-based health management. One reason for this is that the routine national health management information systems (HMIS) do not extend to the ‘last mile’, the communities and the informal setting of villages, where a significant proportion of health events occur. Community-based HMIS data collection is often either poor, or non-existent, in low resource settings. Efforts at establishing community-based HMIS in the past have often failed, or at best, become dysfunctional, beset by challenges with supporting infrastructure such as erratic power supply, poor road transportation and poor telecommunication.
However, the advent of mobile technology with its increasing penetration into the rural areas has permitted a re-envisioning and redesign of HMIS data collection. The study described in this paper presents lessons from the application of mobile technology to the collection of data from households and individuals, with the aim of improving the routine HMIS. It utilized a participatory action research approach; and was carried out in Cross River State in Southern Nigeria. The paper makes three major contributions. Firstly, it briefly describes the context and operations of a mobile-based community data collection system designed and implemented to provide high quality health and demographic data for the national HMIS. Secondly, it details organizational mechanisms by which the application of mobile technology reduces the difficulty of data collection from communities and districts, thus strengthening the district-based national health information system.
Thirdly, the paper points to emerging challenges and areas for further research. Overall, evidence from the research suggests mechanisms by which mHealth data collection improves the HMIS organization, through savings in organizational resources, increases in information quality and in organizational efficiency (technology as an occasion to restructure) as well as in creating new possibilities for institutionalized HMIS data collection. Click to read more