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Adoption factors of electronic health record systems

Author

Listed:
  • Spatar, Daria
  • Kok, Orhun
  • Basoglu, Nuri
  • Daim, Tugrul

Abstract

The main goal of the study is to investigate the factors that affect adoption of EHR systems. The adoption has been looked at through four lenses: users' satisfaction, impact on quality of care, infusion and diffusion of the technology. The study incorporates the results of the most important studies in the field. The findings of the research allow decision-makers to select an EHR that better suits needs of the users, to choose a strategy to avoid users’ resistance and lack of support. The study offers a comprehensive framework that can be used in different settings, i.e. small and large clinics, developing and developed countries, etc. Also it contributes to the state of knowledge, as it provides an extensive analysis of the factors, both system- and user-related, that affect user adoption and proves applicability of TAM in the healthcare settings.

Suggested Citation

  • Spatar, Daria & Kok, Orhun & Basoglu, Nuri & Daim, Tugrul, 2019. "Adoption factors of electronic health record systems," Technology in Society, Elsevier, vol. 58(C).
    • Handle: RePEc:eee:teinso:v:58:y:2019:i:c:s0160791x19300442
    DOI: 10.1016/j.techsoc.2019.101144
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    References listed on IDEAS

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    1. Basoglu, Nuri & Ok, Ali Emre & Daim, Tugrul U., 2017. "What will it take to adopt smart glasses: A consumer choice based review?," Technology in Society, Elsevier, vol. 50(C), pages 50-56.
    2. Cayir, Sinan & Basoglu, Nuri & Daim, Tugrul U., 2016. "A study on the relationship between task, information, and individual performance," Technology in Society, Elsevier, vol. 46(C), pages 1-9.
    3. William H. DeLone & Ephraim R. McLean, 1992. "Information Systems Success: The Quest for the Dependent Variable," Information Systems Research, INFORMS, vol. 3(1), pages 60-95, March.
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    Cited by:

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    3. Demirkol, Denizhan & Seneler, Cagla & Daim, Tugrul & Shaygan, Amir, 2020. "Measuring emotional reactions of university students towards a Student Information System (SIS): A Turkish university case," Technology in Society, Elsevier, vol. 63(C).
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    5. Gourav Jain & Tripti Mahara & S. C. Sharma & Om Prakash Verma & Tarun Sharma, 2022. "Clustering-Based Recommendation System for Preliminary Disease Detection," International Journal of E-Health and Medical Communications (IJEHMC), IGI Global, vol. 13(4), pages 1-14, August.
    6. Mutanu, Leah & Gupta, Khushi & Gohil, Jeet, 2022. "Leveraging IoT solutions for enhanced health information exchange," Technology in Society, Elsevier, vol. 68(C).
    7. Rajak, Manindra & Shaw, Krishnendu, 2021. "An extension of technology acceptance model for mHealth user adoption," Technology in Society, Elsevier, vol. 67(C).
    8. Carboni, Chiara & Wehrens, Rik & van der Veen, Romke & de Bont, Antoinette, 2022. "Conceptualizing the digitalization of healthcare work: A metaphor-based Critical Interpretive Synthesis," Social Science & Medicine, Elsevier, vol. 292(C).
    9. Yavuz, Merve & Çorbacıoğlu, Eda & Başoğlu, Ahmet Nuri & Daim, Tugrul Unsal & Shaygan, Amir, 2021. "Augmented reality technology adoption: Case of a mobile application in Turkey," Technology in Society, Elsevier, vol. 66(C).
    10. Alanazi, Hamad & Daim, Tugrul, 2021. "Health technology diffusion: Case of remote patient monitoring (RPM) for the care of senior population," Technology in Society, Elsevier, vol. 66(C).
    11. Shahbaz, Muhammad & Gao, Changyuan & Zhai, LiLi & Shahzad, Fakhar & Khan, Imran, 2021. "Environmental air pollution management system: Predicting user adoption behavior of big data analytics," Technology in Society, Elsevier, vol. 64(C).
    12. Rajak, Manindra & Shaw, Krishnendu, 2019. "Evaluation and selection of mobile health (mHealth) applications using AHP and fuzzy TOPSIS," Technology in Society, Elsevier, vol. 59(C).

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