Journal of Family Medicine and Primary Care (Jan 2018)

Monitoring of birth registry coverage and data quality utilizing lot quality assurance sampling methodology: A pilot study

  • Shiyam Sunder Tikmani,
  • Sarah Saleem,
  • Elizabeth McClure,
  • Farnaz Zehra Naqvi,
  • Farina Abrejo,
  • Zahid Soomro,
  • Dennis Wallace,
  • Robert L Goldenberg

DOI
https://doi.org/10.4103/jfmpc.jfmpc_59_17
Journal volume & issue
Vol. 7, no. 3
pp. 522 – 525

Abstract

Read online

Background: Effectively monitoring the coverage and quality of data in low-resource settings is challenging. Lot quality assurance sampling (LQAS) is a method to classify coverage as adequate or inadequate. The aim of this pilot study is sought to determine the coverage and quality of a birth registry in a rural district in Pakistan. Methods: This survey was conducted in 14 clusters of Thatta, Pakistan. LQAS methodology was used to monitor the birth registry from December 2015 to February 2016. We randomly selected 19 villages from each cluster. We used a short questionnaire to review the quality of data collection for select variables. Frequency and percentages were reported for categorical variables. For data validation, Kappa statistics (κ) were applied to assess the agreement between categorical observations, and the Bland–Altman test was used to assess agreement for continuous data. Results: Of the 14 clusters sampled, 12 clusters had adequate coverage. Agreement of hemoglobin performance between the women's response and information in birth registry data was good (κ = 0.718) (95% confidence interval [CI]: 0.58–0.82); agreement on birth outcome recorded by the workers in the registry and as mentioned by women was very good (κ = 1.0); and agreement whether birth weight was assessed within 48 h of delivery was good (κ = 0.648) (0.37–0.92). Conclusion: LQAS is a powerful tool to monitor coverage and data quality of the birth registry maintained by the global network for women's and children's health in Pakistan and potentially for data from other surveillance systems.

Keywords