BIG DATA RISKS AND REWARDS

When you wake in the morning, you may reach for your cell phone to reply to a few text or email messages that you missed overnight. On your drive to work, you may stop to refuel your car. Upon your arrival, you might swipe a key card at the door to gain entrance to the facility. And before finally reaching your workstation, you may stop by the cafeteria to purchase a coffee.

From the moment you wake, you are in fact a data-generation machine. Each use of your phone, every transaction you make using a debit or credit card, even your entrance to your place of work, creates data. It begs the question: How much data do you generate each day? Many studies have been conducted on this, and the numbers are staggering. Estimates suggest that nearly 1 million bytes of data are generated every second for every person on earth.

As the volume of data increases, information professionals have looked for ways to use big data—large, complex sets of data that require specialized approaches to use effectively. Big data has the potential for significant rewards—and significant risks—to healthcare. In this Discussion, you will consider these risks and rewards.

To Prepare:

· Review the Resources and reflect on the web article  Big Data Means Big Potential, Challenges for Nurse Execs.

· Reflect on your own experience with complex health information access and management and consider potential challenges and risks you may have experienced or observed.

Post a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why. Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described. Be specific and provide examples.

Solution Preview

One potential benefit of using big data as part of a clinical system is improved clinical decision-making. Big data analytics can process and analyze vast amounts of patient data, including medical records, diagnostic tests, and treatment outcomes, to identify patterns and trends that may not be apparent through traditional methods. This can enable healthcare providers to make more informed and evidence-based decisions about patient care. For example, by analyzing data from a large population of patients with similar conditions, healthcare professionals can identify the most effective treatments and interventions, leading to better patient outcomes.

However, one potential challenge or risk of using big data in a clinical system is the issue of data privacy and security. With the increasing volume of data being generated and shared within the healthcare system, there is a heightened risk of data breaches and unauthorized access to sensitive patient information. This can lead to violations of patient privacy and the potential for identity theft or fraud. Additionally, the misuse or mishandling of patient data can result in legal and ethical consequences for healthcare organizations.

To mitigate the challenges and risks associated with using big data in clinical systems, healthcare organizations can implement several strategies:

1. Robust Data Encryption: Utilize advanced encryption techniques to protect patient data both at rest and in transit. This ensures that even if unauthorized access occurs, the data remains unreadable and unusable.
2. Access Controls and Authentication: Implement strict access controls and authentication measures to limit access to patient data only to authorized personnel. Multi-factor authentication can add an extra layer of security.
3. Regular Auditing and Monitoring: Conduct regular audits and monitoring of data access and usage to detect any unusual or unauthorized activities. Promptly investigate and address any suspicious activities.
4. Compliance with Data Regulations:…ORDER A COMPLETE AND PLAGIARISM FREE ANSWER HERE