Factors Determining Nurse Acceptance of Hospital Information Systems in the Medication Process

Hesamaddin Kamalzadeh Takhti, Azizah Abdul Rahman, Samireh Abedini


A growing interest in implementing Hospital Information Systems to improve the patient safety and nurses’ unwillingness to integrate HIS into their workflow, justifies further research into the factors influencing nurses’ acceptance of those systems in the medication process. This study recruited practicing nurses from a Malaysian public hospital. A total of 227 questionnaires were sent, and 186 were returned, for a response rate of 82%. Structural equation modelling using the partial least squares method was utilized to evaluate measurement and structural models. The findings showed that nurses’ intention to use an HIS was significantly influenced by two factors: trustworthiness of the information and perceived usefulness. Furthermore, these two factors can be predicted by information quality. Consequently, the model explains 72% of the variance in intention to use an HIS. These findings strongly support the proposed model and highlight the important roles of information quality and trust in predicting nurses’ intention to use an HIS in the medication process.


Medication errors, Hospital information systems, Patient Safety, Nursing

Full Text:

Abstract PDF


Abdrbo, A. A., Hudak, C. A., Anthony, M. K. & Douglas, S. L. 2011. Information Systems Use, Benefits, And Satisfaction Among Ohio Rns. Computers, Informatics, Nursing, 29, 59-65.

Abedini, S., Sihes, A. J. B., Takhti, H. K. & Abedini, S. 2011. Assessing Nursing Curriculum: Graduate Nurse Viewpoints. Canadian Journal Of Nursing Informatics, 6.

Aggelidis, V. P. & Chatzoglou, P. D. 2009. Using A Modified Technology Acceptance Model In Hospitals. International Journal Of Medical Informatics 78 115-126.

Ahmadi, H., Nilashi, M., & Ibrahim, O. (2015). Prioritizing Critical Factors to Successful Adoption of Total Hospital Information System. Journal of Soft Computing and Decision Support Systems, 2(4), 6-16.

Ahmadi, H., Nilashi, M., & Ibrahim, O. (2015). Organizational decision to adopt hospital information system: An empirical investigation in the case of Malaysian public hospitals. International journal of medical informatics, 84(3), 166-188.

Ahmadi, H., Nilashi, M., Ibrahim, O., Ramayah, T., Wong, M. W., Alizadeh, M., ... & Almaee, A. (2015). Exploring Potential Factors in Total Hospital Information System Adoption. Journal of Soft Computing and Decision Support Systems, 2(1), 52-59.

Ahmadi, H., Ibrahim, O., & Nilashi, M. (2015). Investigating a New Framework for Hospital Information System Adoption: A Case on Malaysia. Journal of Soft Computing and Decision Support Systems, 2(2), 26-33.

Ammenwertha, E., Gräberb, S., Herrmannc, G., Bürkled, T. & Königb, J. 2003. Evaluation Of Health Information Systems-Problems And Challenges. International Journal Of Medical Informatics, 71, 125-135.

Callen, J., Mcintosh, J. & Li, J. 2010. Accuracy Of Medication Documentation In Hospital Discharge Summaries: A Retrospective Analysis Of Medication Transcription Errors In Manual And Electronic Discharge Summaries. International Journal Of Medical Informatics, 79, 58-64.

Chiang, H.-Y., Lin, S.-Y., Hsu, S.-C. & Ma, S.-C. 2010 Factors Determining Hospital Nurses’ Failures In Reporting Medication Errors In Taiwan. Nursing Outlook, 58, 17-25.

Chin, W. W. 1998. The Partial Least Squares Approach To Structural Equation Modeling. In: Marcoulides, G. A. (Ed.) Modern Methods For Business Research. London: Lawrence Erlbaum.

Davis, F. D. 1989. Perceived Usefulness,Perceived Ease Of Use, And User Acceptance Of Information Technology. Mis Quarterly, 13, 319-340.

Delone, W. H. & Mclean, E. R. 2003. The Delone And Mclean Model Of Information Systems Success:A Ten-Year Update. Journal Of Management Information Systems, 19, 9-30.

Dünnebeil, S., Sunyaev, A., Blohm, I., Leimeister, J. M. & Krcmar, H. 2012. Determinants Of Physicians’ Technology Acceptance For E-Health In Ambulatory Care. International Journal Of Medical Informatics.

Egea, J. M. O. & González, M. V. R. 2011. Explaining Physicians’ Acceptance Of Ehcr Systems: An Extension Of Tam With Trust And Risk Factors. Computers In Human Behavior, 27 319-332.

Fahimi, F., Nazari, M. A., Abrishami, R., Sistanizad, M., Mazidi, T., Faghihi, T., Soltani, R. & Baniasadi, S. 2009. Transcription Errors Observed In A Teaching Hospital Arch Iran Med, 12, 173-175.

Fogg, B. J. Prominence-Interpretation Theory: Explaining How People Assess Credibility Online. Human Factors In Computing Systems, 2003 Florida. 722-723.

