NURS 6411 Week 10 Clinical Decision Support Systems Essay Assignment Paper

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NURS 6411 Week 10 Clinical Decision Support Systems Essay Assignment Paper

NURS 6411: Information and Knowledge Management | Week 10

The term clinical decision support system (CDS) refers to data analysis tools that help health care providers access the information they need to make evidence-based clinical decisions. With this technology, evidence-based practices are more easily and accurately applied. Consider for example, an individual who has sporadically sought medical help for abdominal pains and gastric distress symptoms over a span of five years. What might otherwise have appeared as a series of unrelated or minimal events could be analyzed collectively to reveal a potentially more serious condition such as Crohn’s disease or colitis?

This week, you assess features of clinical decision support systems that are available to health care professionals.

Learning Objectives

Students will:

  • Analyze the advantages and disadvantages of using clinical decision support systems
  • Evaluate the use of clinical decision support systems to improve patient care
  • Develop a database to answer a specific clinical question

Required Readings

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.

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

  • Chapter 13, “Business Intelligence and Data Warehouses” (pp. 589-636)This chapter explores data warehousing and how it improves organizational decision making. It also evaluates how, in some situations, the internet may affect data storage and assessments.

Wright, A., Sittig, D. F., Ash, J. S., Feblowitz, J., Meltzer, S., McMullen, C., …& Middleton, B. (2011). Development and evaluation of a comprehensive clinical decision support taxonomy: Comparison of front-end tools in commercial and internally developed electronic health record systems. Journal of American Medical Informatics Association, 18(3), 232–242

 

The authors of this article compare front-end and back-end clinical decision support (CDS) tools. They also evaluate the efficiency and accuracy of taxonomies in the design and implementation of EHR system features.

Souza, N. M., Sebaldt, R. J., Mackay, J. A., Prorok, J. C., Weise-Kelly, L., Navarro, …& Haynes, R. B. (2011). Computerized clinical decision support systems for primary preventive care: A decision-maker-researcher partnership systematic review of effects on process of care and patient outcomes. Implementation Science, 6(1), 87–100.

In this article, the authors explore applied computerized clinical decision support systems (CCDSSs). In addition, they evaluate how much these systems improved drug prescription processes and patient care outcomes.

Roshanov, P. S., Misra, S., Gerstein, H. C., Garg, A. X., Sebaldt, R. J., Mackay, J. A., …& Haynes, R. B. (2011). Can computerized clinical decision support systems improve practitioners’ diagnostic test ordering behavior? A decision-maker-researcher partnership systematic review. Implementation Science, 6(88), 1–12.

The authors of this article explore the relationship between CCDSSs and effective diagnostic testing. Through their decision-maker-researcher partnership systemic review, they evaluate efforts to improve diagnostic testing through data collection and assessment requirement procedure and EHRs.

Frisher, M., Short, D., & Bashford, J. (2010). Determining patient characteristics for decision analysis support systems using anonymized electronic patient records. Health Informatics Journal, 16(1), 49–57.

 

This article reports on a study conducted with stroke patients that examined how decision analysis support systems can be applied. The authors discuss how evidence-based consultations of patients and data analysis can improve decision making.

Huryk, L. A. (2012). Information systems and decision support systems. American Journal of Nursing, 112(1), 62–65.

The Health Information Technology for Economic and Clinical Health (HITECH) Act has encouraged the implementation of technologies in evidence-based practice, diagnostics, and research. One result of this is the growing reliance on decision support systems in patient care. The author of this article examines how the nursing field and curricula are adapting to meet this change in practice.

Ensuring data integrity. (2009). Nature Neuroscience, 12(10), 1205.

 

This article explores methods that health care organizations can employ to ensure the integrity of collected and stored data.

Open Clinical: Knowledge Management for Medical Care. (2011). Decision support systems. Retrieved from http://www.openclinical.org/dss.html

 

This site explores decision support systems and their functions in health care. It also explores how each organization can integrate decision support systems to their own task sets.

Required Media

Laureate Education, Inc. (Executive Producer). (2012). Clinical decision support systems. Baltimore, MD: Author.

Note: The approximate length of this media piece is 11 minutes.

Dr. Patricia Abbott, a highly experienced nurse, nurse educator, and informatics researcher, describes decision support systems and provides health care-based examples. She also explains how critical it is to involve nurses in the development of health care standards.

Decision support systems were first designed and implemented in the corporate world to support business management. The integration of support systems into health care organizations brings a sharpened analysis capacity to data warehousing and data mining. This refined data analysis capability can lead to improved patient care and diagnoses through evaluation of various symptoms, prediction of certain drug interaction outcomes, and much more.

In this Discussion, you explore the use of clinical decision support systems and consider their value in assisting advanced practice nurses in making informed decisions and providing quality health care.

To prepare:

  • Review the information in the Learning Resources focusing on the use of clinical decision support systems.
  • Consider where you seek support for clinical decisions. Do you seek advice from other health care professionals in your organization? Do you use computerized clinical decision support systems? Do you perform your own research? Assess the advantages and disadvantages of each approach.
  • Reflect on how decision support technologies, including databases, might assist nurses in clinical practice.
  • Consider how you can validate the integrity of the data you are using in a clinical decision support system.
  • Peruse the information presented at the Open Clinical website presented in this week’s Learning Resources. Locate an article that focuses on how clinical decision support systems can be used to support or improve patient care. How does the information in the article align with or differ from your own experiences?

By Day 3

Post a description of how you currently seek support for clinical decision making and how you determine the integrity of the information you gather. Analyze the advantages and disadvantages of using computerized clinical decision support systems in clinical practice. Justify your response. Finally, summarize the article you selected from the Open Clinical website and include an evaluation of how computerized clinical decision support systems can be used to improve care.

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.
  • Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
  • Offer and support an alternative perspective using readings from the classroom or from your own research in the Walden Library.
  • Make a suggestion based on additional evidence drawn from readings or after synthesizing multiple postings.

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