Research article Special Issues

Iranian physicians’ expectations of telemedicine development and implementation infrastructures in teaching hospitals

  • Introduction: In spite of the fact that telemedicine has various advantages; similarly as in some other data systems, it is essential to investigate clients’ perspective of technology. Besides, the clients’ awareness and satisfaction of the telemedicine are significant issues that ought to be considered before starting a telemedicine program. The present examination in this way looks to assess Iranian doctors’ demeanor and recognition toward the infrastructures of telemedicine development and implementation. Methods: The participants of this examination included doctors working in health care organizations subsidiary to Semnan University of Medical Sciences during 2019 in Iran. A valid and reliable questionnaire was used in order to evaluate the subjects’ attitudes. Results: The mean score of physicians’ attitudes towards human factors was 3.43 ± 0.59, towards educational factors was 3.68 ± 0.94 and towards security factors was 3.50 ± 0.52. Regression analysis showed that there were significant relationships between physicians’ knowledge and their attitudes towards human (P < 0.001), educational (P < 0.001) and security (P = 0.046) infrastructures. Conclusion: the findings of this study show that there are several obstacles that can be reduced through teaching, change-management methods and personal patient-to-provider communication. These techniques can improve acceptance and continuous usage of telemedicine among Iranian physicians.

    Citation: Seyedeh Fatemeh Ghafari, Jamileh Mahdizadeh, Ali Valinejadi, Esmaeil Mehraeen, Ali Mohammadpour, Hamid Bouraghi, Mehdi Kahouei. Iranian physicians’ expectations of telemedicine development and implementation infrastructures in teaching hospitals[J]. AIMS Public Health, 2019, 6(4): 514-522. doi: 10.3934/publichealth.2019.4.514

    Related Papers:

    [1] Sarafa A. Iyaniwura, Musa Rabiu, Jummy F. David, Jude D. Kong . Assessing the impact of adherence to Non-pharmaceutical interventions and indirect transmission on the dynamics of COVID-19: a mathematical modelling study. Mathematical Biosciences and Engineering, 2021, 18(6): 8905-8932. doi: 10.3934/mbe.2021439
    [2] Enahoro A. Iboi, Oluwaseun Sharomi, Calistus N. Ngonghala, Abba B. Gumel . Mathematical modeling and analysis of COVID-19 pandemic in Nigeria. Mathematical Biosciences and Engineering, 2020, 17(6): 7192-7220. doi: 10.3934/mbe.2020369
    [3] Seyedeh N. Khatami, Chaitra Gopalappa . A reinforcement learning model to inform optimal decision paths for HIV elimination. Mathematical Biosciences and Engineering, 2021, 18(6): 7666-7684. doi: 10.3934/mbe.2021380
    [4] Ruiping Yuan, Jiangtao Dou, Juntao Li, Wei Wang, Yingfan Jiang . Multi-robot task allocation in e-commerce RMFS based on deep reinforcement learning. Mathematical Biosciences and Engineering, 2023, 20(2): 1903-1918. doi: 10.3934/mbe.2023087
