Medication errors are expensive and sometimes costly to healthcare systems, patients and their families, and clinicians. The National Health Insurance of Taiwan provided a NHI-PharmaCIoud web-based database that contains the most complete drug histories of patients across different healthcare facilities in Taiwan. Several research studies have reported that adoption of a computerized physician order entry system (CPOE) with clinical decision support (CDS) function by medication prescribers can prevent medication errors and improve medication safety in patients; however, new drugs and drug-related knowledge are being quickly and frequently released. Thus, the same pharmacological mechanism of different drugs can be hard to detect; furthermore, there is a lack of patient-centered, integrated medication history that is necessary to prescribe the correct medication. Therefore, prevention of medication errors remains difficult for the clinical staff. To flexibly add more checking rules and improve drug-use safety among patients, we developed a scalable, expandable decision reminder solution (Therapeutic Decision Reminder Engine; TDRE) based on the NHI-PharmaCIoud in the Taipei Medical University Hospital, which would support the clinical staff and more efficiently prevent medication errors. In addition, to ensure an effective TDRE performance in future implementations, we also conducted load testing to determine the maximum workload that TDRE could support. The test results showed that TDRE was effective and able to support our expected service quantity.
|主出版物標題||WCECS 2016 - World Congress on Engineering and Computer Science 2016|
|出版狀態||已發佈 - 2016|
|事件||2016 World Congress on Engineering and Computer Science, WCECS 2016 - San Francisco, 美国|
持續時間: 十月 19 2016 → 十月 21 2016
|其他||2016 World Congress on Engineering and Computer Science, WCECS 2016|
|期間||10/19/16 → 10/21/16|
ASJC Scopus subject areas
- Computer Science (miscellaneous)
Yang, C. Y., Tsai, M. C., Chen, R. J., Lo, Y. S., Kang, L. Y., & Liu, C. T. (2016). Developing a scalable, cross-facility-based therapeutic decision reminder engine. 於 WCECS 2016 - World Congress on Engineering and Computer Science 2016 (卷 2225, 頁 201-207). Newswood Limited.