Bibliometric Analysis of Electronic Medical Records (EMR) Acceptance and Adoption: Trends, Insights, and Future Directions

Ananda Haris ^1*  , Qurratul Aini ¹

This study showed a comprehensive bibliometric analysis of EMR acceptance and adoption trends over a decade, emphasizing theoretical frameworks and global research patterns.

Abstract

Background: The integration of Electronic Medical Records (EMRs) and Electronic Health Records (EHRs) has revolutionized healthcare by enabling digital storage, exchange, and management of patient information. This abstract explores the landscape of EMR acceptance and adoption through a bibliometric analysis of research literature indexed in Scopus from January 2014 to December 2023. The study identified 138 relevant articles focusing on EMR and EHR acceptance, employing tools like VOSviewer and Rstudio-Biblioshiny for data visualization and analysis. Method: This study is qualitative research with a literature study approach. The data collection technique in this study used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and obtained 138 documents for analysis. This dataset is converted to CSV format for further processing in Mapchart, VosViewer, and Rstudio-Biblioshiny  for thorough analysis. Result: Key findings reveal a predominant focus on factors influencing EMR adoption, including technological infrastructure, user training, and regulatory mandates. The United States and Canada emerged as leading contributors to EMR research, highlighting their advanced healthcare systems. Theoretical frameworks such as the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) were frequently employed to assess adoption determinants. Conclusions: The study identifies gaps in research, particularly in areas such as cybersecurity and user satisfaction, suggesting future avenues for investigation. By addressing these gaps, researchers can enhance the usability and effectiveness of EMR and EHR systems, thereby improving healthcare delivery and patient outcomes globally.

Keywords: Bibliometric Approach; Electronic Medical Records, Electronic Health Records, Acceptance, Adoption

References

Abdekhoda, M., Ahmadi, M., Dehnad, A., Noruzi, A., & Gohari, M. (2016). Applying electronic medical records in health care: Physicians’ perspective. Applied Clinical Informatics, 7(2), 341.

Abdekhoda, M., Ahmadi, M., Gohari, M., & Noruzi, A. (2015). The effects of organizational contextual factors on physicians’ attitude toward adoption of Electronic Medical Records. Journal of Biomedical Informatics, 53, 174–179.

Abdekhoda, M., Dehnad, A., & Zarei, J. (2019). Determinant factors in applying electronic medical records in healthcare. Eastern Mediterranean Health Journal, 25(1), 24–33.

Adwan, A. S. Al. (2017). Case study and grounded theory: a happy marriage? An exemplary application from healthcare informatics adoption research. International Journal of Electronic Healthcare, 9(4), 294–318.

Aini Muzayyana, Qurratul Aini (2024). Bibliometric Analysis of the Health Belief Model in Healthcare Workers: Trends, Insights, and Future Directions, Journal of Angiotherapy, 8(5), 1-12, 9698

Ajinegara, M. W., & Soebagyo, J. (2022). Analisis Bibliometrik Tren Penelitian Media Pembelajaran Google Classroom Menggunakan Aplikasi VOSViewer. JNPM (Jurnal Nasional Pendidikan Matematika), 6(1), 193–202.

Aldosari, B., Al-Mansour, S., Aldosari, H., & Alanazi, A. (2018). Assessment of factors influencing nurses acceptance of electronic medical record in a Saudi Arabia hospital. Informatics in Medicine Unlocked, 10(September 2017), 82–88. https://doi.org/10.1016/j.imu.2017.12.007

Al-Otaibi, J., Tolma, E., Alali, W., Alhuwail, D., & Mohamed Aljunid, S. (2022). The Factors Contributing to Physicians’ Current Use of and Satisfaction With Electronic Health Records in Kuwait’s Public Health Care: Cross-sectional Questionnaire Study. JMIR Medical Informatics, 10(10). https://doi.org/10.2196/36313

Al-Suqri, M. N., & Al-Kharusi, R. M. (2015). Ajzen and Fishbein’s theory of reasoned action (TRA)(1980). In Information seeking behavior and technology adoption: Theories and trends (pp. 188–204). IGI Global.

Alsyouf, A., Ishak, A. K., Lutfi, A., Alhazmi, F. N., & Al-Okaily, M. (2022). The role of personality and top management support in continuance intention to use electronic health record systems among nurses. International Journal of Environmental Research and Public Health, 19(17), 11125.

