Biosurveillance is the process of identifying biological weapons before they are deployed and creating prevention and protection strategies to safeguard the health and lives of the people (Sebastiani & Mandl, 2004). The world has become a perilous place due to the advancement in technology, but at the same time, the use of technology for surveillance can be used to safeguard life. This paper will assess the CDC Biosurveillance system and needs and recommend the best information access process to share the Biosurveillance data amongst stakeholders.
Center for Disease Control and Prevention (CDC)
CDC is a federal organization that is responsible for promoting and supporting public health through disease prevention and nation preparedness with the goal of safeguarding and improving the overall public health in the United States of America. CDC works in partnership with local, national, and state level healthcare agencies to monitor and prevent disease outbreaks such as bioterrorism and also maintains national health statistics which can be used in national healthcare decision making (Sebastiani & Mandl, 2004). The CDC leads to preventing and controlling chronic and infectious diseases. The organization surveillance systems have played a significant role in achieving the organization mandate of preventing and controlling diseases and infections that are a threat to public health (Sebastiani & Mandl, 2004). CDC has long recognized and tapped into the potential of information technology and systems especially for surveillance and collecting population and diseases data. CDC operates BioSense which is a cloud-based bio information surveillance system which plays a significant role in the consolidation of the healthcare surveillance data for the United States and the globe as a whole.
CDC Biosurveillance Strategy
CDC adopted a new Biosurveillance strategy which recognizes the importance of Biosurveillance strategy on the security of the nation. The roles of CDC in the new Biosurveillance strategy is to use electronic health data, integrate the Biosurveillance data and promote disease detection and cooperation globally with other health partners. CDC operates the National Notifiable Diseases Surveillance System (NDSSS) which links all public health levels with the aim of monitoring occurrences and any conditions. The system is used by many stakeholders, and it is expected to provide timeless, accurate and sufficient information to promote CDC surveillance efforts (Nuzzo, 2017).
BioSense Cloud-Based Health Information Platform
The BioSense system provides a cloud-based information system that contain standardized tools and procedures that help in the collection, evaluation, storage, and sharing of crucial syndromic information. Healthcare officials can use BioSense to analyze information for decision making which helps to improve the awareness on the health threats and helps to enhance safeguards for the public health. The user selected tools of the BioSense makes it a very effective tool for Biosurveillance (Hauenstein et al., 2007). The ability to operate the BioSense information system platform from the cloud and its ability to share information helps all the shareholders such as states and the local healthcare providers to make decisions from remote areas. The standardized software tools contained in the BioSense platform are accessible across the cloud-based computing environment. ESSENCE is the primary tool in BioSense that enables CDC to be able to collaborate and share data with other partners across geopolitical boundaries which helps to promote surveillance (Dicker et al., 2006).
Health Surveillance Needs of CDC
CDC needs a surveillance program that has high security and promotes access from a different geopolitical location which will help the organization to consolidate essential health data and also communicate possible warnings to the partners (Cimen, Kavurucu, & Aydin, 2014). CDC requires a system that can increase data availability, the usability of the system, eradicate redundancies and incorporate new technological tools for the analysis and presentation of data (Broome & Loonsk, 2004). CDC requires a system that can link both the BioSense Syndromic program and the (NDSSS) to ensure synchronized reporting and relaying information to all the stakeholders. Recommendation
Networked Application with Broad-Based Information Access
A networked application is a software that requires to be connected to a network to operate and exchange data between the server and the user. In a networked application, the data being used can reside on a distance server which can be accessed through a network (Broome & Loonsk, 2004). The networked application for CDC can use a client-server architecture which allows partners to be able to be able to access and also disseminate data through a network. The client can use a computer or a mobile to access data using the networked application which can increase the number of partners who can access the data and report new data which is what CDC needs to promote Biosurveillance (Oluwatosin, 2014). Besides, the networked application can be used to integrate the BioSense and the NDSSS servers which will promote reporting and surveillance in a world that is increasingly becoming integrated.
A networked application allows broad-based access to data which can help CDC to create an integrated Biosurveillance information system. The client-server architecture is best suited in this situation because it allows centralized access, centralized placement of resources, and promotes integrity which is necessary for a Biosurveillance system where many partners are involved, and CDC wants to maintain a high level of integrity due to the sensitivity of biodata (Nuzzo, 2017). Besides, the client-server architecture allows greater scalability which means that CDC can increase the capacity of clients and servers separately without affecting the existing framework (Kaur & Rani, 2017). Therefore, the networked application with broad-based access using client-server architecture is the best approach for CDC to promote consolidation of health surveillance data because it can support cloud-based servers which will encourage reporting and access of data (Saggar, Saggar, & Khurana, 2014).
Broome, C. V., & Loonsk, J. (2004). Public health information network-improving early detection by using a standards-based approach to connecting public health and clinical medicine. Morbidity and Mortality Weekly Report, 199-202.
Cimen, C., Kavurucu, Y., & Aydin, H. (2014). Usage of Thin-Client/Server Architecture in Computer Aided Education. Turkish Online Journal of Educational Technology-TOJET, 13(2), 181-185.
Dicker, R., Coronado, F., Koo, D., & Parrish, R. G. (2006). Principles of epidemiology in public health practice. Atlanta GA: US Department of Health and Human Services.
Hauenstein, L., Wojcik, R., Loschen, W., Ashar, R., Sniegoski, C., & Tabernero, N. (2007). Putting it together: the biosurveillance information system. Disease Surveillance A Public Health Informatics Approach. NJ: John Wiley & Sons Inc.
Kaur, P., & Rani, R. (2017). Distributed and Cloud Computing Architecture. Imperial Journal of Interdisciplinary Research, 3(2).
Nuzzo, J. B. (2017). Improving biosurveillance systems to enable situational awareness during public health emergencies. Health security, 15(1), 17-19.
Oluwatosin, H. S. (2014). Client-server model. IOSRJ Comput. Eng, 16(1), 2278-8727.
Saggar, R., Saggar, S., & Khurana, N. (2014). Cloud computing: designing different system architecture depending on real-world examples. International Journal of Computer Science and Information Technologies, 5(4), 5025-5029.
Sebastiani, P., & Mandl, K. (2004). Biosurveillance and outbreak detection. Data Mining: Next Generation Challenges and Future Directions, 185-198.
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