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Nurses’ Demographic and Professional Characteristics and Their Acceptance of Hospital Information Systems: Basis for a Nurse–Centered HIS Acceptance Enhancement Framework


Authors : Jocelyn V. Bautista

Volume/Issue : Volume 11 - 2026, Issue 5 - May


Google Scholar : https://tinyurl.com/3yb9x65c

Scribd : https://tinyurl.com/mr2c7sb5

DOI : https://doi.org/10.38124/ijisrt/26May480

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : This study examined nurses’ demographic and professional characteristics and their acceptance of the Hospital Information System (HIS) as the basis for the development of a Nurse–Centered HIS Acceptance Enhancement Framework. Specifically, the study described the respondents’ profile in terms of age, sex, years of nursing experience, area of practice, perceived level of computer skills, frequency and duration of HIS usage, and HIS-related training. It also determined the level of HIS acceptance in terms of perceived usefulness and perceived ease of use. The study utilized a descriptive cross-sectional survey design and involved 121 licensed registered nurses from Quirino Memorial Medical Center who had at least one year of HIS experience. Data were gathered using an adapted and validated questionnaire based on the Technology Acceptance Model and were analyzed using frequency, percentage, mean, and standard deviation. Findings revealed that most respondents were female, mid-career nurses with good computer skills and daily HIS usage. The respondents demonstrated a moderate level of HIS acceptance, with perceived usefulness obtaining a moderate level while perceived ease of use remained neutral. The findings indicated that nurses recognized the efficiency and productivity benefits of HIS; however, usability concerns such as interface complexity and workflow integration challenges persisted. Based on the results, a Nurse–Centered Hospital Information System Acceptance Enhancement Framework was proposed to improve system usability, user engagement, workflow compatibility, and technology adoption among nurses. The study highlighted the importance of user-centered strategies and targeted interventions in strengthening digital healthcare implementation and improving the quality of patient care.

Keywords : Hospital Information System, Nursing Acceptance, Perceived Usefulness, Perceived Ease of Use, Technology Acceptance Model.

References :

