Developing a scalable, cross-facility-based therapeutic decision reminder engine

Cheng Yi Yang, Ming Chieh Tsai, Ray Jade Chen, Yu Sheng Lo, Lan Ying Kang, Chien Tsai Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationWCECS 2016 - World Congress on Engineering and Computer Science 2016
PublisherNewswood Limited
Pages201-207
Number of pages7
Volume2225
ISBN (Electronic)9789881404718
Publication statusPublished - 2016
Event2016 World Congress on Engineering and Computer Science, WCECS 2016 - San Francisco, United States
Duration: Oct 19 2016Oct 21 2016

Other

Other2016 World Congress on Engineering and Computer Science, WCECS 2016
CountryUnited States
CitySan Francisco
Period10/19/1610/21/16

Fingerprint

Engines
Health insurance
Load testing

Keywords

  • CDS
  • CPOE
  • Load testing
  • Medication errors
  • NHf-PharmaCloud

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

Cite this

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. In WCECS 2016 - World Congress on Engineering and Computer Science 2016 (Vol. 2225, pp. 201-207). Newswood Limited.

Developing a scalable, cross-facility-based therapeutic decision reminder engine. / Yang, Cheng Yi; Tsai, Ming Chieh; Chen, Ray Jade; Lo, Yu Sheng; Kang, Lan Ying; Liu, Chien Tsai.

WCECS 2016 - World Congress on Engineering and Computer Science 2016. Vol. 2225 Newswood Limited, 2016. p. 201-207.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yang, CY, Tsai, MC, Chen, RJ, Lo, YS, Kang, LY & Liu, CT 2016, Developing a scalable, cross-facility-based therapeutic decision reminder engine. in WCECS 2016 - World Congress on Engineering and Computer Science 2016. vol. 2225, Newswood Limited, pp. 201-207, 2016 World Congress on Engineering and Computer Science, WCECS 2016, San Francisco, United States, 10/19/16.
Yang CY, Tsai MC, Chen RJ, Lo YS, Kang LY, Liu CT. Developing a scalable, cross-facility-based therapeutic decision reminder engine. In WCECS 2016 - World Congress on Engineering and Computer Science 2016. Vol. 2225. Newswood Limited. 2016. p. 201-207
Yang, Cheng Yi ; Tsai, Ming Chieh ; Chen, Ray Jade ; Lo, Yu Sheng ; Kang, Lan Ying ; Liu, Chien Tsai. / Developing a scalable, cross-facility-based therapeutic decision reminder engine. WCECS 2016 - World Congress on Engineering and Computer Science 2016. Vol. 2225 Newswood Limited, 2016. pp. 201-207
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