Using lot quality assurance sampling to assess measurements for growth monitoring in a developing country's primary health care system

Int J Epidemiol. 1996 Apr;25(2):381-7. doi: 10.1093/ije/25.2.381.


Background: Local supervisors used lot quality assurance sampling (LQAS) during routine household visits to assess the technical quality of Costa Rican community-based health workers (CHW): measuring and recording weights of children, interpreting their growth trend and providing nutrition education to mothers.

Method: Supervisors sampled 10 households in each of 12 Health Areas (4-8 hours per area). No more than two performance errors were allowed for each CHW. This LQAS decision rule resulted in judgments with a sensitivity and specificity of about 95 percent.

Results: Three categories of results are reported: (1) CHW adequately weighed children, calculated ages, identified children requiring nutritional services, and used the growth chart. (2) They needed to improve referral, education, and documentation skills. (3) The lack of system support to regularly provide growth cards, supplementary feeding to identified malnourished children, and other essential materials may have discouraged some CHW resulting in them not applying their skills.

Conclusions: Supervisors regularly using LQAS should, by the sixth round of supervision, identify at least 90 percent of inadequately performing CHW. This paper demonstrates the strength of LQAS, namely, to be used easily by low level local health workers to identify poorly functioning components of growth monitoring and promotion.

PIP: Nurses and rural health supervisors used the Lot Quality Assurance Sampling (LQAS) technique to assess the quality of growth monitoring and promotion (GMP) conducted by community health workers (CHWs) in 12 health areas in Costa Rica. Each supervisor made 10 routine household visits and spent 4-8 hours in each area. The study allowed no more than two performance errors per CHW. CHWs could correctly identify children in need of the nutritional services of the primary health care (PHC) system. Yet they were weak in their referral, education, and documentation skills. The supply system and the documentation system that support growth monitoring did not work well. Perhaps the inadequate support system may have contributed to the CHWs' inferior use of their skills. The finding that there were inadequate supplies and poor documentation of required GMP data suggest that CHWs did not regularly conduct growth monitoring, perhaps due to a lack of scales and growth charts. The PHC system did not follow children with nutritional deficiencies, suggesting that health facilities did not keep a register and refer these children systematically. This would explain why CHWs did not refer malnourished children to health facilities. CHWs had significant time constraints that influenced their ability to perform regular growth monitoring. The evaluation team required 4-8 hours to observe growth monitoring in 10 households. The PHC system expects each CHW to conduct about 10 complete household visits/day, which includes growth monitoring, vaccinations, pre- and post-natal care, oral rehydration therapy training, and monitoring blood pressure. With each subsequent supervision visit, the misclassification error of substandard CHW (i.e., the probability of identifying an inadequate performer) decreases. By the sixth visit, supervisors could identify almost all CHWs with a performance quality of 80% or less. These findings suggest that supervisors use LQAS methods to regularly identify GMP problems.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Child
  • Child Nutrition Disorders / prevention & control*
  • Clinical Competence / standards*
  • Community Health Workers / education
  • Community Health Workers / standards*
  • Costa Rica
  • Decision Support Techniques
  • Developing Countries
  • Employee Performance Appraisal
  • Growth Disorders / prevention & control*
  • Humans
  • Primary Health Care / standards*
  • Quality Assurance, Health Care / methods*
  • Sampling Studies
  • Sensitivity and Specificity