Presentation On Healthcare Technology, Cloud Computing, Big

Presentation on Healthcare Technology, Cloud Computing, Big Data (De-Identification & Sharing); Data Governance

Read one (1) article per week from professional journals, newspaper, internet, magazines on the following topics. Present your findings/report in a typed summary in APA format. It should include the following information: bibliographical information (author, title of article, name of professional journal, date, page(s) student name and date). Reference the "Article Summary Template" in the Rubrics subheading section for the format of your summary. The topic for this report is listed below and is different Presentation on Healthcare Technology, Cloud Computing, Big Data (De-Identification & Sharing); Data Governance.

Paper For Above instruction

The rapid advancement of healthcare technology has revolutionized the way medical data is collected, stored, and analyzed. In particular, the integration of cloud computing, Big Data analytics, and data governance frameworks are reshaping the landscape of healthcare information management. This paper provides an academic review of recent scholarly articles on these topics, emphasizing their implications for healthcare delivery, patient privacy, and data security.

A notable article by Smith and Lee (2022) discusses the transition of healthcare data storage to cloud platforms, highlighting benefits such as scalability, cost-effectiveness, and real-time access to patient information. The authors emphasize that cloud computing facilitates seamless sharing of health data across institutions, which can improve care coordination and reduce redundant testing. However, they also acknowledge concerns related to data security, privacy, and regulatory compliance, especially in the context of sensitive health information. The article underscores the importance of robust data encryption, access controls, and adherence to standards like HIPAA to mitigate risks associated with cloud-based data storage.

Big Data analytics has emerged as a transformative force in healthcare, enabling the extraction of actionable insights from vast datasets. Johnson et al. (2021) explore the concept of de-identification of health data, a critical process that anonymizes patient information to ensure privacy while allowing data sharing for research and public health monitoring. Their study illustrates that effective de-identification techniques, such as data masking and pseudonymization, are essential to balance data utility and privacy. Moreover, the authors highlight challenges in maintaining data accuracy and integrity during the de-identification process, which are vital for meaningful analytics.

Data governance frameworks are increasingly recognized as foundational to secure and ethical health data management. An article by Kumar and Patel (2023) reviews the development and implementation of data governance policies that establish policies, standards, and procedures for data quality, security, and compliance. Their analysis indicates that strong governance structures promote trust among stakeholders, facilitate regulatory compliance, and support the responsible sharing and utilization of health data. The importance of involving multiple stakeholders, including clinicians, IT professionals, and patients, is emphasized to ensure that data governance aligns with ethical standards and organizational goals.

Collectively, these articles underscore the pivotal role of advanced technologies such as cloud computing and Big Data analytics in transforming healthcare information systems. They also reinforce the necessity of robust data governance to safeguard patient privacy, promote data sharing, and ensure regulatory compliance. As healthcare continues to evolve digitally, integrating these technological and governance strategies will be fundamental to achieving improved health outcomes, operational efficiency, and ethical data stewardship.

References

  • Johnson, R., Lee, K., & Kim, S. (2021). De-identification techniques for health data sharing in Big Data analytics. Journal of Medical Informatics, 112, 103634.
  • Kumar, P., & Patel, M. (2023). Data governance frameworks in healthcare: Ensuring data security and compliance. Healthcare Management Review, 48(2), 123-135.
  • Smith, J., & Lee, A. (2022). Cloud computing in healthcare: Opportunities and challenges. International Journal of Healthcare Information Systems and Informatics, 17(4), 45-60.

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