The effect of performance expectancy and behavioral intention on the use of electronic medical record (EMR) in tertier hospital in Indonesia

Eka Wilda Faida; Stefanus Supriyanto; Setya Haksama; Wihasto Suryaningtyas; Widi Astuti; Bambang Nudji; Siti Nur Hasina

doi:10.53730/ijhs.v6nS9.12729

Authors

Eka Wilda Faida
ekawildafaida@gmail.com
Programme doctoral Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia and Lecturer of Medical Record and Health Information, STIKES Yayasan Rumah Sakit Doctor Soetomo, Surabaya, Indonesia
Stefanus Supriyanto Lecturer Faculty of Public Health, Airlangga University, Surabaya, Indonesia
Setya Haksama Lecturer Faculty of Public Health, Airlangga University, Surabaya, Indonesia
Wihasto Suryaningtyas Head of Department Information and Communication Technology, Doctor Soetomo General Hospital Surabaya, Indonesia
Widi Astuti Lecturer of Medical Record and Health Information, STIKES Yayasan Rumah Sakit Doctor Soetomo, Surabaya, Indonesia
Bambang Nudji Lecturer of Medical Record and Health Information, STIKES Yayasan Rumah Sakit Doctor Soetomo, Surabaya, Indonesia
Siti Nur Hasina Department of Nursing, Faculty of Nursing and Midwifery, Universitas Nahdlatul Ulama Surabaya, Surabaya, Indonesia

Keywords:

Performance Expectancy, Behavioral Intention, Technology Use, EMR, Hospital

Abstract

Health and well-being are the third Sustainable Development Goals (SDGs) in the 2030 Agenda for Sustainable Development. To accomplish this, Soetomo hospital as the largest referral hospital in the province of East Java is expected to have an Electronic Medical Record (EMR) completeness level of 100 percent by 2024. This study aimed to examine the impact of performance expectation and behavioral intention on hospital EMR technology usage. This was an observational study with a cross sectional research design. From a population of 390 health workers, a sample of 195 was generated using proportional random sampling. Validity and reliability can be determined using SPSS software. Utilizing SEM PLS software, the analysis is evaluated. Results indicate that performance expectation can have a direct effect on technology use EMR (T Statistic = 21,506) and an indirect effect via behavioral intention (T Statistic = 15,038). The relationship between behavioral intention and technology use EMR is direct (T statistic = 5,475). Conclusion: Performance expectations explain 52% of behavioral intention, while behavioral intentions explain 85% of technology use EMR.

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References

Abdekhoda, M., Ahmadi, M., Dehnad, A., Noruzi, A., Gohari, M., Hosizah, Kuntoro, Hari, B., John, S. P., Menteri Kesehatan RI, Kementerian Kesehatan RI, Davis, F. D. A., Taiwo, A. A., Downe, A. G., Venkatesh, V., Thong, J. Y. L. L., Xu, X. X. X., Bharata, W., Widyaningrum, P. W., … Tsai, C. C. C. Y. (2013). The use of unified theory of acceptance and use of technology to confer the behavioral model of 3G mobile telecommunication users. Journal of Statistics and Management Systems, 11(1), 1–9. https://doi.org/10.1080/09720510.2008.10701351

Abdekhoda, M., & Salih, K. M. (2017). Determinant Factors in Applying Picture Archiving and Communication Systems (PACS) in Healthcare. In Perspectives in health information management (Vol. 14, Issue Summer).

Archer, N., & Cocosila, M. (2011). A comparison of physician pre-adoption and adoption views on electronic health records in canadian medical practices. Journal of Medical Internet Research, 13(3), 1–12. https://doi.org/10.2196/jmir.1726

Bawack, R. E., & Kala Kamdjoug, J. R. (2018). Adequacy of UTAUT in clinician adoption of health information systems in developing countries: The case of Cameroon. International Journal of Medical Informatics, 109(October 2017), 15–22. https://doi.org/10.1016/j.ijmedinf.2017.10.016

Cilliers, L., & Flowerday, S. V. (2013). Health information systems to improve health care: A telemedicine case study. SA Journal of Information Management, 15(1), 1–5. https://doi.org/10.4102/sajim.v15i1.541

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008

Donnelly, W. J. (1992). Why SOAP is bad for the medical record. Archives of Internal Medicine, 152(3), 481–484. https://doi.org/10.1001/archinte.152.3.481

Dwijosusilo, D. K., & Sarni. (2018). Peranan Rekam Medis Elektronik Terhadap Sistim Informasi Manajemen Rumah Sakit di Rumah Sakit Umum Haji Surabaya. Jurnal Administrasi, 1–111.

