Main Post- Discussion Week 5: Big Data Risks and Rewards

Main Post- Discussion Week 5: Big Data Risks and Rewards

Our world is becoming increasingly connected through technology. Computers, cell phones, social media, and various platforms have become an integral part of our lives. We carry our phones with us everywhere, and even at work, we rely on computers. As nurses, we play a crucial role in connecting patients with valuable data banks. It’s safe to say that we live in a world filled with valuable big data. However, this data comes with both positive and negative aspects.

Benefits of Using Big Data in Healthcare

The presence of big data in the healthcare system offers several advantages. These benefits become evident from the moment we log into the electronic health record (EHR) until we log out. Valuable information is entered into the computers, which can be used to improve protocols, enhance patient outcomes, increase patient safety, and simplify nursing practices. Additionally, it can lead to more insightful diagnoses and treatments, ultimately resulting in higher-quality care (Wang, Kung & Byrd, 2018). This collected information, along with patient data, allows for the analysis of trends and patterns, ultimately leading to high-quality care.

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Moreover, the collected and stored big data can be highly beneficial in detecting diseases at an early stage by examining signs and symptoms. By identifying lifestyle factors that increase the risk of contracting diseases, we can offer advice to patients on how to protect themselves. It also enables us to monitor the health of populations, regardless of their location, and adjust treatment plans promptly. Furthermore, operational, financial, and clinical data can be analyzed for resource utilization and productivity in real-time (Raghupathi & Raghupathi, 2014). These are just some of the anticipated benefits of having access to big data.

Challenges and Risks of Big Data

However, there are specific challenges associated with using big data. One common challenge is the difficulty in fully implementing standardized nursing technology (SNT). Addressing this challenge could significantly improve data analysis. SNTs in nursing care make it easier to retrieve and analyze data through clinical reasoning. They can enhance the visibility of nursing interventions. Failing to fully implement SNTs represents a significant challenge for healthcare systems.

Additionally, another significant challenge is the lack of data standardization. In such cases, healthcare systems struggle to assess organizational performance and, as a result, cannot make well-informed decisions about necessary changes (Thew, 2018). According to Englebright, breaking down data silos, or big data, can improve nursing performance (Thew, 2018). Big data can also pose a risk if it falls into the wrong hands, such as cybercriminals, resulting in significant damage. Therefore, robust systems are required to protect data effectively.

Big data risks extend beyond cyber-attacks to internal mishandling of data, which can also pose significant risks. Statistics show that a quarter of all healthcare data breach cases resulted from unauthorized disclosure or access. Moreover, more than twice as many data breaches were caused by hackers rather than internal mishandling (Fox & Vaidyanathan, 2016). As we’ve learned from our course materials, nursing informatics and big data offer substantial benefits to patients and healthcare professionals, but these advantages come with certain challenges and risks.

Proposed Strategy

In my opinion, I propose implementing stringent measures through legislative acts on healthcare privacy or various professional bodies. One example of such measures is the Health Insurance Portability and Accountability Act (HIPAA). These measures would ensure that patient data is securely kept, and only authorized agencies and organizations can access it. By doing so, patient data will be fully protected from individuals with ill intentions. With maximum data security, we can harness the benefits of big data and improve the services offered by healthcare systems.

Big Data in Healthcare: Risks and Rewards

Benefits of Big Data

As technology continues to advance, it becomes an integral part of our work environment. To enhance our processes, we must utilize big data. Big data refers to the vast amount of information we collect when caring for our patients (Kantode et al., 2022). This data accumulates from the moment a patient arrives at the facility and continues to grow throughout their stay. Big data includes specific details about patients that would be challenging to analyze without technology’s help. The advantage of using big data in clinical systems is the potential to enhance overall patient care quality by increasing efficiency for the staff. According to Goyal et al. (2022), the healthcare industry deals with massive amounts of information due to the large number of consumers and the necessary data for providing proper care. By having effective systems for analyzing this data, organizations can streamline processes to improve the quality of care. One way to manage big data is through electronic health record systems. These systems collect, store, and organize big data, which can be utilized by healthcare teams to determine appropriate treatments.

