Comparing two survey methods of measuring health‐related indicators: Lot Quality Assurance Sampling and Demographic Health Surveys. Issue 12 (27th October 2015)

• Record Type: Journal Article
• Authors: Anoke, Sarah C.; Mwai, Paul; Jeffery, Caroline; Valadez, Joseph J.; Pagano, Marcello
• Is Part Of: Tropical medicine & international health. Volume 20:Issue 12(2015:Dec.)
• Page Start: 1756
• Page End: 1770
• Publication Date: 2015-10-27
• Subjects: monitoring and evaluation -- stratified sampling -- cluster sampling -- lot quality assurance sampling -- demographic and health survey -- Uganda; Tropical medicine -- Periodicals; Public health -- Periodicals; 616.988
• DOI: 10.1111/tmi.12605
• Languages: English
• ISSNs: 1360-2276

Abstract

Abstract: Objectives: Two common methods used to measure indicators for health programme monitoring and evaluation are the demographic and health surveys (DHS) and lot quality assurance sampling (LQAS); each one has different strengths. We report on both methods when utilised in comparable situations. Methods: We compared 24 indicators in south‐west Uganda, where data for prevalence estimations were collected independently for the two methods in 2011 (LQAS: n = 8876; DHS: n = 1200). Data were stratified (e.g. gender and age) resulting in 37 comparisons. We used a two‐sample two‐sided Z ‐test of proportions to compare both methods. Results: The average difference between LQAS and DHS for 37 estimates was 0.062 (SD = 0.093; median = 0.039). The average difference among the 21 failures to reject equality of proportions was 0.010 (SD = 0.041; median = 0.009); among the 16 rejections, it was 0.130 (SD = 0.010, median = 0.118). Seven of the 16 rejections exhibited absolute differences of <0.10, which are clinically (or managerially) not significant; 5 had differences >0.10 and <0.20 (mean = 0.137, SD = 0.031) and four differences were >0.20 (mean = 0.261, SD = 0.083). Conclusion: There is 75.7% agreement across the two surveys. Both methods yield regional results, but only LQAS provides information at less granular levels (e.g. the district level) where managerial action is taken. The cost advantage and localisation make LQAS feasible to conduct more frequently, and provides the possibility for real‐time health outcomes monitoring.