Step-by-step guideline for disease-specific costing studies in low- and middle-income countries: a mixed methodology.

BACKGROUND: Disease-specific costing studies can be used as input into cost-effectiveness analyses and provide important information for efficient resource allocation. However, limited data availability and limited expertise constrain such studies in low- and middle-income countries (LMICs). OBJECTIVE: To describe a step-by-step guideline for conducting disease-specific costing studies in LMICs where data availability is limited and to illustrate how the guideline was applied in a costing study of cardiovascular disease prevention care in rural Nigeria. DESIGN: The step-by-step guideline provides practical recommendations on methods and data requirements for six sequential steps: 1) definition of the study perspective, 2) characterization of the unit of analysis, 3) identification of cost items, 4) measurement of cost items, 5) valuation of cost items, and 6) uncertainty analyses.Please provide the significance of asterisk given in table body. RESULTS: We discuss the necessary tradeoffs between the accuracy of estimates and data availability constraints at each step and illustrate how a mixed methodology of accurate bottom-up micro-costing and more feasible approaches can be used to make optimal use of all available data. An illustrative example from Nigeria is provided. CONCLUSIONS: An innovative, user-friendly guideline for disease-specific costing in LMICs is presented, using a mixed methodology to account for limited data availability. The illustrative example showed that the step-by-step guideline can be used by healthcare professionals in LMICs to conduct feasible and accurate disease-specific cost analyses.

A systematic review and meta-analysis of quantitative interviewing tools to investigate self-reported HIV and STI associated behaviours in low- and middle-income countries.

OBJECTIVE: Studies identifying risks and evaluating interventions for human immunodeficiency virus (HIV) and other sexually transmitted infections often rely on self-reported measures of sensitive behaviours. Such self-reports can be subject to social desirability bias. Concerns over the accuracy of these measures have prompted efforts to improve the level of privacy and anonymity of the interview setting. This study aims to determine whether such novel tools minimize misreporting of sensitive information. METHODS: Systematic review and meta-analysis of studies in low- and middle-income countries comparing traditional face-to-face interview (FTFI) with innovative tools for reporting HIV risk behaviour. Crude odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Cochran's chi-squared test of heterogeneity was performed to explore differences between estimates. Pooled estimates were determined by gender, region, education, setting and question time frame using a random effects model. RESULTS: We found and included 15 data sets in the meta-analysis. Most studies compared audio computer-assisted self interview (ACASI) with FTFI. There was significant heterogeneity across studies for three outcomes of interest: 'ever had sex' (I(2) = 93.4%, P < 0.001), non-condom use (I(2) = 89.3%, P < 0.001), and number of partners (I(2) = 75.3%, P < 0.001). For the fourth outcome, 'forced sex', there was homogenous increased reporting by non-FTFI methods (OR 1.47; 95% CI 1.11-1.94). Overall, non-FTFI methods were not consistently associated with a significant increase in the reporting of all outcomes. However, there was increased reporting associated with non-FTFI with region (Asia), setting (urban), education (>60% had secondary education) and a shorter question time frame. CONCLUSION: Contrary to expectation, differences between FTFI and non-interviewer-administered interview methods for the reported sensitive behaviour investigated were not uniform. However, we observed trends and variations in the level of reporting according to the outcome, study and population characteristics. FTFI may not always be inferior to innovative interview tools depending on the sensitivity of the question as well as the population assessed.