NURS 6051/5051 TN003 Big Data Risks and Rewards Discussion Paper Example

NURS 6051/5051 TN003 Module03 Big Data Risks and Rewards Discussion AssignmentNURS 6051/5051 TN003 Module03 Big Data Risks and Rewards Discussion Assignment

NURS 6051/5051 TN003 Big Data Risks and Rewards Discussion Assignment Brief

Course: NURS 5051 – Transforming Nursing and Healthcare Through Technology

Assignment Title: NURS 6051/5051 TN003 Module03 Big Data Risks and Rewards Discussion Assignment

Assignment Overview

In this assignment, you will explore the risks and rewards associated with utilizing big data in healthcare systems. Big data refers to large, complex datasets that offer valuable insights when analyzed using specialized approaches. As healthcare professionals, understanding how to leverage big data effectively is crucial for improving patient care and optimizing clinical outcomes.

Understanding Assignment Objectives

The main objectives of this assignment are:

  • Analyze the potential benefits of incorporating big data into clinical systems.
  • Identify challenges and risks associated with utilizing big data in healthcare settings.
  • Propose strategies to mitigate these challenges and maximize the benefits of big data in clinical practice.

The Student’s Role

As a student in this assignment, your role is to critically evaluate the impact of big data on healthcare systems. Reflect on your experiences with health information management and consider how big data can influence clinical decision-making and patient outcomes.

Competencies Measured

This assignment measures your ability to:

  • Apply knowledge of informatics principles to healthcare data management.
  • Analyze the implications of standardized terminologies on healthcare practice.
  • Evaluate strategies for mitigating risks associated with big data utilization in clinical settings.

You Can Also Check Other Related Assessments for the NURS 5051 – Transforming Nursing and Healthcare Through Technology Course:

NURS 6051/5051 TN001 Module01 The Nurse Leader as Knowledge Worker Assignment Example

NURS 6051/5051 TN002 Module02 The Impact of Nursing Informatics on Patient Outcomes and Patient Care Efficiencies Assignment Example

NURS 6051/5051 TN004 Module04 The Use of Clinical Systems to Improve Outcomes and Efficiencies Literature Review Assignment Example

NURS 6051/5051 TN005 Module05 The Role of the Nurse Informaticist in Systems Development and Implementation Portfolio Assignment Example

NURS 6051/5051 TN006 Module06 Policy/Regulation Fact Sheet Assignment Example

NURS 6051/5051 TN003 Big Data Risks and Rewards Discussion Paper Example

Benefit of Utilizing Big Data in Clinical Systems

The use of big data in clinical systems offers significant advantages by enhancing evidence-based practice and improving patient outcomes. When we talk about big data in healthcare, we’re referring to the analysis of large datasets containing patient information, treatments, outcomes, and more. This analysis helps identify patterns and trends that can guide clinical decisions.

For example, in home healthcare, big data can be used to analyze rehospitalization rates. By looking at large amounts of patient data, such as past treatments and conditions, healthcare providers can pinpoint factors contributing to readmissions. This insight allows for targeted interventions—like better discharge planning or follow-up care—which can ultimately improve patient outcomes and reduce unnecessary hospital stays.

Wang, Kung, & Byrd (2018) highlight that big data enables a broader view of evidence-based practice, allowing clinicians to make informed decisions based on comprehensive datasets. This can lead to more effective treatments tailored to individual patient needs.

Challenge of Integrating Big Data into Clinical Systems

Despite its benefits, integrating big data into clinical systems comes with challenges. Chief nurse executives often face the daunting task of managing vast amounts of data, leading to information overload and potential inefficiencies (Thew, 2016). Each healthcare system may use different formats and definitions for data, making it challenging to unify and analyze information effectively.

For instance, when analyzing specific patient data, the definition of terms like “diagnosis” or “treatment” might vary between different electronic health record systems. This lack of standardization complicates data analysis and hinders efforts to derive meaningful insights.

Mitigation Strategy for Addressing Big Data Challenges

To address these challenges, healthcare organizations can implement proactive strategies focusing on data standardization. Bates et al. (2014) emphasize the importance of establishing uniform data formats and definitions across systems. By ensuring internal consistency in how data is represented and interpreted, healthcare providers can streamline data analysis processes.

For example, implementing standardized data exchange protocols like HL7 FHIR (Fast Healthcare Interoperability Resources) facilitates seamless data sharing between different systems. This promotes data consistency and interoperability, enabling more accurate and reliable insights from big data analytics.

In addition, investing in advanced analytics tools that automate data processing and interpretation can significantly alleviate the burden on clinicians. These tools not only enhance efficiency but also allow healthcare providers to focus more on patient care rather than data management.


Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014). Big data in healthcare: Using analytics to identify and manage high-risk and high-cost patients. Health Affairs, 33(7), 1123-1131.

Thew, J. (2016, April 19). Big Data Means Big Potential, Challenges for Nurse Execs. Health Leaders. Retrieved from

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

Response 1

Your insights into data overload for nurse executives are pertinent to the discussion. In addition to data standardization, healthcare organizations should invest in robust data governance strategies to ensure data quality and interoperability across systems. For instance, establishing clear policies and procedures for data collection, storage, and sharing can help maintain data integrity and streamline information management processes. Implementing data governance frameworks, such as data stewardship programs, can empower clinicians to make informed decisions based on reliable and consistent data.

Response 2

I appreciate your focus on the benefits of big data in improving evidence-based practice. Another strategy to mitigate data standardization challenges could involve collaborative efforts between healthcare organizations to establish industry-wide data standards. By working together to define common data elements and formats, healthcare providers can enhance data interoperability and facilitate seamless information exchange. For example, initiatives like the Observational Health Data Sciences and Informatics (OHDSI) collaborative aim to develop shared data standards that enable large-scale analytics across diverse healthcare settings.

Detailed Assessment Instructions for the NURS 6051/5051 TN003 Big Data Risks and Rewards Discussion Assignment

Discussion: 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.

By Day 3 of Week 5

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.

By Day 6 of Week 5

Respond to at least two of your colleagues* on two different days, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks.

*Note: Throughout this program, your fellow students are referred to as colleagues.

Submission and Grading Information

Learning Resources

Required Readings

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

  • Chapter 22, “Data Mining as a Research Tool” (pp. 477-493)
  • Chapter 24, “Bioinformatics, Biomedical Informatics, and Computational Biology” (pp. 537-551)

Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45–47. Retrieved from

Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from

Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126(1), 3–13.

Required Media

Laureate Education (Executive Producer). (2012). Data, information, knowledge and wisdom continuum [Multimedia file]. Baltimore, MD: Author. Retrieved from

Laureate Education (Producer). (2018). Health Informatics and Population Health: Analyzing Data for Clinical Success [Video file]. Baltimore, MD: Author.

Vinay Shanthagiri. (2014). Big Data in Health Informatics [Video file]. Retrieved from

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