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Analysis of Clinical Decision Support Systems

Although there are various versions of CDSS in use today, the three major types are diagnostic support systems MYCIN, Computerized Physician Order Entry (CPOE), and Arden Syntax. Developed in the 1970s, the MYCIN helps clinicians choose antibiotics for such diseases as meningitis and bacteremia (Sutton et al., 2020). When using the system, clinicians need to enter facts about the physical findings, history, and laboratory results. Then, the system gives back patient-specific recommendations for the appropriate antibiotics.

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The computerized physician order entry (CPOE) is a technology whose function is to enable tailored information during clinical decisions. The idea is to automate and homogenize the ordering process (Sutton et al., 2020). In addition, data from computer records help in guiding quality management efforts (Sutton et al., 2020).

The Arden Syntax CDSS is a quasi-programming language whose function is to help in encoding decision rules into a format that a computer system can read (Sutton et al., 2020). For example, a lab technician can run the electrolyte from a patient’s blood sample. The results are entered into the lab information system, which sends the data to the hospital IS, which contains the patient ID number and the test results (Sutton et al., 2020). The information then goes to the centralized computer application that manages the hospital to compare with relevant rules.

MYCIN is a rule-based system that makes diagnosis and treatment of infections faster as it makes it easy to determine the appropriate antibiotic for the specific disease. However, it is difficult to maintain and incorporate the system into the workflow of a clinician (Sutton et al., 2020). The CPOE is successful in a wide variety of settings, such as preventing errors in drug dose and interaction. It supports standardized identification, tracking, and reporting of patient safety data (Sutton et al., 2020). However, it is often costly and difficult to maintain in a specific hospital setting (Sutton et al., 2020). The Arden Syntax is very effective in the practical implementation of CDS systems because of its actively developed standard, flexibility in list handling, and ease of syntax readability (Sutton et al., 2020). However, it requires technical integration of the CDS system, especially with heterogeneous health information systems.

Reference

Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., & Kroeker, K. I. (2020). An overview of clinical decision support systems: Benefits, risks, and strategies for success. NPJ Digital Medicine, 3(1), 1-10. Web.

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StudyCorgi. (2022, November 13). Analysis of Clinical Decision Support Systems. Retrieved from https://studycorgi.com/analysis-of-clinical-decision-support-systems/

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StudyCorgi. 2022. "Analysis of Clinical Decision Support Systems." November 13, 2022. https://studycorgi.com/analysis-of-clinical-decision-support-systems/.

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StudyCorgi. (2022) 'Analysis of Clinical Decision Support Systems'. 13 November.

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