NURS 6411: Week 7: Database Normalization Essay Assignment Paper

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NURS 6411: Week 7: Database Normalization Essay Assignment Paper

NURS 6411: Information and Knowledge Management | Week 7

One of the many advantages of databases is the reduction of duplicate information. Consider a patient who visits a health care provider once for an initial check-up, and then returns to the same provider several more times for follow-up examinations and tests. For each visit, the patient’s data (home address, insurance information, health history, etc.) is re-entered as a separate entry in the patient’s paper-based medical file and then reshelved. This unnecessary outflow of time and effort can be avoided through the use of an efficient online health care database system.

This week, you appraise data redundancy and data normalization in health care databases.

Learning Objectives

Students will:

• Analyze normalization of data

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

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

• Chapter 6, “Normalization of Database Tables” (pp. 201-234)When designing a database, normalization can diminish the risk of redundant input. This chapter defines and describes how to perform normalization of a dataset.

Chute, C. G., Beck, S. A., Fisk, T. B., & Mohr, D. N. (2010). The Enterprise Data Trust at Mayo Clinic: A semantically integrated warehouse of biomedical data. Journal of American Medical Informatics Association, 17(2), 131–135.

This article explores the Mayo Clinic’s data warehousing system: the Enterprise Data Trust (EDT). The authors explain the various components of the EDT and detail how it can enhance research productivity, quality improvement, and best-practice monitoring. .

Westra, B. L., Subramanian, A., Hart, C. M., Matney, S. A., Wilsom, P. S., Huff, S., Huber, D. L., & Delaney, C. W. (2010). Achieving “meaningful use” of electronic health records through the integration of the nursing management minimum data set. The Journal of Nursing Administration, 40(7/8), 336–343.

This article describes the process of updating Nursing Management Minimum Data Sets (NMMDS) to achieve meaningful use compliance. The authors explain the methods used to update three NMMDS data elements, in addition to the results of the updates.

Khan, R., & Saber, M. (2010). Design of a hospital-based database system: A case study of BIRDEM. International Journal on Computer Science and Engineering, 2(8), 2616–2621. Retrieved from http://www.enggjournals.com/ijcse/doc/IJCSE10-02-08-050.pdf

 

The authors present the events at BIRDEM hospital surrounding the introduction of a more technologically-based system. The article shows the adjustments made by the staff to move from partial to fully digitized data storage and exchange. It also covers the process by which the data was transferred and organized within the new system.

Discussion: Normalization of Data

The transition into digitized data storage and access systems in health care requires a general adjustment in data capturing techniques. In the days of paper records, redundancy was a standard—information was written and rewritten with each patient visit. Digitized data storage and the normalization of data can help reduce this redundancy. Ideally, a patient can enter a facility and information previously submitted is readily available. The provider can simply apply updates and make adjustments to the information as necessary. This saves the health care provider time and the organization’s information system space. Additionally, this decrease of data input can lead to improved quality and patient safety as fewer diagnostic errors associated with navigating a patient’s information are less likely to occur.

Consider the following scenario:

You have recently been hired by a small community hospital as a nurse informaticist. One of your first responsibilities is to help to convert records to an electronic format. You decide to address the process of ordering medicine for patients and you need to develop a database to address the issue. Currently all of the patient information is contained in an Excel spreadsheet, which contains the following categories: PATIENT ORDER, PATIENT medical record number (MRN), PATIENT Name, Order Number, MEDICATION Name, MEDICATION Description, Quantity, PATIENT Address, and Date Ordered. In designing your database, you need to normalize the data in order to remove redundancies and duplications. What approach will you take to normalize the data?

Note: A PATIENT can have multiple orders but an order can be for only one MEDICATION. Patient medical record number (MRN) and Order Number are the primary keys.

To prepare:

• Review the information in your course text, Database Systems: Design, Implementation, and Management  on how to normalize data.
  • What form of normalization would use (1NF, 2NF, 3NF)?
  • Illustrate the normalized form for PATIENT ORDER.
• Reflect on the issues you encountered as you attempted to normalize the list.
• Consider the consequences of not normalizing data.

By Day 3

Post a brief description of how you would normalize the data from the scenario and your rationale. Describe the challenges that you encountered in determining how to normalize the data. Explain the possible consequences of failing to normalize data.

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:

• Ask a probing question, substantiated with additional background information, evidence, or research.
• Offer and support an alternative perspective using readings from the classroom or from your own research in the Walden Library.
• Validate an idea with your own experience and additional research.

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