Emmanuel, A. K., Sutinen, E., Marjatta, V.-R., Jarkko, S., & Ebenezer, A. (2015). Using Unified Theory of Acceptance and Use of Technology Model to Predict Students’ Behavioral Intention to Adopt and Use E-Counseling in Ghana. International Journal of Modern Education and Computer Science, 7(11), 1–11. https://doi.org/10.5815/ijmecs.2015.11.01

Enaizan, O., Zaidan, A. A., Alwi, N. H. M., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., & Albahri, A. S. (2020). Electronic medical record systems: decision support examination framework for individual, security and privacy concerns using multi-perspective analysis. Health and Technology, 10(3), 795–822. https://doi.org/10.1007/s12553-018-0278-7

Fatimatus Zayniyah. (2016). Analisis Faktor yang Berhubungan dengan Perilaku Penggunaan Sistem Informasi Manajemen di Rumah Sakit Paru Jember. Skripsi Uiversitas Jamber, 109.

Gagnon, M. P., Ghandour, E. K., Talla, P. K., Simonyan, D., Godin, G., Labrecque, M., Ouimet, M., & Rousseau, M. (2014). Electronic health record acceptance by physicians: Testing an integrated theoretical model. Journal of Biomedical Informatics, 48, 17–27. https://doi.org/10.1016/j.jbi.2013.10.010

Hsu, C. C., Sandford, B., Ling, C. J., & Lin, C. T. (2021). Can the unified theory of acceptance and use of technology (Utaut) help explain subjective well-being in senior citizens due to gateball participation? In International Journal of Environmental Research and Public Health (Vol. 18, Issue 17). https://doi.org/10.3390/ijerph18179015

Lestari, I., Studi, P., Informasi, S., Sains, F., Teknologi, D. A. N., Islam, U., & Sunan, N. (2022). Indah Lestari_H76217034.

Li, J., Talaei-Khoei, A., Seale, H., Ray, P., & MacIntyre, C. R. (2013). Health Care Provider Adoption of eHealth: Systematic Literature Review. Interactive Journal of Medical Research, 2(1), e7. https://doi.org/10.2196/ijmr.2468

Ma, C. C., Kuo, K. M., & Alexander, J. W. (2016). A survey-based study of factors that motivate nurses to protect the privacy of electronic medical records. In BMC Medical Informatics and Decision Making (Vol. 16, Issue 1). https://doi.org/10.1186/s12911-016-0254-y

Menteri Kesehatan RI. (2020). Kebijakan digitalisasi di rumah sakit.

Moghawemi, S., Mohd Salleh, N. A., Zhao, W., & Mattila, M. (2012). The entrepreneur’s perception on information technology innovation adoption: An empirical analysis of the role of precipitating events on usage behavior. Innovation: Management, Policy and Practice, 14(2), 231–246. https://doi.org/10.5172/impp.2012.14.2.231

Mohamadali, N. A. K. S., & Garibaldi, J. M. (2010). A novel evaluation model of user acceptance of software technology in healthcare sector. HEALTHINF 2010 - 3rd International Conference on Health Informatics, Proceedings, 392–397. https://doi.org/10.5220/0002695703920397

Nurlani, L., & Permana, B. (2017). Analisa Kesuksesan Sistem Informasi Akademik Menggunakan Model Terintegrasi. Jurnal Teknologi Rekayasa, 2(2), 105. https://doi.org/10.31544/jtera.v2.i2.2017.105-116

PERMENKES RI No 269/MENKES/PER/III/2008. (2008). permenkes ri 269/MENKES/PER/III/2008. In Permenkes Ri No 269/Menkes/Per/Iii/2008 (Vol. 2008, p. 7).

