USING LQAS FOR BASELINE SURVEYS AND REGULAR PERFORMANCE MONITORING IN HEALTH CARE

With decentralization, Local Governments require data to facilitate planning because surveys like demographic and health surveys, national health surveys, sero-behavior surveys and malaria surveys are conducted after three to five years and provide regional and national values not district specific. Health management information system (HMIS) is facility-based and does not give a picture based on the community. To assess the performance of community social development programs, social sector workers and managers routinely monitoring their activities using simplified methods. This presentation will highlight how Lot Quality Assurance Sampling (LQAS) addresses this problem. LQAS is an analysis method that can be used locally in supervision areas to identify priority areas; those not reaching an established performance benchmark for an indicator, measure coverage at an aggregate level (e.g., program catchment area or district or national level), to generate data to inform management decision making; and for sharing information across supervision areas and for reporting purposes. LQAS uses small samples; most frequently used size is 19 per Supervision area. Larger sizes are seldom needed. This methodology works by division of district into 5 or more supervision areas, random selection of 19 locations for interview within each supervision area using the population census village / enumeration area lists, training the district program team members in LQAS, field Work (data collection), hand tabulation and data analysis and finally dissemination of LQAS survey results and implementation of strategic decisions for program improvement. LQAS has been used in various areas like assessing youth friendly services in health facilities, assessing immunization coverage, assessing compliance with health policy and guidelines (patience screening practices), post disasters assessment, women’s health, growth and nutrition, diarrheal disease control, quality management, neonatal tetanus mortality, HIV/AIDS and STIs and routine HMIS data quality assessmen