- Volume 9 Issue 2
DOI QR Code
Development of Adverse Drug Event Surveillance System using BI Technology
BI기술을 적용한 약물부작용감시시스템 개발
- Published : 2009.02.28
In this study, we are analysing adverse drug events and proposing a technical structure of "adverse drug event surveillance system" using business intelligence technology, hoping that we can use the system commonly and actively. It is the recent trend to adopt both of electronic review and manual review process to surveil adverse drug events and this study construct CDW applying ETL in BI Technology. As the result of analysis, the data pool included 701 doctors who prescribed and 3059 patients(1528 male, 1531 female), of total 318,222 cases, 2,086cases(0.6%) were suspected as having adverse drug events. And the single type of T.bilirubin> 3mg/dL(ADE type-LabR0005) was the most common(548 among 2085 cases) within the framework of signals.
- L.T. Kohn, ,J.M. Corrgan, and M.S. Donaldson, " To Err is Human: Building a Safer Health System," Washington, DC: National Academy Press, 1999.
- 범희승, 박성희, 최진욱, 김춘배, "임상의사결정지원시스템의 약제부작용 감소 효과에 관한 메타분석", 대한의료정보학회지, 제8권, 제3호,pp.55-60, 2002.
- A.K. Jha, G.J. Kuperman, J.M. Teich, L.Lucian, S. Brian , R. Eve , E. Burdick, S.D. Lew , V.V. Martha , and D.W. Bates, "Identifying Adverse Drug Events: Development of a Computer-based Monitor and Comparison with Chart Review and Stimulated Voluntary Report", J Am Med Inform Assoc, Vol.5, Np.3,pp.305-314, 1998. https://doi.org/10.1136/jamia.1998.0050305
- H. Benjamin , L. Patrice , R.M. Pulling , D.W. Bates "A computerized method for identifying incidents associated with adverse drug events in outpatients," Int J Med Inform, Vol.6, No.1, pp.21-32, 2001.
- D.W. Bates, R.S. Evans, H.J. Murff, P.D. Stetson, L. Pizziferri, and G. Hripcsak "Detecting Adverse Events Using Information Technology," J Am Med Inform Assoc, Vol.10, No.2, pp.115-128, 2003. https://doi.org/10.1197/jamia.M1074
- G. James, J.J. Stephen , M. Anderson, T.J. Hunt "Evaluating the Capability of Information Technology to Prevent Adverse Drug Events," A Computer Simulation Approach, J Am Med Inform Assoc, Vol.9, No.5, pp.479-490, 2002. https://doi.org/10.1197/jamia.M1099
- A. Kusiak ,S. Shah , "Data Mining and Warehousing in Pharma Industry, In J.Wang(ed.)" Encyclopedia of Data Warehousing and Mining, Idea Group., Hershey, PA, pp.239-244, 2006
- 김이경, "Analysis of Inpatient Adverse Drug Events (ADEs) with Retrospective Review of Electronic Medical Records Using ADE Signals", 숙명여자대학교 임상약학대학원, 2004.
- 김혜영, "약물부작용 시그날을 이용한 약물부작용에 의한 입원 현황조사", 숙명여자대학교 임상약학대학원, 2004.
- H. Benjamin , L. Joshua , R.Jeffrey . " Using computerized data to identify adverse drug events in outpatients," J Am Med Inform Assoc, Vol.8, No.2, pp.254-266, 2001. https://doi.org/10.1136/jamia.2001.0080254
- H.J. Murff , V.L. Patel , G. Hripcsak , D. W.Bates, " Detecting adverse events for patient safety research: a review of current methodologies," J Biomed Inform, Vol.36, No.2, pp.131-143, 2003 https://doi.org/10.1016/j.jbi.2003.08.003
- P.M. Kilbridge , L. Alexander , A. Ahmad " Implementation of a system for computerized adverse drug event surveillance and intervention at an academic medical center," J Clin Outcomes Manage, Vol.13, No.2, pp.94-100, 2006.
- G.J. Kuperman, M.R. Reichley, T.C. Bailey "Using Commercial Knowledge Bases for Clinical Decision Support: Opportunities, Hurdles, and Recommendations," J Am Med Inform Assoc, Vol.13, No.3, pp.369-371, 2006. https://doi.org/10.1197/jamia.M2055
- E. Tyugu "Understanding knowledge architectures," Knowledge-Based Systems, Vol.19, No.1, pp.50-56, 2006(3). https://doi.org/10.1016/j.knosys.2005.07.006
- U. Yavuz, A.S. Hasiloglu, M.D. Kaya, R. Karcioglu, S. Ersoz, "Developing a marketing decision model using a knowledge-based system," Knowledge-Based Systems, Vol.18, No.(2-3), pp.125-129, 2005(4). https://doi.org/10.1016/j.knosys.2004.12.002
- Common data model for decision support system of adverse drug reaction to extract knowledge from multi-center database vol.17, pp.1, 2016, https://doi.org/10.1007/s10799-015-0240-6