IDEAS home Printed from https://ideas.repec.org/a/spr/elcore/v23y2023i3d10.1007_s10660-021-09516-6.html
   My bibliography  Save this article

Should doctors use or avoid medical terms? The influence of medical terms on service quality of E-health

Author

Listed:
  • Jilong Zhang

    (Renmin University of China)

  • Jin Zhang

    (Renmin University of China)

  • Kanliang Wang

    (Renmin University of China)

  • Wei Yan

    (Communication University of China
    Communication University of China)

Abstract

With epidemics and pandemics like COVID-19, many offline healthcare services have been suspended and shifted to online, where patients and doctors typically communicate by typing texts. The limited communication poses a threat to the service quality of E-health, and also raises higher demand on the language skills of doctors, in which medical terms are a common concern. Traditional studies of offline healthcare mostly hold a negative attitude towards the use of medical terms by doctors. However, should we still advise doctors to avoid using medical terms in E-health? To answer this question, this paper conducts a study combining technical and empirical analyses based on real data. In this paper, a novel unsupervised text-mining method is proposed to automatically identify medical terms with crowd wisdom from large-scale doctor-patient communication texts. Then, a TREC-type experiment is carried out to validate the proposed method in terms of Precision, Recall, and $$F_1$$ F 1 -measure, demonstrating that it can identify accurate and comprehensive medical terms. Based on the identified medical terms, an empirical analysis is conducted to verify the influence of medical terms used by doctors on the service quality of E-health. The analysis results show that for patients with low health literacy, the use of medical terms by doctors would decrease their service quality. However, for patients with high health literacy, the use of medical terms by doctors can significantly increase their service quality, revealing that doctors could improve their service quality in E-health by adjusting their medical term usage according to the health literacy of patients.

