Facts about Lot Quality Assurance Sampling

A concise summary of implementing Lot Quality Assurance Sampling (LQAS) in maternal and child health surveying in Kenya and Liberia is now available. The fact sheet describes how the rapid, population-based surveying and analysis method was used in the countries.
LQAS interview
Jack Hazerjian/MEASURE Evaluation

A concise summary of implementing Lot Quality Assurance Sampling (LQAS) in maternal and child health surveying in Kenya and Liberia is now available. The document, entitled “Implementation of Maternal and Child Health Outcome Surveys Using LQAS,” describes how the rapid, population-based surveying and analysis method was used in these countries.

Janine Barden O’Fallon, a MEASURE Evaluation research associate, wrote the fact sheet. She said she created it because most materials on LQAS only describe its methodology. She wanted one that described LQAS implementation issues, as well as how MEASURE Evaluation has applied it. “I wanted to write something that reflected our experiences” with LQAS, she said.

LQAS is a statistical methodology used for data collection in health and other programs by several organizations, and it originated in manufacturing and factory production. While LQAS is perceived as fairly quick to carry out, there are ramifications that come with implementing such a quick program. If using complex surveys, for example, this can increase the amount of time it takes to train interviewers, the amount of time interviewers will spend in the field collecting data, and also the time needed to analyze data. These details can then affect the surveys’ costs.

MEASURE Evaluation conducted three rounds of surveys in Kenya from 2010 to 2012 and two rounds in Liberia from 2011 to 2012. For the Kenya LQAS, implementers analyzed five districts in all eight provinces, and they estimated health outcomes for the districts, or “lots,” in this scenario. Some of the health outcomes analyzed in both programs include those related to water, sanitation and hygiene; breastfeeding, nutrition and food security; and vaccination and immunization. Information gathered on these health outcomes can then be used to prioritize project areas. In Kenya, for example, LQAS results helped re-prioritize water and sanitation issues, focusing on two districts in one of the western provinces.

Generally, Barden O’Fallon said, lots should have the same geographic sampling area as the geographic boundaries used for the health program. This happened in Kenya where the program is set up to reflect the geographic boundaries, or districts, at the provincial and national levels. But in the first round in Liberia, this mapping was not pre-defined, so Barden O’Fallon said they worked with “conceptual lots” designed to reflect different funding sources.

Surveys that employ LQAS can be used to provide data on health behaviors and health outcomes at the household level. These data can then be compared to service-related and other data. An example given in the guidance document is that data on the percent of pregnant women and children under five who slept under a mosquito bed net the night before data were gathered could be compared with the number of bed nets a program distributed in that area. These data can be assessed at both provincial or county and sub-provincial or county (or district) levels.