Amin, M., Setyonugroho, W., Hidayah, N., Brawijaya, J., Kasihan, K., Istimewa Yogyakarta, D., Studi Magister Administrasi Rumah Sakit Universitas Muhammadiyah Yogyakarta, P., Author, C., & kunci-Rekam Medik Elektronik, K. (2021). Implementasi Rekam Medik Elektronik: Sebuah Studi Kualitatif. 8(1), 430–442. http://jurnal.mdp.ac.id

Anshari, M. (2019). Redefining electronic health records (EHR) and electronic medical records (EMR) to promote patient empowerment. IJID (International Journal on Informatics for Development), 8(1), 35–39.

Azmi, N. A., Mahmud, A., & Rahman, A. A. (2022). Satisfaction Level and Its Associated Factors Among Government Electronic Medical Record System Users in Klang Valley. Malaysian Journal of Public Health Medicine, 22(2), 77–86.

Bauer, N. S., Carroll, A. E., & Downs, S. M. (2014). Understanding the acceptability of a computer decision support system in pediatric primary care. Journal of the American Medical Informatics Association, 21(1), 146–153.

Belliger, A., & Krieger, D. J. (2018). The digital transformation of healthcare. Knowledge Management in Digital Change: New Findings and Practical Cases, 311–326.

Biruk, S., Yilma, T., Andualem, M., & Tilahun, B. (2014). Health Professionals’ readiness to implement electronic medical record system at three hospitals in Ethiopia: a cross sectional study. BMC Medical Informatics and Decision Making, 14(1), 1–8.

Bragazzi, N. L., Khamisy-Farah, R., Converti, M., & Health, I. W.-G. on L. M. (2022). Ensuring equitable, inclusive and meaningful gender identity-and sexual orientation-related data collection in the healthcare sector: insights from a critical, pragmatic systematic review of the literature. International Review of Psychiatry, 34(3–4), 282–291.

Broffman, L., Harrison, S., Zhao, M., Goldman, A., Patnaik, I., & Zhou, M. (2023). The relationship between broadband speeds, device type, demographic characteristics, and care-seeking via telehealth. Telemedicine and E-Health, 29(3), 425–431.

Bush, R. A., Connelly, C. D., Pérez, A., Chan, N., Kuelbs, C., & Chiang, G. J. (2017). Physician perception of the role of the patient portal in pediatric health. The Journal of Ambulatory Care Management, 40(3), 238–245.

Bush, R. A., Kuelbs, C., Ryu, J., Jiang, W., & Chiang, G. (2017). Structured data entry in the electronic medical record: perspectives of pediatric specialty physicians and surgeons. Journal of Medical Systems, 41, 1–8.

Bush, R. A., Richardson, A. C., Cardona-Grau, D., Din, H., Kuelbs, C. L., & Chiang, G. J. (2018). Patient Portal Use in Pediatric Urology—Is it Meaningful Use for Everyone? Urology Practice, 5(4), 279–285.

Chang, F., & Gupta, N. (2015). Progress in electronic medical record adoption in Canada. Canadian Family Physician, 61(12), 1076–1084.

Cho, I., Lee, J., Han, H., Phansalkar, S., & Bates, D. W. (2014). Evaluation of a Korean version of a tool for assessing the incorporation of human factors into a medication-related decision support system: the I-MeDeSA. Applied Clinical Informatics, 5(02), 571–588.

de Oliveira, M. T., Reis, L. H. A., Marquering, H., Zwinderman, A. H., & Olabarriaga, S. D. (2022). Perceptions of a Secure Cloud-Based Solution for Data Sharing During Acute Stroke Care: Qualitative Interview Study. JMIR Formative Research, 6(12), e40061.

El-Yafouri, R., Klieb, L., & Sabatier, V. (2022). Psychological, social and technical factors influencing electronic medical records systems adoption by United States physicians: a systematic model. Health Research Policy and Systems, 20(1). https://doi.org/10.1186/s12961-022-00851-0

Faris Amrullah, Qurratul Aini, (2024). Analyzing Sharia Service Standards in Certified Hospitals for Optimal Healthcare Quality, Journal of Angiotherapy, 8(5), 1-8, 9703

Fayad, R., & Paper, D. (2015). The technology acceptance model e-commerce extension: a conceptual framework. Procedia Economics and Finance, 26, 1000–1006.

