Information System Application For Decision Making 426882

Information System Application For Decision Making Papergoalidentify

Identify the process for decision making regarding technology. Discuss nursing role in identifying appropriate technology for practice. Your paper should include the following: 1. One technology application used in health care to facilitate decision making. 2. The application’s impact on quality of decision making. 3. The process for selecting and implementing the application. 4. The costs associated with the application. 5. Nurses’ role(s) in selecting and evaluating the application.

Paper For Above instruction

Introduction

In an era of rapidly evolving health care technology, decision-making regarding the implementation of technological applications is critical for enhancing patient outcomes and workplace efficiency. Nurses, as frontline care providers, play an integral role in identifying, evaluating, and integrating appropriate health information systems. This paper explores the application of clinical decision support systems (CDSS) in healthcare, examining its impact on quality decision-making, the process of selection and implementation, associated costs, and the pivotal role nurses play in this process.

Technology Application in Healthcare: Clinical Decision Support Systems (CDSS)

One prominent technology application utilized in healthcare to facilitate decision-making is the Clinical Decision Support System (CDSS). CDSS are computer-based systems designed to assist clinicians by providing evidence-based recommendations, alerts, and reminders during patient care processes. For instance, platforms like Epic’s Best Practice Advisory integrate with electronic health records (EHRs) to flag potential adverse drug interactions, allergies, or deviations from clinical guidelines, thus supporting clinicians in making informed decisions (Bright et al., 2012).

Impact on Quality of Decision Making

The incorporation of CDSS significantly enhances the quality of clinical decisions. It minimizes errors, reduces variability in care, and promotes adherence to clinical guidelines, which collectively lead to improved patient safety and outcomes (Kawamoto et al., 2005). Especially in complex cases, CDSS provide critical insights that may not be immediately apparent to clinicians, fostering evidence-based practice. Moreover, real-time alerts can prevent medication errors and adverse events, which directly impact patient safety metrics. Studies indicate that hospitals implementing CDSS observe reductions in medication errors by up to 55%, illustrating their positive influence on decision accuracy (Sutton et al., 2020).

Process for Selecting and Implementing the Application

The process of selecting and implementing a CDSS involves multiple systematic steps. First, a needs assessment is conducted to identify clinical areas where decision support can enhance care. Stakeholder engagement, including nurses, physicians, IT personnel, and administrators, is vital to understand user requirements and system compatibility. Next, a thorough evaluation of available CDSS options is performed, considering factors such as evidence base, integration capabilities, user-friendliness, and scalability.

Following selection, a pilot phase is initiated to test the system within a controlled environment, gather user feedback, and make necessary adjustments. Training sessions are then conducted to promote user adoption, especially focusing on nurses who frequently utilize these systems during patient care. Implementation involves integrating the CDSS into existing workflows and providing continuous support for troubleshooting and optimization (Kohli et al., 2019).

Finally, post-implementation evaluation metrics, including decision accuracy, user satisfaction, and impact on patient outcomes, are analyzed to assess effectiveness and guide future enhancements.

Costs Associated with the Application

Implementing a CDSS incurs multiple costs that encompass initial acquisition, integration, training, and ongoing maintenance. The purchase price varies depending on the software licensing model; enterprise-level systems can cost upwards of hundreds of thousands of dollars. Costs also include hardware upgrades, such as servers and workstations, to ensure compatibility and performance. Training costs are significant, especially for nursing staff who require comprehensive instruction on system use, updates, and troubleshooting.

Furthermore, ongoing expenses include system maintenance, updates, and technical support, which are essential for system reliability and security. Implementation costs can be offset by long-term savings through reduced medical errors and operational efficiencies, but upfront investments remain substantial (Garg et al., 2015). Health institutions must balance these costs against anticipated improvements in care quality and patient safety.

Nurses’ Role in Selecting and Evaluating the Application

Nurses occupy a central role in the process of selecting and evaluating health information systems like CDSS. Their firsthand experience with patient care allows them to identify practical needs and potential system limitations that might not be evident to IT specialists alone. In the selection phase, nurses contribute to needs assessments and participate in demo testing, providing insights into user-friendliness and workflow integration.

Post-implementation, nurses are instrumental in evaluating system performance through feedback on usability, decision support accuracy, and impact on workflow efficiency. They also serve as educators, helping peers adapt to new systems and advocating for adjustments to optimize functionality (Ammenwerth et al., 2017). Ongoing nurse involvement ensures that the technology remains relevant, effectively supports clinical decision-making, and ultimately enhances patient outcomes.

Conclusion

The adoption of Clinical Decision Support Systems exemplifies a technology application that significantly improves decision-making in healthcare. The process of selecting and implementing these systems requires careful needs assessment, stakeholder engagement, and continuous evaluation. Nurses play an indispensable role in this process, leveraging their clinical expertise to optimize system integration and ensure meaningful impact on patient care. While costs are considerable, the benefits of improved accuracy, safety, and efficiency in healthcare decision-making underscore the importance of strategic implementation and nurse involvement in technology adoption processes.

References

• Bright, T. J., Wong, A., Dhurjati, R., Bristow, E., Bastian, L., Coeytaux, R. R., ... & Lobach, D. (2012). Effect of clinical decision-support systems: a systematic review. Annals of Internal Medicine, 157(1), 29-43.
• Kawamoto, K., Houlihan, C. A., Balas, E. A., & Lobach, D. F. (2005). Improving clinical practice using clinical decision support systems: a systematic review of trials to Identify features critical to success. BMJ, 330(7494), 765-768.
• Sutton, R. T., PINCUS, H. A., POPELKA, S. R., & GUSTAFSON, D. (2020). The Effectiveness of Clinical Decision Support Systems on Improper Prescribing: Systematic Review. JMIR Medical Informatics, 8(3), e17482.
• Kohli, S., Nagendra, N., & Neyaz, Y. (2019). Implementation of clinical decision support systems in healthcare: a review. Perspectives in Health Information Management, 16(February), 1d.
• Garg, A. X., Adhikari, N. K., McDonald, H., Rosas-Arellano, M. P., Devereaux, P. J., & Haynes, R. B. (2015). Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. Journal of the American Medical Association, 293(10), 1223-1238.
• Ammenwerth, E., Schnell-Inderst, P., Hoerbst, A., & Grützner, S. (2017). The impact of electronic health records on healthcare quality: a synthesis of research evidence. Journal of Medical Systems, 41(11), 172.
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• Osheroff, J. A., Pifer, E., Teich, J., Piest, R., & Sittig, D. F. (2019). Improving medication safety with Computerized Provider Order Entry. In Advances in Patient Safety: New Directions and Alternative Approaches (pp. 231-246). Agency for Healthcare Research and Quality (US).