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Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Large-scale data reporting of paediatric morbidity and mortality in developing countries: it can be done
Trevor Duke1, Edilson Yano2, Adrian Hutchinson3
1Centre for International Child Health, University of Melbourne, MCRI, Royal Children's Hospital, Parkville, Victoria, Australia School of Medicine and Health Sciences, University of Papua New Guinea, Port Moresby, Papua New Guinea.
Abstract:
Although the WHO recommends all countries use International Classification of Diseases (ICD)-10 coding for reporting health data, accurate health facility data are rarely available in developing or low and middle income countries. Compliance with ICD-10 is extremely resource intensive, and the lack of real data seriously undermines evidence-based approaches to improving quality of care and to clinical and public health programme management. We developed a simple tool for the collection of accurate admission and outcome data and implemented it in 16 provincial hospitals in Papua New Guinea over 6 years. The programme was low cost and easy to use by ward clerks and nurses. Over 6 years, it gathered data on the causes of 96,998 admissions of children and 7128 deaths. National reports on child morbidity and mortality were produced each year summarising the incidence and mortality rates for 21 common conditions of children and newborns, and the lessons learned for policy and practice. These data informed the National Policy and Plan for Child Health, triggered the implementation of a process of clinical quality improvement and other interventions to reduce mortality in the neediest areas, focusing on diseases with the highest burdens. It is possible to collect large-scale data on paediatric morbidity and mortality, to be used locally by health workers who gather it, and nationally for improving policy and practice, even in very resource-limited settings where ICD-10 coding systems such as those that exist in some high-income countries are not feasible or affordable.
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