Garets, D., & Davis, M. (2006). Electronic medical records vs. electronic health records: yes, there is a difference. Policy White Paper. Chicago, HIMSS Analytics, 1.

Götz, O., Liehr-Gobbers, K., & Krafft, M. (2009). Evaluation of structural equation models using the partial least squares (PLS) approach. In Handbook of partial least squares: Concepts, methods and applications (pp. 691–711). Springer.

Hakiem, L., Dewanto, I., & Jassey, B. (2022). Applying the Healthcare Failure Mode and Effect Analysis (HFMEA) Method for the Risk Management of Self-Developed Electronic Medical Records (EMRs) in Hospitals. International Journal?: JMMR (Jurnal Medicoeticolegal Dan Manajemen Rumah Sakit), 11(3), 245–263.

Honavar, S. G. (2020). Electronic medical records–The good, the bad and the ugly. Indian Journal of Ophthalmology, 68(3), 417.

Hossain, A., Quaresma, R., & Rahman, H. (2019). Investigating factors influencing the physicians’ adoption of electronic health record (EHR) in healthcare system of Bangladesh: An empirical study. International Journal of Information Management, 44, 76–87.

Hsieh, P.-J. (2015). Physicians’ acceptance of electronic medical records exchange: An extension of the decomposed TPB model with institutional trust and perceived risk. International Journal of Medical Informatics, 84(1), 1–14.

Hwang, H.-G., Dutta, B., & Chang, H.-C. (2019). The Differing Effect of Gender and Clinical Specialty on Physicians’ Intention to Use Electronic Medical Record. Methods of Information in Medicine, 58(1), E58–E71. https://doi.org/10.1055/s-0039-1695718

Johnson, M. P., Zheng, K., & Padman, R. (2014). Modeling the longitudinality of user acceptance of technology with an evidence-adaptive clinical decision support system. Decision Support Systems, 57, 444–453.

Jones, D. T., & Kerber, K. A. (2022). Artificial intelligence and the practice of neurology in 2035: the neurology future forecasting series. Neurology, 98(6), 238–245.

Kementerian Kesehatan RI. (2022). Permenkes No.24 Tentang Rekam Medis Elektronik.

Kementerian Kesehatan RI. (2023). Rumah Data untuk Satu Data Kesehatan Indonesia. SATUSEHAT. https://satusehat.kemkes.go.id/data

Kerai, P., Wood, P., & Martin, M. (2014). A pilot study on the views of elderly regional Australians of personally controlled electronic health records. International Journal of Medical Informatics, 83(3), 201–209.

Kernebeck, S., Busse, T. S., Jux, C., Dreier, L. A., Meyer, D., Zenz, D., Zernikow, B., & Ehlers, J. P. (2022). Evaluation of an Electronic Medical Record Module for Nursing Documentation in Paediatric Palliative Care: Involvement of Nurses with a Think-Aloud Approach. International Journal of Environmental Research and Public Health, 19(6), 3637.

Kim, S., Lee, K.-H., Hwang, H., & Yoo, S. (2015). Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital. BMC Medical Informatics and Decision Making, 16(1), 1–12. https://doi.org/10.1186/s12911-016-0249-8

Lakbala, P., & Dindarloo, K. (2014). Physicians’ perception and attitude toward electronic medical record. Springerplus, 3(1), 1–8.

Legesse, B., & Berhanie, D. (2022). Informatics in Medicine Unlocked Barriers to the acceptance of electronic medical records from the perspective of physicians and nurses?: A scoping review. Informatics in Medicine Unlocked, 31(June), 100991. https://doi.org/10.1016/j.imu.2022.100991

Liu, Y., Hao, H., Sharma, M. M., Harris, Y., Scofi, J., Trepp, R., Farmer, B., Ancker, J. S., & Zhang, Y. (2022). Clinician Acceptance of Order Sets for Pain Management: A Survey in Two Urban Hospitals. Applied Clinical Informatics, 13(02), 447–455.

Maillet, É., Mathieu, L., & Sicotte, C. (2015). Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT. International Journal of Medical Informatics, 84(1), 36–47. https://doi.org/10.1016/j.ijmedinf.2014.09.004

Mathai, N., McGill, T., & Toohey, D. (2022). Factors influencing consumer adoption of electronic health records. Journal of Computer Information Systems, 62(2), 267–277.

