IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i16p8415-d611231.html
   My bibliography  Save this article

Factors Influencing the Use of Health Information Exchange by Physicians—Using the National Health Insurance PharmaCloud System in Taiwan

Author

Listed:
  • Chiou-Hwa Chuang

    (Medical Information Management Office, National Taiwan University Hospital, Taipei 100225, Taiwan
    National Defense Medical Center, School of Public Health, Taipei 114201, Taiwan)

  • Yi-Fan Li

    (Division of Clinical Chinese Medicine, National Research Institute of Chinese Medicine (NRICM), Ministry of Health and Welfare, Taipei 112304, Taiwan)

  • Lu-Cheng Kuo

    (National Taiwan University Hospital and College of Medicine, Taipei 100025, Taiwan)

  • Ming-Chin Yang

    (Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei 100025, Taiwan)

  • Li-Ting Kao

    (National Defense Medical Center, School of Public Health, Taipei 114201, Taiwan
    National Defense Medical Center, Graduate Institute of Life Sciences, Taipei 114201, Taiwan
    Department of Pharmacy Practice, Tri-Service General Hospital, Taipei 114202, Taiwan
    National Defense Medical Center, School of Pharmacy, Taipei 114201, Taiwan)

Abstract

This study aimed to investigate the factors influencing physicians use of the PharmaCloud system in Taiwan through Technology Continuance Theory (TCT) and to construct a TCT-based structured questionnaire to demonstrate the attitude and behavior of physicians in the Taiwanese medical system. It focused on investigating “confirmation”, “perceived usefulness”, “perceived ease of use”, “attitude”, “satisfaction”, and “continuance intention” towards the preload-based comparison and manual search in PharmaCloud by attending physicians during their outpatient clinics. Path analysis was used to analyze the cause and effect relationship between variables. This study collected 528 valid questionnaires and the results of path analysis found that factors affecting physicians’ continued use of preload-based comparison in PharmaCloud included “perceived usefulness”, “satisfaction”, and “attitude” (all p < 0.001); however, factors that influenced physicians’ continued use of manual search in PharmaCloud were only “satisfaction” and “attitude” (all p < 0.001). Additionally, the effects of “perceived usefulness” and “perceived ease of use” on “satisfaction” could only be seen in preload-based comparison in PharmaCloud. In conclusion, when physicians’ actual use of PharmaCloud met their expectations, physicians had higher levels of confirmation and better perceived usefulness, which naturally increased their satisfaction and attitude towards PharmaCloud and positively prompted them to continue using it.