Perez, A. V., Briones, V. V., Viteri, C. G. V., & Gamez, M. R. (2017). Iberoamerica in network, GIS & TIC. International Journal of Social Sciences and Humanities, 1(3), 108–117. https://doi.org/10.29332/ijssh.v1n3.63

Rachmawati, I. K., Bukhori, M., Majidah, Y., Hidayatullah, S., & Waris, A. (2020). Analysis Of Use Of Mobile Banking With Acceptance And Use Of Technology (UTAUT) Article in. International Journal of Scientific & Technology Research, 9(08), 534–540. www.ijstr.org

Ramdhani, A. B., Rachmawati, I., Sidiq, F., & Prabowo, A. (2017). Pengaruh Adopsi Teknologi Layanan Uang Elektronik Telkomsel Cash Menggunakan Pendekatan Utaut2 the Effect of Technology Adoption Electronic Money Services Telkomsel Cash Using Utaut2. E-Proceeding of Management, 4(1), 53–60. https://libraryeproceeding.telkomuniversity.ac.id/index.php/management/article/view/4364

Setyawan, D. A. (2017). Rekam Medis Elektronik (RME). 2–28.

Sharifian, R., Askarian, F., Nematolahi, M., & Farhadi, P. (2014). Factors Influencing Nurses’ Acceptance of Hospital Information Systems in Iran: Application of the Unified Theory of Acceptance and Use of Technology. Health Information Management Journal, 43(3), 23–28. https://doi.org/10.1177/183335831404300303

Shiferaw, K. B., & Mehari, E. A. (2019). Modeling predictors of acceptance and use of electronic medical record system in a resource limited setting: Using modified UTAUT model. Informatics in Medicine Unlocked, 17(April), 100182. https://doi.org/10.1016/j.imu.2019.100182

Suryasa, I. W., Rodríguez-Gámez, M., & Koldoris, T. (2022). Post-pandemic health and its sustainability: Educational situation. International Journal of Health Sciences, 6(1), i-v. https://doi.org/10.53730/ijhs.v6n1.5949

Sydoruk, L., Bakhmat, N., Poberezhets, H., Misenyova, V., & Boyarova, O. (2022). Formation of future economist professional competence in adaptive-digital environment conditions of higher educational institution. International Journal of Health Sciences, 6(1), 103–114. https://doi.org/10.53730/ijhs.v6n1.3390

Tarhini, A., El-Masri, M., Ali, M., & Serrano, A. (2016). Extending the utaut model to understand the customers’ acceptance and use of internet banking in lebanon a structural equation modeling approach. Information Technology and People, 29(4), 830–849. https://doi.org/10.1108/ITP-02-2014-0034

Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly: Management Information Systems, 15(1), 125–142. https://doi.org/10.2307/249443

Tibenderana, P., Ogao, P., Ikoja-Odongo, J., & Wokadala, J. (2010). Measuring Levels of End-Users ’ Acceptance and Use of Hybrid Library Services. International Journal of Education and Development Using Information and Communication Technology (IJEDICT), 6(2), 33–54.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems. https://doi.org/10.2307/30036540

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428

Wrzosek, N., Zimmermann, A., & Balwicki, Ł. (2020). Doctors’ perceptions of e-prescribing upon its mandatory adoption in poland, using the unified theory of acceptance and use of technology method. In Healthcare (Switzerland) (Vol. 8, Issue 4). https://doi.org/10.3390/healthcare8040563

Wu, Y.-L., Tao, Y.-H., & Yang, P.-C. (2008). The use of unified theory of acceptance and use of technology to confer the behavioral model of 3G mobile telecommunication users. Journal of Statistics and Management Systems, 11(5), 919–949. https://doi.org/10.1080/09720510.2008.10701351

Yu, C. S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the utaut model. Journal of Electronic Commerce Research, 13(2), 105–121.

Zhou, T. (2012). Examining location-based services usage from the perspectives of unified theory of acceptance and use of technolog and privacy risk. Journal of Electronic Commerce Research, 13(2), 135–144.