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Using big data in healthcare presents several opportunities, especially for nursing leadership in clinical systems, as the article ” Big Data Means Big Potential, Challenges for Nurse Execs ” clarifies. The ability of big data to improve patient outcomes in clinical systems is a notable benefit by aiding forecasting analytics. For example, in my ongoing nursing experience with complex health information systems, patients at risk of re-entering the hospital have been identified through predictive analytics, leading to early interventions like follow-up care and customized discharge plans. Patterns found in collecting and analyzing massive amounts of patient data can help predict health events and enable proactive interventions. According to a study by Raghupathi and Raghupathi (2014), real-time data processing using big data analytics can enhance clinical decision-making and help nurses and clinicians provide prompt and accurate interventions.
There are drawbacks to using big data as well. For example, some health systems need help securely integrating multiple data sources without compromising patient privacy, which can be a significant HIPPA violation. Healthcare data is susceptible, and breaches can seriously affect patients and healthcare organizations. A 2021 report highlighted that healthcare data breaches affected over 40 million people in the United States alone, illustrating the scale of this issue. (Office for Civil Rights, 2022). This sensitivity means that breaches can have severe and far-reaching consequences for patients and healthcare organizations, ranging from identity theft to medical fraud, reputational damage, and legal penalties (McGonigle & Mastrian, 2022). Unauthorized access is a common risk associated with data sharing. Data breaches are more likely when multiple parties—insurers, third-party vendors, or research institutions—handle or access patient data. This risk is further compounded by the possibility that different organizations sharing data may not follow the same privacy and security regulations. Furthermore, the growth of mobile health technologies and cloud-based systems has increased the attack surface, which makes it simpler for hackers to take advantage of holes in the system (McGonigle & Mastrian, 2021).
A multi-layered strategy for data security is necessary to reduce these risks. Encrypting data while in transit and at rest makes it unreadable even in the event of data interception, provided the correct decryption key is unavailable. In addition, regular auditing and adherence to frameworks such as the Health Insurance Portability and Accountability Act (HIPAA) help maintain vigorous data protection practices. In systems I have observed, only individuals with the proper authorization based on their role (e.g., physicians, nurses, administrative staff) can access specific data sets. Access to sensitive data should also be restricted via role-based access control (RBAC) (McCann, 2014).
References
McCann, E. (2014, February 13). Big data means big potential, Challenges for nurse execs.
Healthcare IT News. https://www.healthcareitnews.com/news/big-data-means-big-potential-challenges-nurse-execsLinks to an external site.
McGonigle, D., & Mastrian, K. G. (2021). Nursing informatics and the foundation of
knowledge (5th ed.). Jones & Bartlett Learning.
Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: Promise and
potential. Health Information Science and Systems, 2(1), 1-10. https://doi.org/10.1186/2047-2501-2-3Links to an external site.
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