Successful implementation of electronic disease reporting in Georgia

Objective The objective of this study was to evaluate several aspects of the electronic disease reporting system and its abilities used in Georgia. Also, the study assessed if the system abilities are tailored to the national surveillance requirements. User attitudes (system strength and weaknesses) toward the system was also surveyed. Introduction The Ministry of Health of Georgia accepted the Electronic Integrated Disease Surveillance System (EIDSS) as an official disease reporting system in 2012. The Georgian government adopted electronic reporting for both veterinary and human diseases in 2015. We conducted a comparative assessment of progress in the implementation of electronic reporting. Methods A face-to-face initial survey was conducted in 2012, a follow-up survey (through telephone interviews) was performed in 2016. The initial survey was conducted in regions that had EIDSS installed and the follow-up survey was conducted in all regions. Standardized questionnaires were used and data was analyzed in Epi Info. Results Out of 450 trained EIDSS users, 32% were interviewed in the initial survey and 25% (of 550) EIDSS trained users were interviewed in the follow-up survey. Of 147 respondents in the initial survey and 138 in the follow-up survey, 44% and 79%, believed that they were using EIDSS effectively, respectively. The follow-up survey showed a 23% increase in respondents who acknowledge an improvement of the electronic reporting; acceptance of EIDSS increased from 80.3% to 97.8%. Of those interviewed in the follow-up survey, 19.7% mentioned that the main success in development of the system is due to improved collaboration between institutes. However, 17.36% of the respondents in the follow-up survey reported non-sufficient quality data. Conclusions Our study suggests that the acceptance and use of EIDSS has noticeably improved, indicating the successful implementation of electronic reporting. Recommendations have been made to further improve the data quality by conducting regular data cleaning and additional user training. We recommend the continuation of EIDSS training.