Lot Quality Assurance Sampling (LQAS) and Annealing Techniques can help refine programme performance

/, CIDRZ FrontPage, Frontpage Article, In The Press, Latest News, News, Research Rounds, Success Stories/Lot Quality Assurance Sampling (LQAS) and Annealing Techniques can help refine programme performance

Lot Quality Assurance Sampling (LQAS) and Annealing Techniques can help refine programme performance

The Government of the Republic of Zambia in partnership with the European Union (EU), the United Nations Children’s Fund (UNICEF), the Liverpool School of Tropical Medicine (LSTM) and the Centre for Infectious Disease Research in Zambia (CIDRZ) evaluated progress made by the Millennium Development Goal Initiative (MDGI) in Lusaka and Copperbelt Provinces.

The Ministry of Health, LSTM and CIDRZ implemented household surveys using the Lot Quality Assurance Sampling (LQAS) method in order to estimate improvements in maternal, newborn, child health (MNCH), and water, sanitation and hygiene (WASH) at the district and provincial level.

Presenting survey findings during the CIDRZ weekly research meeting, Professor Joseph Valadez, Chair

Professor Joseph Valadez during the CIDRZ research meeting

of Global Health at the LSTM, said that LQAS was developed to assess performance in multiple districts, provinces and programmes as a whole. “Using LQAS, areas are classified as performing “acceptably” or “unacceptably. Resources can then be directed in areas with unacceptable coverage to identify and address underlying reasons for the problems as well as to Identify effective practices in areas with acceptable coverage”.

 

 

The survey concluded that at the end of five years, 72% of all indicators improved and 44% targets were reached. Analyses showed which districts in both provinces required further investments to improve delivery, post-partum, breast feeding, vaccination, nutrition, WASH and other child health services. “Further health facility assessments and mixed methods are needed to understand and address barriers to access quality service,” Prof. Valadez said.

He added that LQAS data could be combined with data from the district health information system (DHIS-2) and health management information system (HMIS) to measure and improve the accuracy of district coverage estimates. “This annealing technique could be part of regular program in order to refine key programme indicators and programme performance within and across countries”.

 

 

 

 

About the Author:

Leave A Comment