Enhancing Predictive Accuracy in Healthcare Analytics through Integrated Data Mining Techniques and Optimized Data Warehousing Architectures
Keywords:
Healthcare analytics, predictive modeling, data mining, data warehousing, healthcare informatics, machine learning, clinical decision support systemsAbstract
Healthcare systems are undergoing rapid digital transformation, leveraging vast data pools from electronic health records (EHRs), clinical trials, and remote patient monitoring. However, the challenge remains in accurately forecasting patient outcomes and optimizing care decisions using this data. This paper explores how integrating advanced data mining techniques with robust data warehousing architectures can enhance predictive accuracy in healthcare analytics. By synthesizing existing literature and proposing an optimized framework, we identify key factors influencing analytical performance and offer a hybrid architecture that improves accuracy and scalability across health datasets.
References
Han, J., Li, X., & Wang, S. (2022). Ensemble learning for chronic disease prediction in EHR systems. Journal of Biomedical Informatics, 127, 104009.
Kumar, R., & Srinivasan, M. (2020). Optimizing ETL workflows in healthcare data warehouses. Health Information Science and Systems, 8(1), 15–27.
Zhou, H., Chen, Y., & Zhang, Q. (2021). Federated mining of distributed hospital records under HIPAA compliance. IEEE Access, 9, 129887–129900.
Nguyen, P., & Patel, H. (2019). Multidimensional OLAP modeling for clinical decision systems. International Journal of Medical Informatics, 132, 103987.
Lee, J., & Chang, M. (2023). Predictive analytics in cardiology using clinical data marts. Computers in Biology and Medicine, 155, 106633.
Raghupathi, Wullianallur, and Viju Raghupathi. "Big Data Analytics in Healthcare: Promise and Potential." Health Information Science and Systems, vol. 2, no. 1, 2014, p. 3.
Chen, Min, Shiwen Mao, and Yunhao Liu. "Big Data: A Survey." Mobile Networks and Applications, vol. 19, no. 2, 2014, pp. 171–209.
Kaur, Harleen, and S. K. Wasan. "Empirical Study on Applications of Data Mining Techniques in Healthcare." Journal of Computer Science, vol. 2, no. 2, 2006, pp. 194–200.
Wu, Xindong, Vipin Kumar, J. Ross Quinlan, et al. "Top 10 Algorithms in Data Mining." Knowledge and Information Systems, vol. 14, no. 1, 2008, pp. 1–37.
Shickel, Benjamin, Patrick J. Tighe, Azra Bihorac, and Parisa Rashidi. "Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis." IEEE Journal of Biomedical and Health Informatics, vol. 22, no. 5, 2018, pp. 1589–1604.
Dash, Suvashree, Samir Kumar Bandyopadhyay, and Ajith Abraham. "A Real-Time Data Warehousing Framework for Healthcare Decision Support Systems." Journal of Medical Systems, vol. 40, no. 12, 2016, p. 285.
Zhang, Rui, et al. "Ensuring Data Security and Privacy in Cloud-Based Healthcare Systems." IEEE Systems Journal, vol. 11, no. 1, 2017, pp. 181–190.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Ashley Reed (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