    [5] Rhiannon Loster, Sarah Smook, Lia Humphrey, David Lyver, Zahra Mohammadi, Edward W. Thommes, Monica G. Cojocaru . Behaviour quantification of public health policy adoption - the case of non-pharmaceutical measures during COVID-19. Mathematical Biosciences and Engineering, 2025, 22(4): 920-942. doi: 10.3934/mbe.2025033
    [6] Jin Zhang, Nan Ma, Zhixuan Wu, Cheng Wang, Yongqiang Yao . Intelligent control of self-driving vehicles based on adaptive sampling supervised actor-critic and human driving experience. Mathematical Biosciences and Engineering, 2024, 21(5): 6077-6096. doi: 10.3934/mbe.2024267
    [7] Feng Guo, Haiyu Xu, Peng Xu, Zhiwei Guo . Design of a reinforcement learning-based intelligent car transfer planning system for parking lots. Mathematical Biosciences and Engineering, 2024, 21(1): 1058-1081. doi: 10.3934/mbe.2024044
    [8] Roman Zúñiga Macías, Humberto Gutiérrez-Pulido, Edgar Alejandro Guerrero Arroyo, Abel Palafox González . Geographical network model for COVID-19 spread among dynamic epidemic regions. Mathematical Biosciences and Engineering, 2022, 19(4): 4237-4259. doi: 10.3934/mbe.2022196
    [9] Zi Sang, Zhipeng Qiu, Xiefei Yan, Yun Zou . Assessing the effect of non-pharmaceutical interventions on containing an emerging disease. Mathematical Biosciences and Engineering, 2012, 9(1): 147-164. doi: 10.3934/mbe.2012.9.147
    [10] David Lyver, Mihai Nica, Corentin Cot, Giacomo Cacciapaglia, Zahra Mohammadi, Edward W. Thommes, Monica-Gabriela Cojocaru . Population mobility, well-mixed clustering and disease spread: a look at COVID-19 Spread in the United States and preventive policy insights. Mathematical Biosciences and Engineering, 2024, 21(4): 5604-5633. doi: 10.3934/mbe.2024247
  • Introduction: In spite of the fact that telemedicine has various advantages; similarly as in some other data systems, it is essential to investigate clients’ perspective of technology. Besides, the clients’ awareness and satisfaction of the telemedicine are significant issues that ought to be considered before starting a telemedicine program. The present examination in this way looks to assess Iranian doctors’ demeanor and recognition toward the infrastructures of telemedicine development and implementation. Methods: The participants of this examination included doctors working in health care organizations subsidiary to Semnan University of Medical Sciences during 2019 in Iran. A valid and reliable questionnaire was used in order to evaluate the subjects’ attitudes. Results: The mean score of physicians’ attitudes towards human factors was 3.43 ± 0.59, towards educational factors was 3.68 ± 0.94 and towards security factors was 3.50 ± 0.52. Regression analysis showed that there were significant relationships between physicians’ knowledge and their attitudes towards human (P < 0.001), educational (P < 0.001) and security (P = 0.046) infrastructures. Conclusion: the findings of this study show that there are several obstacles that can be reduced through teaching, change-management methods and personal patient-to-provider communication. These techniques can improve acceptance and continuous usage of telemedicine among Iranian physicians.



