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KMID : 1011320210130010024
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Journal of Pharmacoepidemiology and Risk Management
2021 Volume.13 No. 1 p.24 ~ p.29
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Improving the Prescription System to Prevent Adverse Drug Reactions
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Kim Hyun-Jee
Moon Mi-Ra
Kim Hyun-Hwa
Park Soo-Been
Kang Rae-Young
Park Ga-Yoon
Kang Hye-Ryun
Kang Dong-Yoon
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Abstract
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Objective: Many medical institutions provide warnings when physicians prescribe medication with a history of adverse reaction to prevent adverse drug reaction. If the range of warning is too narrow, it cannot prevent adverse drug reactions due to a similar structure and component. However, if the range is too wide it provides too many warnings resulting in alert fatigue. In our study, we upgraded the algorithm for adverse drug reaction warning to lower the overall frequency of alert warning but improve the clinical significance of alerts.
Methods: The authors upgraded the alert algorithm to include information about the potential for cross-reactivity, past adverse drug reaction type, severity, and causality. To verify the effect of the upgraded system, we compared the frequency of alerts of six months before and after the system upgrade, a satisfaction of physicians using the upgraded prescription system, and recurrence of drug allergy.
Results: After six months of upgraded prescription system, the number of alerts decreased significantly from 10,474 cases per month to 1,060 cases per month (p ＜ 0.05). The recurrence of drug allergy decreased by 53%, from 57 cases to 27 cases per 6 months. Survey results show that physician satisfaction improved from 3.48 points to 4.15 points and improvement in patient care improved from 3.80 points to 4.33 points significantly (p ＜ 0.05).
Conclusion: By reducing the number of clinically less important warnings, the upgraded prescription system can raise the interest in clinically significant adverse reactions and it can be effective in preventing recurrence of adverse drug reactions.
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KEYWORD
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Drug-related side effects and adverse reactions, Drug hypersensitivity, Cross reactions, Medical order entry systems, Clinical decision supporting systems
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