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.
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.
Full Answer Section
- More targeted treatment plans: By identifying specific risk factors and genetic predispositions, doctors can tailor treatment plans to individual patients, improving effectiveness and reducing side effects.
- Earlier disease detection: Analyzing large datasets may reveal subtle patterns that could indicate the early onset of diseases like cancer or heart disease. This allows for earlier intervention and potentially better outcomes.
Challenge: Data Security and Privacy
A major challenge associated with big data in healthcare is data security and privacy. Clinical systems often hold extremely sensitive information about patients, including medical history, diagnoses, and treatment details. A data breach could have devastating consequences, causing emotional distress and potentially leading to identity theft or misuse of medical information. Additionally, the vast amount of data collected raises concerns about patient privacy. Patients may be hesitant to share their data if they are unsure how it will be used or protected.
Mitigating the Risk: Robust Security Measures and Transparency
Several strategies can be implemented to mitigate the risks associated with data security and privacy in big data healthcare systems:
- Encryption: All patient data should be encrypted at rest and in transit, making it unreadable even if intercepted by unauthorized individuals.
- Access Controls: Strict access controls should be implemented to ensure only authorized personnel can access patient data, and their access should be limited to the specific information they need for their job functions.
- Regular Security Audits: Regular security audits should be conducted to identify and address any vulnerabilities in the system.
- Patient Education and Transparency: Patients should be clearly informed about how their data is collected, used, and protected. They should have the right to access and control their data, and to opt-out of data collection if desired.
These strategies, along with ongoing research and development in data security, can help build trust with patients and ensure their information remains safe while allowing healthcare systems to leverage the power of big data for improved patient care.
Sample Answer
Big data offers exciting possibilities for improving healthcare, but also presents significant challenges that need to be addressed. Here's a closer look at a potential benefit and a potential risk of using big data in clinical systems:
Benefit: Personalized Medicine and Early Disease Detection
One of the biggest potential benefits of big data in healthcare is the ability to personalize medicine. By analyzing vast amounts of data from various sources, including electronic health records (EHRs), genetic information, and wearable device readings, healthcare professionals can gain a more comprehensive understanding of individual patients. This can lead to: