Conducting a Baseline Healthcare Household Survey
Gazing across the rural Kurian countryside, you see houses scattered miles apart from each other, hills rolling, and no major roads but rather tiny, winding walking paths that stretch through fields of maize, over streams without bridges, and over the horizon out of sight. To perform a survey in this landscape is trying – because enumerators must walk day in and day out. We rely on village elders to show us the boundaries and residents of each village; and to complete a survey takes longer than the norm because we must account for the time to walk between households themselves.
M&E in Kenya is preparing for yet again another survey. Not too long ago, we carried out and completed an assessment of poverty in the region using the MPAT tool. Now, we are planning to conduct a baseline healthcare household survey to be able to begin determining the success of the interventions conducted by the healthcare team. The goal of the healthcare team is to reduce under-five mortality. Thus, we will aim to measure the efficacy of the health trainings and interventions carried out by Nuru’s Community Health Workers (CHWs), who address the following health topics related to under-five mortality:
- Neonatal health & immunizations
- Health danger signs of such conditions plus pregnancy & delivery
We must determine which sampling technique will best work given our difficult terrain issues. Also, we do not have recently reliable census data from the areas which we wish to survey. With the 2009 Kenyan Census, we have (somewhat outdated) population numbers and household numbers by sub-location; however, we do not have a breakdown of village-specific (smaller area within a sub-location) numbers. We started to look into Lot Quality Assurance Sampling (LQAS) methodology as a simple, cost-effective technique, especially when accurate population data is not available. For the MPAT, we used a modified 30 x 30 cluster survey sampling technique and our team is now familiar with this method. Some studies confirm that LQAS may prove to be a “statistically appropriate alternative to the more time consuming 30 x 30 cluster-survey.” However, in using this method, I am concerned about incorrectly interpreting findings (given that the sample size in an area is automatically 19) and because there are critiques of LQAS for use in evaluations (as opposed to monitoring). Any outside advice on such sampling techniques?
As for other news, we’re happy to report that the Kenya-based M&E team now has additional and exceptional staff members. Besides our Program Lead Rogonga Augustine, we have Field Managers to cover other program areas – Bhoke Diana with Education; Esther Marube with Healthcare; Mwita Babere with Agriculture; and Mutuki Peter with our CED program (pictured below).
Already next week, a new Western staff team will also join us here in Kenya to start assuming program responsibilities. David Brown will be working as a fellow with M&E. I doubt if he heard about the fellow position from the Nuru Fellows Program’s great video (featuring me!). We are excited he is ready to work and volunteer for 8 months – hopefully continuing to improve upon and add expertise to the M&E team.