Clinical Decision Support Systems
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?
Post by tomorrow 8/2/16 550 words in APA format and 3 references from the list below. Include the level one heading below:
1) a description of how you currently seek support for clinical decision making and how you determine the integrity of the information you gather.
2) Analyze the advantages and disadvantages of using computerized clinical decision support systems in clinical practice. Justify your response.
3) 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.
Required Resources
Coronel, C. & Morris, S. (2015). Database systems: Design, implementation, and management (11th ed.). Stamford, CT: Cengage Learning.
Chapter 13, “Business Intelligence and Data Warehouses” (review) (pp. 559–623)
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.
Retrieved from the Walden Library databases.
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.
Retrieved from the Walden Library databases.
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.
Retrieved from the Walden Library databases.
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.
Retrieved from the Walden Library databases.
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.
Retrieved from the Walden Library databases.
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.
Retrieved from the Walden Library databases.
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
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.
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.

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