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KMID : 1100520190250020124
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Healthcare Informatics Research
2019 Volume.25 No. 2 p.124 ~ p.130
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Risk Factor Analysis of Extended Opioid Use after Coronary Artery Bypass Grafting: A Clinical Data Warehouse-Based Study
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Kang Ji-Won
Kim Jae-Hun
Lee Kyung-Hyun
Lee Woo-Seok
Chang Hyoung-Woo
Kim Jun-Sung
Park Kay-Hyun
Lim Cheong
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Abstract
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Objectives: A clinical data warehouse (CDW) is part of our hospital information system, and it provides user-friendly ‘data search and extraction’ interfaces for query composition. We carried out a risk factor analysis for the extended use of opioids after coronary artery bypass grafting (CABG), taking advantage of the CDW system.
Methods: From 2015 to 2017, clinical data from 461 patients who had undergone either isolated or concomitant CABG were extracted using the CDW; the extracted data included baseline patient characteristics, various examination results, and opioid prescription information. Supplementary data that could not be extracted with the CDW were collected via manual review of the electronic medical records.
Results: Data from a total of 447 patients were analyzed finally. The mean patient age was 66.8 ± 10.9 years, 332 patients (74%) were male, and 235 patients (53%) had diabetes. Among the 447 patients, 90 patients (20.1%) took some type of opioid at the 15th postoperative day. An oral rapid-acting agent was the most frequently used opioid (83%). In the risk factor analysis for extended opioid use, duration of operation was the only significant risk factor (odds ratio = 1.004; 95% confidence interval, 1.001?1.007; p = 0.008).
Conclusions: Longer operation time was associated with the risk of extended opioid use after CABG. CDW was a helpful tool for extracting mass clinical data rapidly, but to maximize its utility, the data should be checked carefully as they are entered in the system so that post-processing can be minimized. Further refinement of the clinical data input and output interface is warranted.
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KEYWORD
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Coronary Artery Bypass, Opioid, Pain, Database Management Systems, Data Warehousing
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