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.