Systematic review on impact of different medical institutions mix model on tuberculosis case detection

doi:10.3969/j.issn.1000-6621.2014.12.011

Abstract

Abstract: Objective Systematic review on impact of different international medical institutions mix model on tuberculosis case detection. Methods We determined the key words by experts’ discussion, and searched 12 database, 3 health agencies websites(World Health Organization network, National Health and Family Planning Commission of the People’s Republic of China and the United States Centers for Disease Control and Prevention) and Google Scholar. Our inclusion criteria were research papers that reported describing public-private, public-public (general hospital and TB dispensary) mix, Non-governmental organizations (NGO)-private mix, case detection, effect evaluation. Eight hundred and three studies (published in 2000-2013)were retrieved, except perspective-related articles, letters, news, editorials, reviews, bibliography and conference summary, 27 full-text studies were included and analyzed. Results The results showed that there are mainly 3 kinds of mixes: public-public (general hospital and TB dispensary) mix, which implement mainly in China, improved the case detection rate ranging from 24.4% to 50.1% through mix; Public-private mix, mainly in India, Indonesia, and Vietnam, Kenya, Nepal, South Korea and the United States and other countries, case detection rate increased 7%-57% through mix; Non-governmental organization-private mix, mainly in India, the case detection rate increased 12%-40% through mix. Conclusion We should further perfect the existing general hospital and TB dispensary mix in China, bring the non-governmental organizations and private institutions into general hospital and TB dispensary mix system, to improve the tuberculosis case detection in China.

Key words: Tuberculosis/diagnosis, Cooperative behavior, Health systems agencies

MA Yan, DU Jian, LI Liang, LIU Yu-hong. Systematic review on impact of different medical institutions mix model on tuberculosis case detection[J]. Chinese Journal of Antituberculosis, 2014, 36(12): 1055-1061. doi: 10.3969/j.issn.1000-6621.2014.12.011

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