McCullagh, L. J., Sofianou, A., Kannry, J., Mann, D. M., & McGinn, T. G. (2014). User centered clinical decision support tools. Applied Clinical Informatics, 5(04), 1015–1025.

McCullagh, L., Mann, D., Rosen, L., Kannry, J., & McGinn, T. (2014). Longitudinal adoption rates of complex decision support tools in primary care. BMJ Evidence-Based Medicine, 19(6), 204–209.

Md. Halimuzzaman, Jaideep Sharma et al. (2024). Healthcare Service Quality Digitization with Enterprise Resource Planning, Journal of Angiotherapy, 8(5), 1-11, 9716

Menachemi, N., Matthews, M., Ford, E. W., Hikmet, N., & Brooks, R. G. (2009). The relationship between local hospital IT capabilities and physician EMR adoption. Journal of Medical Systems, 33, 329–335.

Ming, D. Y., Wong, W., Jones, K. A., Antonelli, R. C., Gujral, N., Gonzales, S., Rogers, U., Ratliff, W., Shah, N., & King, H. A. (2023). Feasibility of Implementation of a Mobile Digital Personal Health Record to Coordinate Care for Children and Youth With Special Health Care Needs in Primary Care: Protocol for a Mixed Methods Study. JMIR Research Protocols, 12(1), e46847.

Molisani, S. E., Parikh, D., DiGiovine, M., Dlugos, D., Fitzgerald, M. P., Fried, L., Helbig, I., Kessler, S. K., McDonnell, P. P., & Melamed, S. (2023). A quality improvement initiative to improve folic acid supplementation counseling for adolescent females with epilepsy. Epilepsia, 64(10), 2818–2826.

Noraziani, K., Nurul’Ain, A., Azhim, M. Z., Ekhab, S., Drak, B., Sharifa Ezat, W. P., & Siti Nurul Akma, A. (2013). An overview of electronic medical record implementation in healthcare system: Lesson to learn. World Applied Sciences Journal, 25(2), 323–332. https://doi.org/10.5829/idosi.wasj.2013.25.02.2537

Phansalkar, S., Zachariah, M., Seidling, H. M., Mendes, C., Volk, L., & Bates, D. W. (2014). Evaluation of medication alerts in electronic health records for compliance with human factors principles. Journal of the American Medical Informatics Association, 21(e2), e332–e340.

Qurratul Aini, and  Nur Rachman Dzakiyullah (2024). Leadership Styles in healthcare settings for Hospital Management and Employee Engagement, Journal of Angiotherapy, 8(5), 1-7, 9697

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.

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, 100182.

Silvestre, E. (2018). How Electronic Health Records Strengthen the Health Systems of Low- and Middle-Income Countries: Learning from Eswatini and Mexico. Measure Evaluation, 1(1), 1–10.

Stevens, A. F., & Stetson, P. (2023). Theory of trust and acceptance of artificial intelligence technology (TrAAIT): An instrument to assess clinician trust and acceptance of artificial intelligence. Journal of Biomedical Informatics, 148, 104550.

Strudwick, G., Booth, R., & Mistry, K. (2016). Can social cognitive theories help us understand nurses’ use of electronic health records? CIN: Computers, Informatics, Nursing, 34(4), 169–174.

Sukums, F., Mensah, N., Mpembeni, R., Massawe, S., Duysburgh, E., Williams, A., Kaltschmidt, J., Loukanova, S., Haefeli, W. E., & Blank, A. (2015). Promising adoption of an electronic clinical decision support system for antenatal and intrapartum care in rural primary healthcare facilities in sub-Saharan Africa: The QUALMAT experience. International Journal of Medical Informatics, 84(9), 647–657.

Sultan, A. A., & Noor, S. M. (2017). Absorptive capacity, civil conflict and e-commerce adoption among Iraqi firms. Advanced Science Letters, 23(8), 7992-7995.

Sultan, A. A., Alfaiza, S. A., & Riyadh, H. A. (2022). Impact of mass collaboration on knowledge sharing process using mediating role of innovation capability. International journal of organizational analysis, 30(5), 1085-1099.