Potential Challenges of Big Data

One significant potential challenge of incorporating big data into clinical systems is the issue of privacy. Healthcare organizations are expected to adhere to HIPAA regulations when handling patient care data, and mishandling this data could lead to sensitive information leaks. Wang et al. (2018) notes that mishandling big data due to poor healthcare data management can result in increased healthcare costs and poor patient outcomes. Patient data breaches can be harmful to both the patients and the healthcare organizations involved. It’s crucial to have security measures in place to ensure data remains secure and is not stolen by individuals seeking to profit from it. Furthermore, as big data is uploaded into clinical systems like electronic health records, there is a risk of data loss due to system errors. Data could be lost due to human error, system malfunctions, or even due to a widespread cyber-attack within the organization.

Strategy to Mitigate Big Data Risks

As a nurse leader, one strategy to mitigate big data risks would be to establish policies to prevent the mishandling of sensitive patient data. Comprehensive training should be provided to all staff members, educating them on the proper handling of sensitive information. This training should emphasize the importance of reporting any potential breaches or data losses related to patient information. All staff should receive training on the correct use of electronic health records, as these records are a common source of healthcare big data (Kantode et al., 2022). It is the organization’s responsibility to ensure that the staff is well-equipped to effectively utilize this source of big data, and that they are aware of best practices for data security.

 Reply

Big Data Risks and Rewards sample 4

Module 3, Week 5 Discussion: Big Data Risks and Rewards

Every day, big data is generated not only in healthcare but across various industries. The sheer volume and complexity of this data make it challenging to store and process efficiently. Healthcare organizations need to find ways to sift through big data and harness it to enhance care quality, reduce costs, and improve efficiency (McGonigle & Mastrian, 2022).

Benefits of Using Big Data

One significant advantage of incorporating big data into clinical systems is its potential to generate new ideas and innovations that can boost productivity and establish competitive advantages (Wang et al., 2018). Instead of waiting for a specific time to collect and analyze data, big data can swiftly provide insights, enabling us to propose interventions or innovations (Threw, 2016). For instance, in the cancer clinic where I work, we recently introduced palliative care services for our patients. Before launching this program, it would have been valuable for nurse informaticists and nurse executives to use big data related to palliative care for oncology patients to design the most effective program. This data could include when patients typically require palliative care during their diagnosis and treatment, whether in-person or virtual visits are more effective, and how nursing can best support a palliative care program for oncology patients. With such data, we could develop an effective program, leading to improved patient outcomes.

Challenges of Using Big Data

One significant challenge of integrating big data into clinical systems is the lack of data standardization, both within and across healthcare organizations (Threw, 2016). Moreover, over 75% of big data is unstructured, residing in text files, making it easy to overlook during analysis (McGonigle & Mastrian, 2022). This becomes crucial when considering the example of creating a palliative care program for oncology patients. Palliative care extends beyond numerical data; it encompasses individual patient experiences and needs. Including this unstructured data is essential to developing an effective program.

Strategy to Mitigate the Challenge of Using Big Data

Addressing the challenge of unstructured data involves creating structured representations to make it more comprehensible (Oubenali et al., 2022, p. 2). Research on this issue suggests using Natural Language Processing (NLP) models when analyzing the data (Oubenali et al., 2022). NLP utilizes word embedding methods, replacing individual words with numerical values. This approach allows for the inclusion of patient feedback regarding their palliative care needs and experiences during cancer treatment. It also enables the incorporation of provider experiences and comments into data collection. Incorporating unstructured data offers a more in-depth understanding and empowers nurse informaticists and nurse executives to design a more effective palliative care program for patients.

References

McGonigle, D. & Mastrian, K. (2022). Nursing informatics and the foundation of knowledge (5^th ed.). Jones & Bartlett Learning.

Oubenali, N., Messaoud, S., Filiot, A., Lamer, A., & Andrey, P. (2022).  Visualization of medical concepts represented using word embeddings: A scoping review. BMC Medical Informatics & Decision Making, 22(1), 1-14. doi/org/10.1186/s12911-022-01822-9

Threw, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execsLinks to an external site.

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(1), 3-13. Big Data Risks and Rewards

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