IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v11y2014i2p1369-1383d32529.html
   My bibliography  Save this article

Detection of Potential Drug-Drug Interactions for Outpatients across Hospitals

Author

Listed:
  • Yu-Ting Yeh

    (Graduate Institute of Medical Sciences, College of Medicine, Taipei Medical University, 250 Wuhsing St., Taipei 110, Taiwan
    Information Technology Office, Shuang Ho Hospital, Taipei Medical University, 291 Zhongzheng Rd., New Taipei City 235, Taiwan)

  • Min-Hui Hsu

    (Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250 Wuhsing St., Taipei 110, Taiwan)

  • Chien-Yuan Chen

    (Department of Information Management, Wan Fang Hospital, Taipei Medical University, Section 3, 111 HsingLong Rd., Taipei 116, Taiwan)

  • Yu-Sheng Lo

    (Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250 Wuhsing St., Taipei 110, Taiwan)

  • Chien-Tsai Liu

    (Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250 Wuhsing St., Taipei 110, Taiwan)

Abstract

The National Health Insurance Administration (NHIA) has adopted smart cards (or NHI-IC cards) as health cards to carry patients’ medication histories across hospitals in Taiwan. The aims of this study are to enhance a computerized physician order entry system to support drug-drug interaction (DDI) checking based on a patient’s medication history stored in his/her NHI-IC card. For performance evaluation, we developed a transaction tracking log to keep track of every operation on NHI-IC cards. Based on analysis of the transaction tracking log from 1 August to 31 October 2007, physicians read patients’ NHI-IC cards in 71.01% (8,246) of patient visits; 33.02% (2,723) of the card reads showed at least one medicine currently being taken by the patient, 82.94% of which were prescribed during the last visit. Among 10,036 issued prescriptions, seven prescriptions (0.09%) contained at least one drug item that might interact with the currently-taken medicines stored in NHI-IC cards and triggered pop-up alerts. This study showed that the capacity of an NHI-IC card is adequate to support DDI checking across hospitals. Thus, the enhanced computerized physician order entry (CPOE) system can support better DDI checking when physicians are making prescriptions and provide safer medication care, particularly for patients who receive medication care from different hospitals.

Suggested Citation

  • Yu-Ting Yeh & Min-Hui Hsu & Chien-Yuan Chen & Yu-Sheng Lo & Chien-Tsai Liu, 2014. "Detection of Potential Drug-Drug Interactions for Outpatients across Hospitals," IJERPH, MDPI, vol. 11(2), pages 1-15, January.
  • Handle: RePEc:gam:jijerp:v:11:y:2014:i:2:p:1369-1383:d:32529
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/11/2/1369/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/11/2/1369/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marcia R. Friesen & Carole Hamel & Robert D. McLeod, 2013. "A mHealth Application for Chronic Wound Care: Findings of a User Trial," IJERPH, MDPI, vol. 10(11), pages 1-16, November.
    2. Wang, Ming-Jye & Lin, Shu-Ping, 2010. "Study on doctor shopping behavior: Insight from patients with upper respiratory tract infection in Taiwan," Health Policy, Elsevier, vol. 94(1), pages 61-67, January.
    3. Eric S. Donkor & Patience B. Tetteh-Quarcoo & Patrick Nartey & Isaac O. Agyeman, 2012. "Self-Medication Practices with Antibiotics among Tertiary Level Students in Accra, Ghana: A Cross-Sectional Study," IJERPH, MDPI, vol. 9(10), pages 1-11, October.
    4. Chung-Feng Liu & Yung-Chieh Tsai & Fong-Lin Jang, 2013. "Patients’ Acceptance towards a Web-Based Personal Health Record System: An Empirical Study in Taiwan," IJERPH, MDPI, vol. 10(10), pages 1-18, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gow-Lieng Tseng & Cheng-Yu Chen, 2015. "Doctor-Shopping Behavior among Patients with Eye Floaters," IJERPH, MDPI, vol. 12(7), pages 1-10, July.
    2. Ming-Hwai Lin & Hsiao-Ting Chang & Chun-Yi Tu & Tzeng-Ji Chen & Shinn-Jang Hwang, 2015. "Doctor-Shopping Behaviors among Traditional Chinese Medicine Users in Taiwan," IJERPH, MDPI, vol. 12(8), pages 1-11, August.
    3. Yuan Tang & Yu-Tao Yang & Yun-Fei Shao, 2019. "Acceptance of Online Medical Websites: An Empirical Study in China," IJERPH, MDPI, vol. 16(6), pages 1-22, March.
    4. Jae-Hyun Kim & Eun-Cheol Park, 2019. "Can diabetes patients seeking a second hospital get better care? Results from nested case–control study," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-10, January.
    5. Zykova, Yana V. & Mannberg, Andrea & Myrland, Øystein, 2022. "Effects of ‘doctor shopping’ behaviour on prescription of addictive drugs in Sweden," Social Science & Medicine, Elsevier, vol. 296(C).
    6. Yu-Hua Yan & Chih-Ming Kung & Horng-Ming Yeh, 2019. "The Impacts of the Hierarchical Medical System on National Health Insurance on the Resident’s Health Seeking Behavior in Taiwan: A Case Study on the Policy to Reduce Hospital Visits," IJERPH, MDPI, vol. 16(17), pages 1-10, August.
    7. Mengling Yan & Hongying Tan & Luxue Jia & Umair Akram, 2020. "The Antecedents of Poor Doctor-Patient Relationship in Mobile Consultation: A Perspective from Computer-Mediated Communication," IJERPH, MDPI, vol. 17(7), pages 1-16, April.
    8. Adi Alsyouf & Abdalwali Lutfi & Nizar Alsubahi & Fahad Nasser Alhazmi & Khalid Al-Mugheed & Rami J. Anshasi & Nora Ibrahim Alharbi & Moteb Albugami, 2023. "The Use of a Technology Acceptance Model (TAM) to Predict Patients’ Usage of a Personal Health Record System: The Role of Security, Privacy, and Usability," IJERPH, MDPI, vol. 20(2), pages 1-24, January.
    9. Chung-Hung Tsai, 2014. "Integrating Social Capital Theory, Social Cognitive Theory, and the Technology Acceptance Model to Explore a Behavioral Model of Telehealth Systems," IJERPH, MDPI, vol. 11(5), pages 1-21, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:11:y:2014:i:2:p:1369-1383:d:32529. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.