Sultan, A. A., Hassan, M. G., & Noor, S. M. (2017). E-Commerce Adoption Among Iraqi Companies: Does Context Matters? QALAAI ZANIST JOURNAL, 2(4), 339-348.

Sultan, A. A., Noor, S. M., & Nasirun, N. (2018). Technological factors and e-commerce adoption among small medium enterprises in Kurdistan, Iraq. Int. J. Eng. Technol, 7(3.5), 98-101.

Tavares, J., & Oliveira, T. (2016). Electronic health record patient portal adoption by health care consumers: an acceptance model and survey. Journal of Medical Internet Research, 18(3), e5069.

Tavares, J., & Oliveira, T. (2017). Electronic health record portal adoption: a cross country analysis. BMC Medical Informatics and Decision Making, 17(1), 1–17.

Tavares, J., Goulão, A., & Oliveira, T. (2018). Electronic health record portals adoption: empirical model based on UTAUT2. Informatics for Health and Social Care, 43(2), 109–125.

Tsai, C. H., Eghdam, A., Davoody, N., Wright, G., Flowerday, S., & Koch, S. (2020). Effects of electronic health record implementation and barriers to adoption and use: A scoping review and qualitative analysis of the content. Life, 10(12), 1–27. https://doi.org/10.3390/life10120327

Turan, A. H., & Koç, T. (2022). Health information technology adoption and acceptance of Turkish physicians-A model proposal and empirical assessment. Health Informatics Journal, 28(2). https://doi.org/10.1177/14604582221096041

van der Nat, D. J., Huiskes, V. J. B., Taks, M., Pouls, B. P. H., van den Bemt, B. J. F., & van Onzenoort, H. A. W. (2022). Usability and perceived usefulness of patient-centered medication reconciliation using a personalized health record: a multicenter cross-sectional study. BMC Health Services Research, 22(1), 1–17.

Venkatesh, V., Sykes, T. A., & Zhang, X. (2011). “Just what the doctor ordered”: a revised UTAUT for EMR system adoption and use by doctors. 2011 44th Hawaii International Conference on System Sciences, 1–10.

Wells, S., Rozenblum, R., Park, A., Dunn, M., & Bates, D. W. (2015). Organizational strategies for promoting patient and provider uptake of personal health records. Journal of the American Medical Informatics Association, 22(1), 213–222.

Witzman, S., Massey, S. L., Kessler, S., Gonzalez-Giraldo, E., Fridinger, S. E., Worden, L., Lewin, N., Dlugos, D., Melamed, S., & Fitzgerald, M. (2020). Acceptability of standardized EEG reporting in an electronic health record. Journal of Clinical Neurophysiology: Official Publication of the American Electroencephalographic Society, 37(5), 455.

Wong, M. C. S., Huang, J., Chan, P. S. F., Lok, V., Leung, C., Wang, J., Cheung, C. S. K., Wong, W. N., Cheung, N. T., Ho, C. P., & Yeoh, E. K. (2020). The perceptions of and factors associated with the adoption of the electronic health record sharing system among patients and physicians: Cross-sectional survey. JMIR Medical Informatics, 8(5). https://doi.org/10.2196/17452

Wylie, M. C., Baier, R. R., & Gardner, R. L. (2014). Perceptions of electronic health record implementation: a statewide survey of physicians in Rhode Island. The American Journal of Medicine, 127(10), 1010-e21.

Yarbrough, A. K., & Smith, T. B. (2007). Technology acceptance among physicians: A new take on TAM. Medical Care Research and Review, 64(6), 650–672. https://doi.org/10.1177/1077558707305942

Yoo, S., Lim, K., Jung, S. Y., Lee, K., Lee, D., Kim, S., Lee, H.-Y., & Hwang, H. (2022). Examining the adoption and implementation of behavioral electronic health records by healthcare professionals based on the clinical adoption framework. BMC Medical Informatics and Decision Making, 22(1), 1–9.

Zeltzer, D., Einav, L., Rashba, J., Waisman, Y., Haimi, M., & Balicer, R. D. (2023). Adoption and utilization of device-assisted telemedicine. Journal of Health Economics, 90, 102780.

Zulfa Nadia Danasti,  Qurratul Aini (2024). Implementation and Impact of Hospital Bylaws in Indonesian Healthcare: A Scoping Review, Journal of Angiotherapy, 8(5), 1-7, 9696