Suggested Citation

  • Jilong Zhang & Jin Zhang & Kanliang Wang & Wei Yan, 2023. "Should doctors use or avoid medical terms? The influence of medical terms on service quality of E-health," Electronic Commerce Research, Springer, vol. 23(3), pages 1775-1805, September.
  • Handle: RePEc:spr:elcore:v:23:y:2023:i:3:d:10.1007_s10660-021-09516-6
    DOI: 10.1007/s10660-021-09516-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10660-021-09516-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10660-021-09516-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273, January.
    2. Smith, Sian K. & Dixon, Ann & Trevena, Lyndal & Nutbeam, Don & McCaffery, Kirsten J., 2009. "Exploring patient involvement in healthcare decision making across different education and functional health literacy groups," Social Science & Medicine, Elsevier, vol. 69(12), pages 1805-1812, December.
    3. Zhihong Li & Yining Song & Xiaoying Xu, 2019. "Incorporating facial attractiveness in photos for online dating recommendation," Electronic Commerce Research, Springer, vol. 19(2), pages 285-310, June.
    4. Xiaofei Zhang & Xitong Guo & Kee-hung Lai & Wu Yi, 2019. "How does online interactional unfairness matter for patient–doctor relationship quality in online health consultation? The contingencies of professional seniority and disease severity," European Journal of Information Systems, Taylor & Francis Journals, vol. 28(3), pages 336-354, May.
    5. Wu, Hong & Deng, Zhaohua, 2019. "Knowledge collaboration among physicians in online health communities: A transactive memory perspective," International Journal of Information Management, Elsevier, vol. 49(C), pages 13-33.
    6. Lu Yan & Yong Tan, 2014. "Feeling Blue? Go Online: An Empirical Study of Social Support Among Patients," Information Systems Research, INFORMS, vol. 25(4), pages 690-709, December.
    7. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    8. Huosong Xia & Yitai Yang & Xiaoting Pan & Zuopeng Zhang & Wuyue An, 2020. "Sentiment analysis for online reviews using conditional random fields and support vector machines," Electronic Commerce Research, Springer, vol. 20(2), pages 343-360, June.
    9. Jian Mou & Dong-Hee Shin & Jason F. Cohen, 2017. "Trust and risk in consumer acceptance of e-services," Electronic Commerce Research, Springer, vol. 17(2), pages 255-288, June.
    10. L. G. Pee, 2016. "Customer co-creation in B2C e-commerce: does it lead to better new products?," Electronic Commerce Research, Springer, vol. 16(2), pages 217-243, June.
    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. Liu, Huiyuan & Perera, Sandun C. & Wang, Jian-Jun, 2023. "Does the physicians’ medical team joining behavior affect their performance on an online healthcare platform? Evidence from two quasi-experiments," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    2. Liu, Huiyuan & Perera, Sandun C. & Wang, Jian-Jun & Leonhardt, James M., 2023. "Physician engagement in online medical teams: A multilevel investigation," Journal of Business Research, Elsevier, vol. 157(C).
    3. Qing Ye & Hong Wu, 2023. "Offline to online: The impacts of offline visit experience on online behaviors and service in an Internet hospital," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-21, December.
    4. Paolo Naticchioni & Silvia Loriga, 2011. "Short and Long Term Evaluations of Public Employment Services in Italy," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 57(3), pages 201-229.
    5. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    6. Ellison, Richard B. & Ellison, Adrian B. & Greaves, Stephen P. & Sampaio, Breno, 2017. "Electronic ticketing systems as a mechanism for travel behaviour change? Evidence from Sydney’s Opal card," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 80-93.
    7. Turner, Alex J. & Fichera, Eleonora & Sutton, Matt, 2021. "The effects of in-utero exposure to influenza on mental health and mortality risk throughout the life-course," Economics & Human Biology, Elsevier, vol. 43(C).
    8. Wang, Xu & Zhang, Xiaobo & Xie, Zhuan & Huang, Yiping, 2016. "Roads to innovation: Firm-level evidence from China:," IFPRI discussion papers 1542, International Food Policy Research Institute (IFPRI).
    9. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    10. Preusse, Verena & Wollni, Meike, 2021. "Adoption of sustainable agricultural practices in the context of urbanisation and environmental stress – Evidence from farmers in the rural-urban interface of Bangalore, India," 2021 Annual Meeting, August 1-3, Austin, Texas 312690, Agricultural and Applied Economics Association.
    11. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    12. Jeffrey Smith, 2000. "A Critical Survey of Empirical Methods for Evaluating Active Labor Market Policies," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 136(III), pages 247-268, September.
    13. François Fall & Akim Almouksit, 2016. "The impact of formal financing on small informal enterprises in Comoros," Working Papers hal-01566389, HAL.
    14. Amarendra Sharma, 2019. "Indira Awas Yojana and Housing Adequacy: An Evaluation using Propensity Score Matching," ASARC Working Papers 2019-05, The Australian National University, Australia South Asia Research Centre.
    15. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    16. Balima, Wenéyam Hippolyte & Combes, Jean-Louis & Minea, Alexandru, 2017. "Sovereign debt risk in emerging market economies: Does inflation targeting adoption make any difference?," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 360-377.
    17. Federico Biagi & Daniele Bondonio & Alberto Martini, 2015. "Counterfactual Impact Evaluation of Enterprise Support Programmes. Evidence from a Decade of Subsidies to Italian Firm," ERSA conference papers ersa15p1619, European Regional Science Association.
    18. Bono, Pierre-Henri & David, Quentin & Desbordes, Rodolphe & Py, Loriane, 2022. "Metro infrastructure and metropolitan attractiveness," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    19. Rajeev Dehejia, 2013. "The Porous Dialectic: Experimental and Non-Experimental Methods in Development Economics," WIDER Working Paper Series wp-2013-011, World Institute for Development Economic Research (UNU-WIDER).
    20. Nathalie Greenan & Pierre-Jean Messe, 2018. "Transmission of vocational skills in the second part of careers: the effect of ICT and management changes," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 52(1), pages 1-16, December.

    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:spr:elcore:v:23:y:2023:i:3:d:10.1007_s10660-021-09516-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.