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KMID : 0311120220630010008
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Yonsei Medical Journal
2022 Volume.63 No. 1 p.8 ~ p.15
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Physician Knowledge Base: Clinical Decision Support Systems
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Kim Si-Ra
Kim Eung-Hee
Kim Hun-Sung
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Abstract
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With the introduction of electronic medical records (EMRs), it has become possible to accumulate massive amounts of qualitative medical data. As such, EMRs have become increasingly used in clinical decision support systems (CDSSs). While CDSSs aim to reduce medical errors normally occurring in the process of treating patients by physicians, technical maturity and the completeness of CDSSs do not meet standards for medical use yet. As data further accumulates, CDSS algorithms must be continuously updated to allow CDSSs to perform their core functions. Doing so, however, requires extensive time and manpower investments. In current practice, computational systems already perform a wide variety of functions in medical settings to allow medical staff to focus on other tasks. However, no prior research has evaluated the potential effectiveness of future CDSSs nor analyzed possibilities for their further development. In this article, we evaluate CDSS technology with the consideration that medical staff also understand the core functions of such systems.
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KEYWORD
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Artificial intelligence, decision support systems, clinical, deep learning
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