Big Data Risks and Rewards: Data in Nursing Practice

Information is crucial in decision-making, be it in a professional environment or in one’s personal life. However, the reliability and effectiveness of the information used relies on the volume of data utilized and the processes used to analyze it. My experience with complex health information access and management has not always been easy although the related technologies make positive differences in the healthcare industry. Security breach is the most common risk and challenge I have observed in the application of health informatics. I have reported several cases of hacked computers and stolen confidential information myself.

Additionally, there have been instances of medical errors in the form of wrong prescriptions and misdiagnoses, particularly from professionals who are not sure on how to use the healthcare systems. Even though big data has improved the healthcare sector it bears several challenges. Every invention has risks and rewards, but the difference-maker is the strategy put in place to minimize the former and maximize the latter.

During my practice as a medical practitioner I have observed numerous benefits of big data application in the healthcare industry. One of them is cost reduction in different areas including admission rates, medications, operational procedures, and staffing. Hospitals that have embraced the invention use predictive analysis to improve staffing through the prediction of admission rates over a period of time, which allows the management to assign staff accordingly (McGonigle & Mastrian, 2017).

Consequently, the hospital will be able to improve its general efficiency, prevent overstaffing, and reduce patient wait times, elements that medical centers across the globe are trying to improve. Furthermore, big data also helps reduce the costs spent on the purchase of various drugs by analyzing their effectiveness on patients. Big data has granted hospitals a tool to analyze and manage their expenses.

Secondly, big data has significantly improved preventative healthcare along with long-term and follow-up patient care. The technology has been crucial in forecasting the type of clients who are most likely to heed the doctors’ advice and those that are not (Wang et al., 2018). This approach has helped hospitals avoid readmissions, especially when dealing with vulnerable individuals. Similarly, medics can now use the data in GPS-enabled inhalers to help track and monitor asthmatic patients and to determine whether they are taking their drugs or not (Glassman, 2017). Big data provides adequate and relevant information which can be used together with medical technology to improve patient care.

Nonetheless, there hindrances to big data, which affect its applicability in medical environments, and the most common one is security. Most healthcare organizations prioritize keeping their data safe to prevent any loss in the event of fires, hackings, breaches, and ransom episodes. These threats can occur in the form of malware and phishing attacks on computers both inside and outside hospitals. Since big data implies large amounts of information which cannot be managed using traditional methods, it means they are subject to numerous vulnerabilities (Thew, 2016). Without proper security measures, patient and hospital management data can be accessed by unauthorized personnel.

Consequently, one strategy that can help mitigate the challenges of big data including security issues that I have observed is the use of standard information-related safety protocols. The Health Insurance Portability and Accountability Act (HIPAA) Security Rule should be used by all facilities that are actively using big data to improve their operations (Laureate Education, 2012). These technical guidelines include controls over access, authentication protocols, transmission security, and integrity, which translate to the use of firewalls, antivirus software, and encryption of sensitive data. More attention should be given to security because, without it, the bid data is at risk of corruption.

Big data has changed the approaches healthcare organizations use in using relevant information. Hospitals are now capable of making helpful and more accurate predictions on patient care and resource allocation and as a result, improve the overall efficiency of medical centers. However, security is a number one risk healthcare institutions face while implementing big data technology. Without the proper security standards, all the analyzed and processed information from big data can be stolen and corrupted by hackers and other unauthorized personally. Consequently, it is imperative that hospitals continuously adhere to the technical safety guidelines listed in HIPAA.


Glassman, K. (2017). Using data in nursing practice. American Nurse Today. Web.

Laureate Education. (2012). NURS6051_W3. Mym.cdn.laureate-media. Web.

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.

Thew, J. (2016). Big data means big potential, challenges for nurse execs. Healthleaders. Web.

Wang, Y., Kung, L., & Byrd, T. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13. Web.

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