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Strategies for technology-driven service encounters for patient experience satisfaction in hospitals

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  • Lee, DonHee

Abstract

This study empirically examines the effects of a patient learning experience and technology-driven service encounters on patients' satisfaction with their experience in using self-service capabilities of digital devices and systems in large hospitals. The research model and associated hypotheses were tested using structural equations modeling based on data collected from 212 patients who had care experience at large hospitals in metropolitan areas of South Korea. The findings of the study indicate that patients' learning experience with technologies and technology-driven service encounters encourage patients to participate in the treatment process, which in turn positively affect patients' experience satisfaction. The study results present implications regarding the relationships among patient learning, technology-driven service encounters, participation in treatment processes, and experience satisfaction. The study also provides new insights to hospital administrators regarding investment strategies in medical technologies to optimize their impact on care quality and patient experience satisfaction. Technology-driven devices and systems are especially critical for knowledge-intensive transformative institutions like hospitals for quality patient services and efficient operations. Thus, healthcare organizations should minimize the disruptive effect of innovative technological applications by developing effective planning, education/training, and user guide.

Suggested Citation

  • Lee, DonHee, 2018. "Strategies for technology-driven service encounters for patient experience satisfaction in hospitals," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 118-127.
    • Handle: RePEc:eee:tefoso:v:137:y:2018:i:c:p:118-127
    DOI: 10.1016/j.techfore.2018.06.050
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    Cited by:

    1. Homayounfard, Amir & Zaefarian, Ghasem, 2022. "Key challenges and opportunities of service innovation processes in technology supplier-service provider partnerships," Journal of Business Research, Elsevier, vol. 139(C), pages 1284-1302.
    2. Sang M. Lee & DonHee Lee, 2022. "Effects of healthcare quality management activities and sociotechnical systems on internal customer experience and organizational performance," Service Business, Springer;Pan-Pacific Business Association, vol. 16(1), pages 1-28, March.
    3. Hayat, Naeem & Salameh, Anas A. & Malik, Haider Ali & Yaacob, Mohd Rafi, 2022. "Exploring the adoption of wearable healthcare devices among the Pakistani adults with dual analysis techniques," Technology in Society, Elsevier, vol. 70(C).
    4. Denicolai, Stefano & Previtali, Pietro, 2020. "Precision Medicine: Implications for value chains and business models in life sciences," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    5. Nadeem, Waqar & Tan, Teck Ming & Tajvidi, Mina & Hajli, Nick, 2021. "How do experiences enhance brand relationship performance and value co-creation in social commerce? The role of consumer engagement and self brand-connection," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    6. Sang M. Lee & DonHee Lee, 2020. "Healthcare wearable devices: an analysis of key factors for continuous use intention," Service Business, Springer;Pan-Pacific Business Association, vol. 14(4), pages 503-531, December.
    7. DonHee Lee & Seong No Yoon, 2021. "Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges," IJERPH, MDPI, vol. 18(1), pages 1-18, January.
    8. Lee, Sang M. & Lee, DonHee, 2021. "Opportunities and challenges for contactless healthcare services in the post-COVID-19 Era," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    9. Lamrhari, Soumaya & Ghazi, Hamid El & Oubrich, Mourad & Faker, Abdellatif El, 2022. "A social CRM analytic framework for improving customer retention, acquisition, and conversion," Technological Forecasting and Social Change, Elsevier, vol. 174(C).

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