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National Cancer Institute
The National Cancer Institute (NCI) coordinates the research and other activities that relate to the prevention, diagnosis, and treatment of cancer. Under the National Institute of Health, the organization runs the Surveillance, Epidemiology, and End Results Program (SEER) that aims to reduce the cancer rate in the United States. (“Overview of the SEER Program,” n.d.). The National Cancer Institute through the SEER program collects data related to cancer and analyses it to expose general trends and disparities. This paper will review the current surveillance activities and discuss the information technology infrastructure the National Cancer Institute requires implementing to enhance its performance.
The SEER program run by the NCI conducts massive surveillance of cancer. The program collects spatial information on cancer diagnosis, its types, epidemiology, treatment, and mortality data. The program also conducts research on potential carcinogens and various therapies. SEER has over 16 registries that collect various data on cancer and combines this surveillance-based data to get the picture of the cancer rate in the United States (“Overview of the SEER Program,” n.d).
The registries share their data and voice their concern about public health to other relevant organizations. The surveillance program requires data input from multiple sources like the electronic health records and mortality records. Different registries located all over the states also sync their data with the NCI. To unify gained data from different registries the organization is developing new applications with proper data sorting, organization and dissemination capabilities. (“Overview of the SEER Program”, n.d.). The NCI also requires having data processing capabilities that will produce relevant and accurate output comprehensible for epidemiologists and other healthcare providers.
The NCI would require a networked application with broad-based information access that could link all the data sources and registries for the enhanced performance of the SEER program. The application would be required to allow multiple input sources with different data types (Sheikhali et al., 2016). The application should be able to receive data in the form of numbers and words. The user interface should be easy to operate. The application should be able to store the data till it is synced to the central data processing center. The application, therefore, should have a fast Internet connection that can be able to handle the vast amounts of data that will be collected and sent to the central location.
The application at the data collection center and the central processing center should be able to sort and organize relevant information easily. The sorting of information can be done with specially designed algorithms that will retain only relevant information (Sheikhali et al., 2016). The ability to select only relevant information will reduce data processing time and lead to the release of accurate output. The algorithm should also organize data outputs according to the required needs of the users.
The software architecture of the NCI should also have massive data processing capabilities. Relevant algorithms should be implemented into the architecture to ensure timely and accurate data processing. The algorithms should also be programmed to release information output in such a way that can be understood by relevant healthcare professionals (Snelick, Ishikawa, Zwickl, & Taylor, 2014). The output data should also be properly organized and structured to avoid overwhelming the users with information.
The software architecture should also allow for the dissemination of information to various healthcare organizations or policy makers in a clear and comprehensible way. The information should also be properly secured and contain no personal data of the patients. (Velsko & Bates, 2016). The system should also allow the users to manipulate the results to discover unknown trends that are likely to affect the population.
In conclusion, the system’s software architecture at the National Cancer Institute that runs the largest cancer surveillance program, SEER, should be tuned to data collection, its processing, and dissemination. The organization also requires implementing algorithms that will sort and process the collected data to point out general trends and disparities in public health. The organization should develop a networked application with broad-based information access to collect data from various sources and unify their content. Proper planning of the system’s software architecture is vital for the organization development and its enhanced performance in the public health sector.
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