  1. Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A. (2023). “Extending the Technology Acceptance Model (TAM) to predict university students’ intentions to use Metaverse-Based Learning platforms”. Education and Information Technologies, 28(11), 15381–15413. https://doi.org/10.1007/s10639-023-11816-3
  2. Alam, M. S., Khan, T., Dhar, S. S., & Munira, K. S. (2020). HR professionals’ intention to adopt and use of artificial intelligence in recruiting talents. Business Perspective Review, 2(2), 15–30. https://doi.org/10.38157/business-perspective-review.v2i2.122
  3. Almalki, M. J., FitzGerald, G., & Clark, M. (2012). The relationship between quality of work life and turnover intention of primary health care nurses in Saudi Arabia. BMC Health Services Research, 12(1), 314. https://doi.org/10.1186/1472-6963-12-314
  4. Alsyouf, A., Lutfi, A., Alsubahi, N., Alhazmi, F. N., Al-Mugheed, K., Anshasi, R. J., Alharbi, N. I., & Albugami, M. (2023). The use of a Technology acceptance model (TAM) to predict patients’ usage of a personal health record system: the role of security, privacy, and usability. International Journal of Environmental Research and Public Health, 20(2), 1347. https://doi.org/10.3390/ijerph20021347
  5. Ameen, N., Willis, R., Abdullah, M. N., & Shah, M. (2018). Towards the successful integration of e‐learning systems in higher education in Iraq: A student perspective. British Journal of Educational Technology, 50(3), 1434–1446. https://doi.org/10.1111/bjet.12651
  6. An, H., Park, W., Liu, P., & Park, S. (2025). Mobile-AI-Based Docent System: Navigation and localization for visually impaired gallery visitors. Applied Sciences, 15(9), 5161. https://doi.org/10.3390/app15095161
  7. 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), e57. https://doi.org/10.2196/jmir.1726
  8. Aurore, N., Valens, M., Lune, N. J., & Nyssen, M. (2016). Assessment of health informatics competencies in undergraduate training of healthcare professionals in Rwanda. Rwanda Journal, 3(1), 36. https://doi.org/10.4314/rj.v3i1.6f
  9. Biruk, K., & Abetu, E. (2018). Knowledge and Attitude of Health Professionals toward Telemedicine in Resource-Limited Settings: A Cross-Sectional Study in North West Ethiopia. Journal of Healthcare Engineering, 2018, 1–7. https://doi.org/10.1155/2018/2389268
  10. Burgess, J., & Honey, M. (2022). Nurse Leaders enabling nurses to adopt Digital health: Results of an Integrative literature review. Nursing Praxis in Aotearoa New Zealand, 38(3). https://doi.org/10.36951/001c.40333
  11. Cerchione, R., Centobelli, P., Riccio, E., Abbate, S., & Oropallo, E. (2022). Blockchain’s coming to hospital to digitalize healthcare services: Designing a distributed electronic health record ecosystem. Technovation, 120, 102480. https://doi.org/10.1016/j.technovation.2022.102480
  12. Cezar-Vaz, M. R., Xavier, D. M., Bonow, C. A., Vaz, J. C., Cardoso, L. S., Sant’Anna, C. F., & Da Costa, V. Z. (2022). Domains of Physical and Mental Workload in Health Work and Unpaid Domestic Work by Gender Division: A Study with Primary Health Care Workers in Brazil. International Journal of Environmental Research and Public Health, 19(16), 9816. https://doi.org/10.3390/ijerph19169816
  13. Comparcini, D., Simonetti, V., Totaro, M., Tomietto, M., Forastefano, B., Jarva, E., Pastore, F., Minoia, F., Gullo, B., Rea, T., Guillari, A., Mikkonen, K., & Cicolini, G. (2025). Profiling Healthcare Professionals’ digital health Competence and Associated Factors: A Cross‐Sectional Study. Journal of Advanced Nursing. https://doi.org/10.1111/jan.70435
  14. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
  15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
  16. Davis, F.D., Bagozzi, R.P. & Warshaw, P.R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35 (8), 982-1003.
  17. Demsash, A. W., Kalayou, M. H., & Walle, A. D. (2024). Health professionals’ acceptance of mobile-based clinical guideline application in a resource-limited setting: using a modified UTAUT model. BMC Medical Education, 24(1), 689. https://doi.org/10.1186/s12909-024-05680-z
  18. Dopp, A. R., Parisi, K. E., Munson, S. A., & Lyon, A. R. (2018). A glossary of user-centered design strategies for implementation experts. Translational Behavioral Medicine, 9(6), 1057–1064. https://doi.org/10.1093/tbm/iby119
  19. Enabulele, A. B. O., Eleweke, C. C., Okechukwu, O., Akanbi, O. O., & Majesty, C. (2025). A Strategic Project Management Framework for implementing Patient-Centered Digital Health Record Systems to improve chronic disease outcomes in the United States. Journal of Sustainable Research and Development, 1(2), 55–67. https://doi.org/10.69739/jsrd.v1i2.1217
  20. Etikan, I., & Bala, K. (2017). Sampling and sampling methods. Biometrics and Biostatistics International Journal, 5(6), 00149. https://doi.org/10.15406/bbij.2017.05.00149
  21. Fedorko, I., Bačik, R., & Gavurova, B. (2022). Analysis of selected technology acceptance model constructs and their impact on user behavior. Innovative Marketing, 18(3), 72–83. https://doi.org/10.21511/im.18(3).2022.07
  22. He, Y., Chen, Q., & Kitkuakul, S. (2018). Regulatory focus and technology acceptance: Perceived ease of use and usefulness as efficacy. Cogent Business & Management, 5(1), 1459006. https://doi.org/10.1080/23311975.2018.1459006
  23. Holden, R. J., & Karsh, B. T. (2010). The technology acceptance model: Its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159–172. https://doi.org/10.1016/j.jbi.2009.07.002
  24. Kelley, K., Clark, B., Brown, V., & Sitzia, J. (2003). Good practice in the conduct and reporting of survey research. International Journal for Quality in Health Care, 15(3), 261–266. https://doi.org/10.1093/intqhc/mzg031
  25. Kim, S. C., Shah, D. V., Namkoong, K., McTavish, F. M., & Gustafson, D. H. (2013). Predictors of Online Health Information Seeking Among Women with Breast Cancer: The Role of Social Support Perception and Emotional Well-Being. Journal of Computer-Mediated Communication, 18(2), 98–118. https://doi.org/10.1111/jcc4.12002
  26. Kotp, M. H., Ismail, H. A., Basyouny, H. a. A., Aly, M. A., Hendy, A., Nashwan, A. J., Hendy, A., & Elmoaty, A. E. E. A. (2025). Empowering nurse leaders: readiness for AI integration and the perceived benefits of predictive analytics. BMC Nursing, 24(1), 56. https://doi.org/10.1186/s12912-024-02653-x
  27. Lyon, J. Y., Bogodistov, Y., & Moormann, J. (2021). AI-driven Optimization in Healthcare: the Diagnostic Process. European Journal of Management Issues, 29(4), 218–231. https://doi.org/10.15421/192121
  28. Mara, U. T., Suhaimi, A., Mulud, Z. A., Mara, U. T., Sharoni, S. K. A., Mara, U. T., Zainodin, W. H. W., & Mara, U. T. (2023). FACTORS CONTRIBUTED TO JOB SATISFACTION AMONG NURSES WORKING AT TERTIARY HOSPITALS IN THE KLANG VALLEY: AN ADAPTATION OF THE HERZBERG’S THEORY. Journal of Sustainability Science and Management, 18(6), 135–148. https://doi.org/10.46754/jssm.2023.06.012
  29. Mazmi, F. I. A. (2025). Utilizing Artificial Intelligence in Government Communication: adoption and implementation. Journal of Information Systems Engineering & Management, 10(49s), 543–553. https://doi.org/10.52783/jisem.v10i49s.9905
  30. Miller, K. S. (2024). Informatics and Nursing: Opportunities and Challenges. Lippincott Williams & Wilkins.
  31. Omol, E. J. (2023). Organizational digital transformation: from evolution to future trends. Digital Transformation and Society, 3(3), 240–256. https://doi.org/10.1108/dts-08-2023-0061
  32. Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Wolters Kluwer.
  33. Rojas-Sánchez, M. A., Palos-Sánchez, P. R., & Folgado-Fernández, J. A. (2022). Systematic literature review and bibliometric analysis on virtual reality and education. Education and Information Technologies, 28(1), 155–192. https://doi.org/10.1007/s10639-022-11167-5
  34. Scherer, R., Siddiq, F., & Tondeur, J. (2018). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
  35. Scherer, R., Siddiq, F., & Tondeur, J. (2018). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
  36. Setia, M. S. (2016). Methodology series module 3: Cross-sectional studies. Indian Journal of Dermatology, 61(3), 261–264. https://doi.org/10.4103/0019-5154.182410
  37. Sinha, M., Fukey, L., Balasubramanian, K., Hanafiah, M. H., Kunasekaran, P., & Ragavan, N. A. (2021). Acceptance of Consumer-Oriented Health Information Technologies (CHITs): Integrating Technology Acceptance Model with Perceived Risk. Informatica, 45(6). https://doi.org/10.31449/inf.v45i6.3484
  38. Sinha, M., Fukey, L., Balasubramanian, K., Hanafiah, M. H., Kunasekaran, P., & Ragavan, N. A. (2021b). Acceptance of Consumer-Oriented Health Information Technologies (CHITs): Integrating Technology Acceptance Model with Perceived Risk. Informatica, 45(6). https://doi.org/10.31449/inf.v45i6.3484
  39. Sofilkanych, M. (2022). The formation of a new information culture of the future: the socio-philosophical content. Futurity Philosophy., 56–67. https://doi.org/10.57125/fp.2022.03.30.05
  40. Venkatesh, V., Thong, J., & 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
  41. Verina, C., Yanti, A. R., & Andry, A. (2025). Organizational culture and leadership affect nurses’ use of EMR through work motivation at Hospital X Tangerang. Epaper Bisnis., 2(3), 228–245. https://doi.org/10.61132/epaperbisnis.v2i3.557
  42. Villemagne, V., Burnham, S., Bourgeat, P., Reiman, E., Quiroz, Y., Fleisher, A., Jack, C., Lowe, V., Weigand, S., Bateman, R., Xiong, C., Benzinger, T., Gordon, B., Blazey, T., Su, Y., Braak, H., Thal, D., Ghebremedhin, E., Tredici, D., . . . Brayne, C. (2023). 2023 Alzheimer’s disease facts and figures. Alzheimer S & Dementia, 19(4), 1598–1695. https://doi.org/10.1002/alz.13016
  43. Wan, D., & Guo, Z. (2025). Research on Digital transformation of hospital Finance based on "Big Data + Cloud Platform. Journal of Sustainable Competitive Intelligence, 15, e0576. https://doi.org/10.37497/eaglesustainable.v15i.576
  44. World Medical Association. (2013). World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA, 310(20), 2191–2194. https://doi.org/10.1001/jama.2013.281053
  45. Wynn, M., & Garwood‐Cross, L. (2024). Reassembling nursing in the digital age: An actor‐network theory perspective. Nursing Inquiry, 31(4), e12655. https://doi.org/10.1111/nin.12655

