Browse > Article
http://dx.doi.org/10.4040/jkan.2014.44.3.294

Implementation of Ontology-based Clinical Decision Support System for Management of Interactions Between Antihypertensive Drugs and Diet  

Park, Jeong-Eun (College of Nursing, Kyungpook National University)
Kim, Hwa-Sun (Department of Medical Information Technology, Daegu Haany University)
Chang, Min-Jung (Yonsei Institute of Pharmaceutical Sciences, College of Pharmacy, Yonsei University)
Hong, Hae-Sook (College of Nursing, Kyungpook National University)
Publication Information
Journal of Korean Academy of Nursing / v.44, no.3, 2014 , pp. 294-304 More about this Journal
Abstract
Purpose: The influence of dietary composition on blood pressure is an important subject in healthcare. Interactions between antihypertensive drugs and diet (IBADD) is the most important factor in the management of hypertension. It is therefore essential to support healthcare providers' decision making role in active and continuous interaction control in hypertension management. The aim of this study was to implement an ontology-based clinical decision support system (CDSS) for IBADD management (IBADDM). We considered the concepts of antihypertensive drugs and foods, and focused on the interchangeability between the database and the CDSS when providing tailored information. Methods: An ontology-based CDSS for IBADDM was implemented in eight phases: (1) determining the domain and scope of ontology, (2) reviewing existing ontology, (3) extracting and defining the concepts, (4) assigning relationships between concepts, (5) creating a conceptual map with CmapTools, (6) selecting upper ontology, (7) formally representing the ontology with Protege (ver.4.3), (8) implementing an ontology-based CDSS as a JAVA prototype application. Results: We extracted 5,926 concepts, 15 properties, and formally represented them using Protege. An ontology-based CDSS for IBADDM was implemented and the evaluation score was 4.60 out of 5. Conclusion: We endeavored to map functions of a CDSS and implement an ontology-based CDSS for IBADDM.
Keywords
Ontology; Clinical decision support system (CDSS); Interactions between antihypertensive drug and diet;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Mahmud FB, Yusof NM, Shahrul AN. Ontological based clinical decision support system (CDSS) for weaning ventilator in intensive care unit (ICU). IEEE International Conference on Electrical Engineering and Informatics (ICEEI); 2011 July 17-19; Bandung, Indonesia: IEEE. http://dx.doi.org/10.1109/ICEEI.2011.6021506
2 KIMS. Interaction [Internet]. Seoul: KIMS OnLine; 2010 [cited 2012 December 10]. Available from: http://www.kimsonline.co.kr/.
3 KOICD. KCD tree Daejeon: Frugal Solution; 2013 [cited 2012 December 10]. Available from: http://www.koicd.kr/.
4 Park JE, Chung KA, Cho H, Kim HS. Construction of the nursing diagnosis ontology in obstetric and gynecologic nursing unit using nursing process and SNOMED CT. Korean Journal of Women Health Nursing. 2013;19(1):1-12. http://dx.doi.org/10.4069/kjwhn.2013.19.1.1   DOI   ScienceOn
5 Protege3.4.7 [Online Database]. Stanford University. 2013 [cited December 7]. Available from: http://www.stanford.edu/.
6 Rho SG, Park JS. Ontology. 3rd ed. Seoul: Good's Toy; 2009.
7 The Florida Institute for Human and Machine Cognition. CmapTools [Internet]. Pensacola, FL: Author 2003 [cited 2013 December 17]. Available from: http://cmap.ihmc.us/.
8 The International Health Terminology Standards Development Organisation. SNOMED CT [Internet]. Copenhagen, DK: Author; 2010 [cited 2013 December 17]. Available from: http://www.ihtsdo.org/snomed-ct.
9 Kehagias DD, Papadimitriou I, Hois J, Tzovaras D, Bateman J. A methodological approach for ontology evaluation and refinement. ASK-IT International Conference; 2008 June 26-27; Nuremberg, De.
10 Wyatt J, Spiegelhalter D. Field trials of medical decision-aids: Potential problems and solutions. Proceedings of the Annual Symposium on Computer Applications in Medical Care. 1991:3-7.
11 Weiss SM, Kulikowski CA, Safir A. A model-based consultation system for the long-term management of glaucoma. In: The International Joint Conferences on Artificial Intelligence, editor. Proceedings of the 5th international joint conference on artificial intelligence: Volume 2. San Francisco, CA: Morgan Kaufmann Publishers Inc.; 1977. p. 826-832.
12 Taylor P. From patient data to medical knowledge: The principles and practice of health informatics. London, UK: Blackwell BMJ Books; 2006.
13 Buchanan BG, Shortliffe EH. Rule-based expert systems: The MYCIN experiments of the stanford heuristic programming project. Reading, MA: Addison-Wesley Publishing Company; 1984.