Suggested Citation

  • Chiou-Hwa Chuang & Yi-Fan Li & Lu-Cheng Kuo & Ming-Chin Yang & Li-Ting Kao, 2021. "Factors Influencing the Use of Health Information Exchange by Physicians—Using the National Health Insurance PharmaCloud System in Taiwan," IJERPH, MDPI, vol. 18(16), pages 1-14, August.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:16:p:8415-:d:611231
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/16/8415/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/16/8415/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bernadette Szajna, 1996. "Empirical Evaluation of the Revised Technology Acceptance Model," Management Science, INFORMS, vol. 42(1), pages 85-92, January.
    2. Liao, Chechen & Palvia, Prashant & Chen, Jain-Liang, 2009. "Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT)," International Journal of Information Management, Elsevier, vol. 29(4), pages 309-320.
    3. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    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. Sarv Devaraj & Robert F. Easley & J. Michael Crant, 2008. "Research Note ---How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use," Information Systems Research, INFORMS, vol. 19(1), pages 93-105, March.
    2. Wei Wang & Shoujian Zhang & Yikun Su & Xinyang Deng, 2019. "An Empirical Analysis of the Factors Affecting the Adoption and Diffusion of GBTS in the Construction Market," Sustainability, MDPI, vol. 11(6), pages 1-24, March.
    3. Raphael Warren Jankeeparsad & Dev Tewari, 2018. "End-User Adoption of Bitcoin in South Africa," Journal of Economics and Behavioral Studies, AMH International, vol. 10(5), pages 230-243.
    4. Xin Xu & Viswanath Venkatesh & Kar Yan Tam & Se-Joon Hong, 2010. "Model of Migration and Use of Platforms: Role of Hierarchy, Current Generation, and Complementarities in Consumer Settings," Management Science, INFORMS, vol. 56(8), pages 1304-1323, August.
    5. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    6. Gao, Tao (Tony) & Rohm, Andrew J. & Sultan, Fareena & Pagani, Margherita, 2013. "Consumers un-tethered: A three-market empirical study of consumers' mobile marketing acceptance," Journal of Business Research, Elsevier, vol. 66(12), pages 2536-2544.
    7. Nuray Cakirli Akyüz & Ludwig Theuvsen, 2020. "The Impact of Behavioral Drivers on Adoption of Sustainable Agricultural Practices: The Case of Organic Farming in Turkey," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    8. Johannes Putzke & Detlef Schoder & Kai Fischbach, 2010. "Adoption of Mass-Customized Newspapers: An Augmented Technology Acceptance Perspective," Journal of Media Economics, Taylor & Francis Journals, vol. 23(3), pages 143-164.
    9. Irfan Bashir & C. Madhavaiah, 2014. "Determinants of Young Consumers’ Intention to Use Internet Banking Services in India," Vision, , vol. 18(3), pages 153-163, September.
    10. Wong Lai Soon & Bobby Chai Boon Hui & Wong Kee Luen, 2013. "Joining the New Band: Factors Triggering the Intentions of Malaysian College and University Students to Adopt 4G Broadband," Information Management and Business Review, AMH International, vol. 5(2), pages 58-65.
    11. Hasnan Baber & N M Baki Billah, 2022. "Fintech and Islamic Banks - an integrative model approach to predict the intentions," Review of Applied Socio-Economic Research, Pro Global Science Association, vol. 24(2), pages 24-45, December.
    12. Ainsworth, Jeremy & Ballantine, Paul W., 2017. "Consumers’ cognitive response to website change," Journal of Retailing and Consumer Services, Elsevier, vol. 37(C), pages 56-66.
    13. Hai, Le Chi & Alam Kazmi, Syed Hasnain, 2015. "Dynamic Support of Government in Online Shopping," MPRA Paper 66027, University Library of Munich, Germany, revised 16 Jul 2015.
    14. Naresh K. Malhotra & Sung S. Kim & Ashutosh Patil, 2006. "Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research," Management Science, INFORMS, vol. 52(12), pages 1865-1883, December.
    15. Türker, Cansu & Altay, Burak Can & Okumuş, Abdullah, 2022. "Understanding user acceptance of QR code mobile payment systems in Turkey: An extended TAM," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    16. Shivraj Kanungo & Vikas Jain, 2008. "Modeling email use: a case of email system transition," System Dynamics Review, System Dynamics Society, vol. 24(3), pages 299-319, September.
    17. Maier, Erik, 2016. "Supply and demand on crowdlending platforms: connecting small and medium-sized enterprise borrowers and consumer investors," Journal of Retailing and Consumer Services, Elsevier, vol. 33(C), pages 143-153.
    18. Maria Tsourela & Dafni-Maria Nerantzaki, 2020. "An Internet of Things (IoT) Acceptance Model. Assessing Consumer’s Behavior toward IoT Products and Applications," Future Internet, MDPI, vol. 12(11), pages 1-23, November.
    19. Wang, Yu-Yin & Wang, Yi-Shun & Lin, Tung-Ching, 2018. "Developing and validating a technology upgrade model," International Journal of Information Management, Elsevier, vol. 38(1), pages 7-26.
    20. Devaki Rau & Thorvald Haerem, 2010. "Applying an organizational learning perspective to new technology deployment by technological gatekeepers: A theoretical model and key issues for future research," Information Systems Frontiers, Springer, vol. 12(3), pages 287-297, July.

    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:18:y:2021:i:16:p:8415-:d:611231. 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.