DNP-815 Topic 3 Discussion 1: How can large aggregated databases be used to improve population health?
DNP-815 Topic 3 Discussion 1: How can large aggregated databases be used to improve population health?
Topic 3 DQ 1
Assessment Description
How can large aggregated databases be used to improve population health? Provide an example of a current disease affecting your population of interest and explain what health promotion or disease prevention evidence-based strategies you would recommend and why. Explain how related data could improve your strategies to promote health and prevent disease. Support your response with relevant literature.
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Topic 3 DQ 1
Big Data and Population Health
Improving population health is an ever-ongoing process through programs that help individuals to live happier lives. Implementing a population health management that takes into account the various determinants of health including genetics, public health interventions, social and physical environment, individual behavior, and adequacy of medical practices is paramount to improving population health (Oesterreich et al., 2020). Fortunately, big data acts as a source where all patient information can be stored and retrieved to influence care. The concept of big data is new in healthcare despite being common in business. Big data is defined as data containing greater variety, arriving in increased volume, and with more velocity (Pastorino et al., 2019). The introduction of electronic health records has helped bridge the gap in the storage of patient information, thus a source of big data. Big data sets can be used in detecting patterns and turning high volumes of data into actionable knowledge for research and formulation of policies that enhance clinical decision-making.
The outbreak of Covid-19 is one of the issues affecting my community. Covid-19 is a viral respiratory tract infection that transmits rapidly through contact with nasal droplets of the infected individuals during exhalation, coughing, or sneezing (CDC, 2022). To reduce its spread, various evidence-based strategies were recommended. Such include the use of face masks, avoidance of social gatherings, washing hands, observing physical distance, sterilizing equipment, and putting on protective gear (Jia et al., 2020). These recommendations are the best ways to protect patients, healthcare providers, and visitors and should be used to control every setting to prevent the spread of Covid-19. Finally, obtaining data about the trend of the disease is essential to the adoption of further protective and preventive measures to curb the spread. According to Oesterreich et al. (2020), such measures include the deployment of public health force, training healthcare providers, research, isolation of victims, screening and testing, and adoption of quarantine measures for all suspected and infected individuals.
References
CDC. (2022, August 23). Transmission. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/transmission/index.html
Jia, J., Ding, J., Liu, S., Liao, G., Li, J., Duan, B., Wang, G., & Zhang, R. (2020). Modeling the control of COVID-19: Impact of policy interventions and meteorological factors. In arXiv [q-bio.PE] (Issue 23, pp. 1–24). https://doaj.org/article/ce65912eea46415fb398bfca27014b19
Oesterreich, S., Cywinski, J. B., Elo, B., Geube, M., & Mathur, P. (2020). Quality improvement during the COVID-19 pandemic. Cleveland Clinic Journal of Medicine. https://doi.org/10.3949/ccjm.87a.ccc041
Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European Journal of Public Health, 29(Supplement_3), 23–27. https://doi.org/10.1093/eurpub/ckz168
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