    Acknowledgments



    We thank all participants in this study. We also thank the research council and Clinical Research Development Unit of Kowsar and Amir Al-Moamenin hospitals for providing facilities for this work. Research reported in this publication was supported by a grant [number: 1522] from the Semnan University of Medical Sciences, Semnan, Iran.

    Conflict of interest



    All authors report no conflict of interest.

    [1] Harst L, Lantzsch H, Scheibe M (2019) Theories Predicting End-User Acceptance of Telemedicine Use: Systematic Review. J Med Internet Res 21: e13117. doi: 10.2196/13117
    [2] Scott Kruse C, Karem P, Shifflett K, et al. (2018) Evaluating barriers to adopting telemedicine worldwide: A systematic review. J Telemed Telecare 24: 4–12. doi: 10.1177/1357633X16674087
    [3] Mohammadi A, Valinejadi A, Sakipour S, et al. (2018) Improving the distribution of rural health houses using elicitation and GIS in Khuzestan province (the southwest of Iran). Int J Health Policy Manage 7: 336.
    [4] Alipour J, Safari Lafti S, Askari Majdabadi H, et al. (2016) Factors affecting hospital information system acceptance by caregivers of educational hospitals based on technology acceptance model (TAM): A study in Iran. IIOAB J 119–123.
    [5] Hanson RE, Truesdell M, Stebbins GT, et al. (2019) Telemedicine vs Office Visits in a Movement Disorders Clinic: Comparative Satisfaction of Physicians and Patients. Mov Disord Clin Pract 6: 65–69.
    [6] Kamal SA, Hussain S, Shafiq M, et al. (2018) Investigating the Adoption of Telemedicine Services: An Empirical Study of Factors Influencing Physicians' Perspective in Pakistan. The Nucl 55: 153–163.
    [7] Jansen-Kosterink S, Dekker-van Weering M, van Velsen L (2019) Patient acceptance of a telemedicine service for rehabilitation care: A focus group study. Int J Med Inf 125: 22–29. doi: 10.1016/j.ijmedinf.2019.01.011
    [8] Ward MM, Merchant KA, Carter KD, et al. (2018) Use of telemedicine for ED physician coverage in critical access hospitals increased after CMS policy clarification. Health Aff 37: 2037–2044. doi: 10.1377/hlthaff.2018.05103
    [9] Zayapragassarazan Z, Kumar S (2016) Awareness, knowledge, attitude and skills of telemedicine among health professional faculty working in teaching hospitals. J Clin Diagn Res JCDR 10: JC01.
    [10] Alaboudi A, Atkins A, Sharp B, et al. (2016) Barriers and challenges in adopting Saudi telemedicine network: The perceptions of decision makers of healthcare facilities in Saudi Arabia. J Inf Public Health 9: 725–733. doi: 10.1016/j.jiph.2016.09.001
    [11] Salehahmadi Z, Hajialiasghari F (2013) Telemedicine in Iran: chances and challenges. World J Surg 2: 18.
    [12] Nobakht S, Bagheri S, Mehraeen E, et al. (2018) The Feasibility of Telemedicine Technology Implementation in the Selected Hospitals of Iran. J Payavard Salamat 12: 25–33.
    [13] Sadeghi M (2013) Feasibility of Telepathology Implementation in the training hospitals affiliated to Tehran University of medical sciences. Thesis, School of Health Management and Information Sciences, Tehran University of Medical Science.
    [14] Miandoab AT, Alizadeh G, Rezaei P (2017) 148: The Study of Specialist Physician Knowledge and Attitude of Telemedicine and Barriers to its Implementation in Tabriz Teaching Hospitals. BMJ open 7(Suppl 1): bmjopen-2016-015415.148.
    [15] Rezaei P, Maserrat E, Torab-Miandoab A (2018) Specialist Physicians' Perspectives about Telemedicine and Barriers to using it in Tabriz Teaching Hospitals. ISMJ 20: 562–572.
    [16] Ray KN, Felmet KA, Hamilton MF, et al. (2017) Clinician attitudes toward adoption of pediatric emergency telemedicine in rural hospitals. Pediatr Emerg Care 33: 250–257. doi: 10.1097/PEC.0000000000000583
    [17] De La Torre-Díez I, López-Coronado M, Vaca C, et al. (2015) Cost-utility and cost-effectiveness studies of telemedicine, electronic and mobile health systems in the literature: a systematic review. Telemed E-Health 21: 81–85. doi: 10.1089/tmj.2014.0053
    [18] Hoonakker P (2016) Human factors in telemedicine. In Handbook of Human Factors and Ergonomics in Health Care and Patient Safety. CRC Press, 322–333.
    [19] Hwang D, Chang JW, Benjafield AV, et al. (2018) Effect of telemedicine education and telemonitoring on continuous positive airway pressure adherence. The tele-OSA randomized trial. Am J Respir Crit Care Med 197: 117–126. doi: 10.1164/rccm.201703-0582OC
    [20] Chang MJ, Jung JK, Park MW, et al. (2015) Strategy to reinforce security in telemedicine services. In: 2015 17th International Conference on Advanced Communication Technology (ICACT), IEEE, 170–175.
    [21] Ayatollahi H, Mirani N, Nazari F, et al. (2018) Iranian healthcare professionals' perspectives about factors influencing the use of telemedicine in diabetes management. World J Diabetes 9: 92. doi: 10.4239/wjd.v9.i6.92
    [22] Ly BA, Kristjansson E, Labonté R, et al. (2018) Determinants of the Intention of Senegal's Physicians to Use Telemedicine in Their Professional Activities. Telemed E-Health 24: 897–898. doi: 10.1089/tmj.2017.0276
  • Reader Comments
  • © 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(4957) PDF downloads(381) Cited by(3)

Article outline

Figures and Tables

Figures(2)  /  Tables(2)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog