Collecting data is difficult. Collecting data in low resource settings is even more difficult.
In my epidemiology courses, I have the luxury of generating correlation coefficients and p-values with cleaned, robust data sets. I was oblivious, however, to the process of getting information into this organized and beautifully coded package. That is until I was introduced to this process after I arrived in Mbola, Tanzania to work for the Millennium Villages Project (MVP).
Landing in Tabora on an unpaved airstrip in the middle of the dry season, I was greeted by MVP staff and immediately ushered to the office. For the next few months, I was going to assess progress of the tuberculosis (TB) and prevention of mother to child transmission (PMTCT) of HIV projects in the Mbola cluster. This meant that I would travel to each of five health facilities that served the cluster, speak with health care providers and examine patient registers – notebooks where patient data are kept.
My interactions with health providers – nursing officers, doctors and health care volunteers – revealed that those working in clinics are immensely knowledgeable and dedicated to meeting community health needs. As in the rest of Tanzania, however, Mbola suffers from a detrimental human resources shortage.
Tanzanian Ministry of Health guidelines state that a dispensary must have at least five health care professionals staffed at clinics. Ilolangulu, the largest primary health care facility in the cluster, has only three. Each health worker is therefore burdened with not only seeing patients but also data entry and report writing.
Due to this shortage of staff, patient tracking and follow-up is inconsistent. Data is often disorganized or incomplete. An added layer to this data problem is that the district medical office demands that staff record patient data in disease-specific registers. For example, a mother who has TB, HIV and seeks antenatal care will have three identification numbers, her information residing in three different registers. This makes patient tracking and follow-up burdensome. It also makes compiling monthly reports tedious.
This is about the change.
In December, my Tanzanian colleagues were furiously working to load all cluster patient data into the ChildCount+ database. ChildCount+ is an mHealth platform developed by MVP to assist communities in improving child survival and maternal health. Each individual in the database will soon have one unique number, which may be used to track patient progress, generate monthly reports, assess medical supply needs, etc. The Mbola data team will soon be in the field to train health care providers to properly collect and enter data into this database.
After poring through many, many registers from health facilities in the cluster, I was able to find out that uptake of HIV testing among men, including male partner tests, increased 2-fold between July and December 2010 compared to the previous six months. This increase was due to a community health worker village initiative in July to mobilize male testing – an incredible achievement.
With the launching of ChildCount+, we will easily be able to determine whether uptake in male testing corresponds to the reduced incidence of mother-to-child transmission in the cluster. We can also explore the relationship between increased male HIV testing and trends of sero-discordant couples – couples where one partner is HIV positive and the other negative.
Knowing the answers to these questions can assist in providing evidence-based strategies to address gaps revealed in the data, garnering funding and ultimately improving health service provision in the cluster.
ChildCount+ is an exciting way to improve data collection and analysis within the MVP system. Not only will it improve health services at the village and cluster levels, it will certainly make an epidemiology student’s life easier when she is called to generate confidence intervals on these data.
Hamsa Subramaniam is an MPH student at the Mailman School of Public Health at Columbia University in the Department of Epidemiology. She spent six months in Tanzania studying micronutrient deficiency and supplementation, and learning about health systems in low resource settings. She will graduate in May 2011.