Colin A Beckworth1, Rosemary H Davis2, Brian Faragher2, Joseph J Valadez2. 1. Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK cab@liverpool.ac.uk. 2. Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.
Abstract
BACKGROUND: Lot Quality Assurance Sampling (LQAS) is a classification method that enables local health staff to assess health programmes for which they are responsible. While LQAS has been favourably reviewed by the World Bank and World Health Organization (WHO), questions remain about whether using local health staff as data collectors can lead to biased data. METHODS: In this test-retest research, Pallisa Health District in Uganda is subdivided into four administrative units called supervision areas (SA). Data collectors from each SA conducted an LQAS survey. A week later, the data collectors were swapped to a different SA, outside their area of responsibility, to repeat the LQAS survey with the same respondents. The two data sets were analysed for agreement using Cohens' kappa coefficient and disagreements were analysed. RESULTS: Kappa values ranged from 0.19 to 0.97. On average, there was a moderate degree of agreement for knowledge indicators and a substantial level for practice indicators. Respondents were found to be systematically more knowledgeable on retest indicating bias favouring the retest, although no evidence of bias was found for practices indicators. CONCLUSIONS: In this initial study, using local health care providers to collect data did not bias data collection. The bias observed in the knowledge indicators is most likely due to the 'practice effect', whereby respondents increased their knowledge as a result of completing the first survey, as no corresponding effect was seen in the practices indicators. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine
BACKGROUND: Lot Quality Assurance Sampling (LQAS) is a classification method that enables local health staff to assess health programmes for which they are responsible. While LQAS has been favourably reviewed by the World Bank and World Health Organization (WHO), questions remain about whether using local health staff as data collectors can lead to biased data. METHODS: In this test-retest research, Pallisa Health District in Uganda is subdivided into four administrative units called supervision areas (SA). Data collectors from each SA conducted an LQAS survey. A week later, the data collectors were swapped to a different SA, outside their area of responsibility, to repeat the LQAS survey with the same respondents. The two data sets were analysed for agreement using Cohens' kappa coefficient and disagreements were analysed. RESULTS: Kappa values ranged from 0.19 to 0.97. On average, there was a moderate degree of agreement for knowledge indicators and a substantial level for practice indicators. Respondents were found to be systematically more knowledgeable on retest indicating bias favouring the retest, although no evidence of bias was found for practices indicators. CONCLUSIONS: In this initial study, using local health care providers to collect data did not bias data collection. The bias observed in the knowledge indicators is most likely due to the 'practice effect', whereby respondents increased their knowledge as a result of completing the first survey, as no corresponding effect was seen in the practices indicators. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine
Authors: Colin A Beckworth; Robert Anguyo; Francis Cranmer Kyakulaga; Stephen K Lwanga; Joseph J Valadez Journal: BMC Health Serv Res Date: 2016-08-17 Impact factor: 2.655
Authors: Daniel A Sprague; Caroline Jeffery; Nadine Crossland; Thomas House; Gareth O Roberts; William Vargas; Joseph Ouma; Stephen K Lwanga; Joseph J Valadez Journal: Emerg Themes Epidemiol Date: 2016-06-14