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Randomized Controlled Trial
. 2009 Dec;14(12):1448-56.
doi: 10.1111/j.1365-3156.2009.02397.x. Epub 2009 Oct 5.

Community-based validation of assessment of newborn illnesses by trained community health workers in Sylhet district of Bangladesh

Abdullah H Baqui  1 , Shams E Arifeen, Heather E Rosen, Ishtiaq Mannan, Syed M Rahman, Arif Billah Al-Mahmud, Daniel Hossain, Milan K Das, Nazma Begum, Saifuddin Ahmed, Mathuram Santosham, Robert E Black, Gary L Darmstadt; Projahnmo Study Group
Affiliations
Randomized Controlled Trial

Community-based validation of assessment of newborn illnesses by trained community health workers in Sylhet district of Bangladesh

Abdullah H Baqui et al. Trop Med Int Health. 2009 Dec.

Abstract

Objectives: To validate trained community health workers' recognition of signs and symptoms of newborn illnesses and classification of illnesses using a clinical algorithm during routine home visits in rural Bangladesh.

Methods: Between August 2005 and May 2006, 288 newborns were assessed independently by a community health worker and a study physician. Based on a 20-sign algorithm, sick neonates were classified as having very severe disease, possible very severe disease or no disease. The physician's assessment was considered as the gold standard.

Results: Community health workers correctly classified very severe disease in newborns with a sensitivity of 91%, specificity of 95% and kappa value of 0.85 (P < 0.001). Community health workers' recognition showed a sensitivity of more than 60% and a specificity of 97-100% for almost all signs and symptoms.

Conclusion: Community health workers with minimal training can use a diagnostic algorithm to identify severely ill newborns with high validity.

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Figures

Figure 1
Figure 1
Clinical algorithm for assessment and classification of sick neonates by CHWs in Sylhet
See this image and copyright information in PMC

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