This study examined nurses’ demographic and professional characteristics and their acceptance of the Hospital Information System (HIS) as the basis for the development of a Nurse–Centered HIS Acceptance Enhancement Framework. Specifically, the study described the respondents’ profile in terms of age, sex, years of nursing experience, area of practice, perceived level of computer skills, frequency and duration of HIS usage, and HIS-related training. It also determined the level of HIS acceptance in terms of perceived usefulness and perceived ease of use. The study utilized a descriptive cross-sectional survey design and involved 121 licensed registered nurses from Quirino Memorial Medical Center who had at least one year of HIS experience. Data were gathered using an adapted and validated questionnaire based on the Technology Acceptance Model and were analyzed using frequency, percentage, mean, and standard deviation. Findings revealed that most respondents were female, mid-career nurses with good computer skills and daily HIS usage. The respondents demonstrated a moderate level of HIS acceptance, with perceived usefulness obtaining a moderate level while perceived ease of use remained neutral. The findings indicated that nurses recognized the efficiency and productivity benefits of HIS; however, usability concerns such as interface complexity and workflow integration challenges persisted. Based on the results, a Nurse–Centered Hospital Information System Acceptance Enhancement Framework was proposed to improve system usability, user engagement, workflow compatibility, and technology adoption among nurses. The study highlighted the importance of user-centered strategies and targeted interventions in strengthening digital healthcare implementation and improving the quality of patient care.

Keywords : Hospital Information System, Nursing Acceptance, Perceived Usefulness, Perceived Ease of Use, Technology Acceptance Model.

Paper Submission Last Date
30 - June - 2026

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