NURS 6411: Information and Knowledge Management | Week 3

Each task that physicians, nurses, and nurse informaticists undertake within their respective positions generates specific data sets and requires explicit data analyses methods. Therefore, data modeling and database design require a sensitivity to specialized focuses within a health care organization. Consider Mary, for example, a nurse at a large private clinic. Her office manager has asked her to verify how many of the babies born in the last six months were later examined by pediatricians associated with the clinic. What data modeling conditions have to be taken into consideration when designing a database that suits Mary’s task? NURS 6411:Week 3: Data Concepts, Design, and Modeling Assignment

This week, you analyze the benefits and challenges associated with data modeling in a health care setting. You also consider how to mitigate database design issues.

 

Learning Objectives 

Students will:

• Evaluate benefits and challenges of data modeling within health care settings
• Analyze strategies to mitigate database design issues

Learning Resources

Note: To access this week’s required library resources, please click on the link to the Course Readings List, found in the Course Materials section of your Syllabus.

Required Readings NURS 6411:Week 3: Data Concepts, Design, and Modeling Assignment

Coronel, C. & Morris, S. (2017). Database systems: Design, implementation, and management (12th ed.). Boston, MA: Cengage Learning.

• Chapter 2, “Data Models” (pp. 35-64)During database design, the objective is to formulate a system where data is stored for optimum access and use. By providing a history of data modeling’s development, the authors build an understanding of the contemporary database models introduced in this chapter.
• Chapter 9, Sections 9.4–9.9, “Database Design” (pp. 457-477)This section of Chapter 9 deals with conceptualizing database design. It explores all the factors and conditions that need to be considered to ensure that the final product satisfies the end user.

Rux, E., & Borchert, T. (2010). You have how many spreadsheets? Computers in Libraries, 30(8), 21–25.

In this article, the authors provide an example of the development of their database, revealing the successes and missteps they encountered during the process. Managing electronic resources requires a system designed to accommodate the storage and flow of necessary data.

Roberts, A. L., & Sewell, J. P. (2011). Data aggregation: A case study. CIN: Computers, Informatics, Nursing, 29(1), 3–7.

The authors of this article address the need for nurses to adapt to database use. As a condition of the HITECH Act, changes in nursing instruction, data capturing, and health care procedures are required to accommodate the increasing reliance on electronic health records in nursing.

Discussion: Data Modeling and Database Design

The use of databases can significantly improve an organization’s ability to access, share, and apply relevant information. However, despite the wealth of data available in a database, its value is greatly dependent on its design. Designing a database that creates logical data relationships for the end users ensures the best conditions for developing information and knowledge for real-world application.

This Discussion focuses on the importance of thoughtful data modeling and database design. You also consider strategies for mitigating design issues.

To prepare:

• Review the information in this week’s Learning Resources on data modeling and database design.
• Reflect on how you have seen these concepts evidenced in a health care organization’s use of databases.
• Consider the benefits and challenges of data modeling, both generally and within an organization with which you are familiar.
• Review the six different issues with database design described in “Data Aggregation: A Case Study,” found in this week’s Learning Resources. Have you experienced any of these in your own database use? How could an organization avoid such issues through planning?
• Select one of the issues and conduct additional research using the Walden Library to locate an article that addresses your selected issue and provides insights into how it can be avoided.

By Day 3

Post the benefits and challenges of data modeling both generally and within a health care organization. Describe the database design issue you selected and briefly summarize your findings (include your reference). Suggest strategies for how this issue could be mitigated in the database planning phase.

Read a selection of your colleagues’ responses.

By Day 6

Respond to at least two of your colleagues on two different days using one or more of the following approaches:

• Expand on your colleagues’ postings by providing additional strategies for mitigating the database design issue.
• Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
• Make a suggestion based on additional evidence drawn from readings or after synthesizing multiple postings. NURS 6411:Week 3: Data Concepts, Design, and Modeling Assignment

 

 

 

ADDITIONAL INFORMATION 

Evaluate benefits and challenges of data modeling within health care settings

Introduction

Healthcare data is a valuable resource, but it can be difficult to understand. In this post, we’ll discuss the benefits and challenges associated with analyzing healthcare data within healthcare settings. We will also discuss how taking a systemic approach to organizing data can help organizations gain insight from their existing records and improve patient care outcomes.

Healthcare data exists in many forms

Healthcare data exists in many forms. It can be unstructured and difficult to capture, and it’s often collected in a variety of formats. Healthcare data is also collected from a wide range of sources, ranging from patient-generated charts to lab results and even social media posts.

The lack of standardization across these different sources makes it difficult for organizations to analyze their data together in meaningful ways that allow them to make decisions that improve patient care while also protecting patient privacy.

Data visualization tools are helpful for data interpretation.

Data visualization tools are helpful for data interpretation. They can help you make sense of your healthcare data in real time, and they can be used to analyze the effects of various interventions or treatments on patients’ health outcomes.

A good example of this is an electronic medical record (EMR) system that uses dashboards to display critical information about patients’ clinical conditions at any given time. The dashboard includes graphs showing how many patients are currently experiencing each type of illness; this allows physicians to see how many people have been treated so far today, which helps them anticipate how much longer it will take for everyone who needs treatment before another doctor arrives on campus tomorrow morning!

Taking a systemic approach to healthcare data enhances value

There are many benefits to using data in healthcare. The most obvious is that it can be used to make decisions and predictions about patient outcomes, which allows for more effective care. It’s also important to remember that data isn’t just about numbers; instead, it’s a source of information that can help you understand your patients’ needs better and improve their quality of life through better treatment plans or medication management strategies.

When used properly, healthcare data has the potential to transform how we do business—and save lives at the same time!

Sequencing unstructured and structured data is key to achieving knowledge discovery.

In health care, it’s important to be able to aggregate and analyze data from disparate sources. By using unstructured and structured data, we can find patterns in our large sets of data that would otherwise not be visible without the use of an analytics tool. This is especially true for complex problems such as those encountered by clinicians in their day-to-day work lives when they encounter patients with a variety of ailments or issues.

It is important to remember that there are both benefits and challenges when it comes to analyzing healthcare data.

It is important to remember that there are both benefits and challenges when it comes to analyzing healthcare data. The benefits of data modeling are that it allows you to see the big picture, which can help you identify patterns and trends in your data. However, it can also be time consuming due to the need for manual analysis and interpretation of the results.

By using visualizations such as bar charts or line graphs, health care professionals have an easier time understanding how their patients’ conditions relate together within each patient’s history over time (or across several patients). This type of visualization helps them make sense out of large amounts of information quickly by providing context on individual cases as well as aggregating all cases into groups within these larger categories so they can be compared against one another easily while still maintaining focus on specific areas needing improvement based on their own experiences with similar individuals who share similar health problems but differ slightly in terms of severity levels associated with those illnesses.”

Conclusion

Healthcare data exists in many forms and can be analyzed in a variety of ways. Data visualization tools are helpful for data interpretation, but it’s important to remember that there are both benefits and challenges when it comes to analyzing healthcare data. Taking a systemic approach to healthcare data enhances value creation by allowing for knowledge discovery as well as integration between different silos within an organization. Sequencing unstructured and structured data is key to achieving knowledge discovery so we recommend that you try some form of systematic analysis of your own before deciding if this option is right for your situation!