Description:
Health and Demographic Surveillance Systems (HDSS) in developing countries
established to generate quality population based health and demographic surveillance
data to explain reasons for diseases and deaths occurrence in specified demographic
surveillance areas. However, poor reporting, inconsistency and inaccuracy are common
problems in HDSS data. Therefore, this evaluation was designed to assess the quality
collection processes of Ifakara HDSS data particularly on malaria deaths data.
The evaluation assessed the Ifakara HDSS staff skills, essential tools, and procedures
incurred to facilitate quality collection process of malaria deaths data. The case study
evaluation design employed for both qualitative and quantitative approaches, where its
sample drawn from IHDSS data collectors and IHDSS programme heads. A rough guide
criterion was used to draw questionnaire respondents among IHDSS data collectors
while purposive sampling was used to obtain interview respondents among programme
heads. Data obtained analysed using stata and Atlas ti software packages.
The results showed that 96.4% of data collectors in IHDSS had appropriate skills
acquired through training and long working duration of more than 6 months, but lacked
competent supervisors. Necessary tools such as technology (software i.e. CSPro,
window XP OS, and kaspersky, and hardware i.e. computer desktops and PC tablets)
and transportation means such as bicycles, motorbikes, and cars were in use but, too old
and out dated. Also data collection procedures applied guidelines such as DSS manual,
disease classification manual, verbal autopsy and standard operation procedures though
data collectors were not familiar with most of the contents within those manuals.
The evaluation concludes that the collection process of malaria deaths data in IHDSS
was not as quality as it was supposed to be, since it is characterised by incompetent
supervisors, outdated data collection tools, and unfamiliarity of the contents involved in
the data collection guidelines by data collectors.