Comparing two survey methods of measuring health-related indicators: Lot Quality Assurance Sampling and Demographic Health Surveys.

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.

How late is too late? Timeliness to scheduled visits as an antiretroviral therapy adherence measure in Nairobi, Kenya and Lusaka, Zambia.

Collecting self-reported data on adherence to highly active antiretroviral therapy (HAART) can be complicated by patients' reluctance to report poor adherence. The timeliness with which patients attend visits might be a useful alternative to estimate medication adherence. Among Kenyan and Zambian women receiving twice daily HAART, we examined the relationship between self-reported pill taking and timeliness attending scheduled visits. We analyzed data from 566 Kenyan and Zambian women enrolled in a prospective 48-week HAART-response study. At each scheduled clinic visit, women reported doses missed over the preceding week. Self-reported adherence was calculated by summing the total number of doses reported taken and dividing by the total number of doses asked about at the visit attended. A participant's adherence to scheduled study visits was defined as "on time" if she arrived early or within three days, "moderately late" if she was four-seven days late, and "extremely late/missed" if she was more than eight days late or missed the visit altogether. Self-reported adherence was <95% for 29 (10%) of 288 women who were late for at least one study visit vs. 3 (1%) of 278 who were never late for a study visit (odds ratios [OR] 10.3; 95% confidence intervals [95% CI] 2.9, 42.8). Fifty-one (18%) of 285 women who were ever late for a study visit experienced virologic failure vs. 32 (12%) of 278 women who were never late for a study visit (OR 1.7; 95% CI 1.01, 2.8). A multivariate logistic regression model controlling for self-reported adherence found that being extremely late for a visit was associated with virologic failure (OR 2.0; 95% CI 1.2, 3.4). Timeliness to scheduled visits was associated with self-reported adherence to HAART and with risk for virologic failure. Timeliness to scheduled clinic visits can be used as an objective proxy for self-reported adherence and ultimately for risk of virologic failure.