14 Schnipper JL, Linder JA, Palchuk MB, Yu DT, McColgan KE, Volk LA, et al. Effects of documentation-based decision support on chronic disease management. American Journal of Managed Care. 2010;16(12 Suppl HIT):SP72-SP81.
15 Cobos A, Vilaseca J, Asenjo C, Pedro-Botet J, Sanchez E, Val A, et al. Cost effectiveness of a clinical decision support system based on the recommendations of the european society of cardiology and other societies for the management of hypercholesterolemia: Report of a cluster-randomized trial. Disease Management and Health Outcomes. 2005;13(6):421-432. http://dx.doi.org/10.2165/00115677-200513060-00007   DOI   ScienceOn
16 Bassa A, del Val M, Cobos A, Torremade E, Bergonon S, Crespo C, et al. Impact of a clinical decision support system on the management of patients with hypercholesterolemia in the primary healthcare setting. Disease Management and Health Outcomes. 2005;13(1):65-72. http://dx.doi.org/10.2165/00115677-200513010-00007   DOI   ScienceOn
17 Roberts LL, Ward MM, Brokel JM, Wakefield DS, Crandall DK, Conlon P. Impact of health information technology on detection of potential adverse drug events at the ordering stage. American Journal of Health-System Pharmacy. 2010;67(21):1838-1846. http://dx.doi.org/10.2146/ajhp090637   DOI   ScienceOn
18 Abas HI, Yusof MM, Moah SAM. The application of ontology in a clinical decision support system for acute postoperative pain management. 2011 International Conference on Semantic Technology and Information Retrieval; 2011 June 28-29; Putrajaya, MY: IEEE.
19 Kuziemsky CE, Lau F. A four stage approach for ontology-based health information system design. Artificial Intelligence in Medicine. 2010;50(3):133-148. http://dx.doi.org/10.1016/j.artmed.2010.04.012   DOI   ScienceOn
20 Ng KH, Stanley AG, Williams B. Hypertension. Medicine. 2010;38 (8):403-408. http://dx.doi.org/10.1016/j.mpmed.2010.05.001   DOI
21 Jauregui-Garrido B, Jauregui-Lobera I. Interactions between antihypertensive drugs and food. Nutricion Hospitalaria. 2012;27(6):1866-1875. http://dx.doi.org/10.3305/nh.2012.27.6.6127
22 Izzo AA, Ernst E. Interactions between herbal medicines and prescribed drugs: An updated systematic review. Drugs. 2009;69(13):1777-1798. http://dx.doi.org/10.2165/11317010-000000000-00000   DOI   ScienceOn
23 Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: A systematic review of trials to identify features critical to success. BMJ: British Medical Journal. 2005;330(7494):765. http://dx.doi.org/10.1136/bmj.38398.500764.8F   DOI   ScienceOn
24 Bushra R, Alsam N, Khan AY. Food-drug interactions. Oman Medical Journal. 2011;26(2):77-83. http://dx.doi.org/10.5001/omj.2011.21   DOI   ScienceOn
25 Abbaszadeh A, Eskandari M, Borhani F. Changing the care process: A new concept in Iranian rural health care. Asian Nursing Research. 2013;7(1):38-43.   DOI   ScienceOn
26 Schnipper JL, Linder JA, Palchuk MB, Yu DT, McColgan KE, Volk LA, et al. Effects of documentation-based decision support on chronic disease management. American Journal of Managed Care. 2010;16(12 Suppl HIT):SP72-SP81.
27 Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: A systematic review. JAMA: the Journal of the American Medical Association. 2005;293(10):1223-1238. http://dx.doi.org/10.1001/jama.293.10.1223   DOI   ScienceOn
28 Jani YH, Barber N, Wong IC. Characteristics of clinical decision support alert overrides in an electronic prescribing system at a tertiary care paediatric hospital. International Journal of Pharmacy Practice. 2011;19(5):363-366. http://dx.doi.org/10.1111/j.2042-7174.2011.00132.x   DOI   ScienceOn
29 Pearson SA, Moxey A, Robertson J, Hains I, Williamson M, Reeve J, et al. Do computerised clinical decision support systems for prescribing change practice? A systematic review of the literature (1990-2007). BMC Health Services Research. 2009;9:154. http://dx.doi.org/10.1186/1472-6963-9-154   DOI   ScienceOn
30 Walsh JM, McDonald KM, Shojania KG, Sundaram V, Nayak S, Lewis R, et al. Quality improvement strategies for hypertension management: A systematic review. Medical Care. 2006;44(7):646-657. http://dx.doi.org/10.1097/01.mlr.0000220260.30768.32   DOI   ScienceOn