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ISSN: 2157-7420

Journal of Health & Medical Informatics
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Research Article

Assessment of Information Sharing Using Social Network Analysis among Health Extension Workers in Konso Woreda: A Cross-Sectional Case Study

Gilano G1*, Megabiaw B2 and Alamirrew A3

1Department of Clinical Nursing, Minch Health Science College, Arba Minch, Ethiopia

2Biostatistics and Epidemiology Department, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia

3Health Informatics Department, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia

*Corresponding Author:
Girma Gilano
Medicine and Health Sciences
Institute of public health
P.O. Box 196, Gondar, Ethiopia
Tel: +251913930384
E-mail: [email protected]

Received Date: December 17, 2016; Accepted Date: March 08, 2017; Published Date: March 15, 2017

Citation: Gilano G, Megabiaw B, Alamirrew A (2017) Assessment of Information Sharing Using Social Network Analysis among Health Extension Workers in Konso Woreda: A Cross-Sectional Case Study. J Health Med Informat 8:251. doi: 10.4172/2157-7420.1000251

Copyright: © 2017 Gilano G, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Introduction: Social network is systematic means of assessing formation and informal networks by mapping and analysing relationships among people, groups, and units of work group or even entire organizations. In this article information Sharing and problem solving methods of health extension worker in Konso woreda was assessed. Objective: This study is aimed to assess information sharing using social network analysis among health extension workers in Konso woreda. Methods: A cross-sectional survey was conducted on all health extension workers in Konso woreda in Southern Ethiopia, using pretested structured pretested roster type questionnaire. All analysis performed by UCINET. Results: The response was rate 77(93%). For who know who network: Degree (64.8), Betweenness (11.1), Eigenvector (0.11), density (79.28%), and for information sharing network Degree (22.3), Betweenness (54.6), Eigenvector (0.11), density (27.2%). Using MR-QAP indicated significant variables such as experience (B=-0.041, p=0.0085), media (B=-0.0430, p=0.0055), site (B=-0.11, p=0.0005) and who know who B=0.1722, p=0.0005). People share information have positive performance (B=0.0466, p=0.01450) Conclusion: The information sharing in HEWs was inadequate. Sharing was observed among different sites rather than the same, people of different experiences than that of the same, and people who have different knowledge of Medias for information Sharing but for who know each other and have performance.

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