Fornell, C. & Larcker, D. F. 1981. Evaluating Structural Equation Models With Unobservabl E Variables And Measurement Error. Marketing Research, 18 39–50.

Heimar, M. 2004. Improving Patient Safety With Technology. International Journal Of Medical Informatics, 73, 543-546.

Holden, R. J. & Karsh, B. T. 2010. The Technology Acceptance Model: Its Past And Its Future In Health Care. Biomedical Informatics, 43 159-172.

Hung, S., Ku, Y. & Chien, J. 2012. Understanding Physicians’ Acceptance Of The Medline System For Practicing Evidence-Based Medicine: A Decomposed Tpb Model. International Journal Of Medical Informatics, 81, 130-142.

Jen, W.-Y. & Chao, C.-C. 2008. Measuring Mobile Patient Safety Information System Success: An Empirical Study. International Journal Of Medical Informatics, 77, 689-697.

Kijsanayotina, B., Pannarunothai, S. & Speedie, S. M. 2009. Factors Influencing Health Information Technology Adoption In Thailand’s Community Health Centers:Applying The Utaut Model. International Journal Of Medical Informatics 78, 404-416.

Kim, J., Hong, S., Min, J. & Lee, H. 2011. Antecedents Of Application Service Continuance: A Synthesis Of Satisfaction And Trust. Expert Systems With Applications 38 9530-9542.

Koppel, R., Metlay, J. P., Cohen, A., Abaluck, B., Localio, A. R., Kimmel, S. E. & Strom, B. L. 2005. Role Of Computerized Physician Order Entry Systems In Facilitating Medication Errors. Journal Of The American Medical Association, 293, 1197-203.

Koval, D. 2005. Real-World Rhio. A Regional Health Information Organization Blazes A Trail In Upstate New York. American Health Information Management Association, 76, 44-48.

Lee, S. & Mcelmurry, B. 2010. Capturing Nursing Care Workflow Disruptions:Comparison Between Nursing And Physician Workflows. Computers, Informatics, Nursing 28, 151-159.

Mäenpää, T., Suominen, T., Asikainen, P., Maass, M. & Rostila, I. 2009. The Outcomes Of Regional Healthcare Information Systems In Health Care: A Review Of The Research Literature. International Journal Of Medical Informatics, 78, 757.

Marin, H. F. 2004. Improving Patient Safety With Technology. International Journal Of Medical Informatics, 73, 543-546.

Melas, C. D., Zampetakis, L. A., Dimopoulou, A. & Moustakis, M. 2011. Modeling The Acceptance Of Clinical Information Systems Among Hospital Medical Staff: An Extended Tam Model. Biomedical Informatics

Menke, J. A., Broner, C. W., Campbell, D. Y., Mckissick, M. Y. & Edwards-Beckett, J. A. 2001. Computerized Clinical Documentation System In The Pediatric Intensive Care Unit. Bmc Medical Informatics & Decision Making, 1.

Mohd, H. & Mohamad, S. M. S. 2005. Acceptance Model Of Electronic Medical Record. Advancing Information And Management Studies, 2, 75-92.

Nelson, N. C., Evans, R. S., Samore, M. H. & Gardner, R. M. 2005. Detection And Prevention Of Medication Errors Using Real-Time Bedside Nurse Charting. The American Medical Informatics Association 12, 390-397.

Overhage, J. M., Evans, L. & Marchibroda, J. 2005. Communities’readiness For Health Information Exchang E: The National Landscape In 2004. Am Med Inform Assoc, 12, 107-112.

Pai, F.-Y. & Huang, K.-I. 2011a. Applying The Technology Acceptance Model To The Introduction Of Healthcare Information Systems. Technological Forecasting And Social Change, 78, 650–660.

Pai, F.-Y. & Huang, K.-I. 2011b. Applying The Technology Acceptance Model To The Introduction Of Healthcare Information Systems. Technological Forecasting And Social Change, 78, 650-660.

Ramayah, T., Ahmad, N. H. & Lo, M.-C. 2010. The Role Of Quality Factors In Intention To Continue Using An E-Learning System In Malaysia Procedia Social And Behavioral Sciences, 2, 5422-5426.

Ringle, C. M., Sarstedt, M. & Straub, D. W. 2012. A Critical Look At The Use Of Pls-Sem In Mis Quarterly. Mis Quarterly, 36, Iii-8.

Schumacher, K. & Lee, W. Y. 2008. Heterogeneous Quality Information In Healthcare Marketplace. In: Klinger, K. (Ed.) Healthcare Information Systems. United States Of America: Information Science Reference.

Tung, F. C., Chang, S. C. & Chou, C. M. 2008. An Extension Of Trust And Tam Model With Idt In The Adoption Of The Electronic Logistics Information System In His In The Medical Industry. International Journal Of Medical Informatics 77 324-335.

Urbach, N. & Ahlemann, F. 2010. Structural Equation Modeling In Information Systems Research Using Partial Least Squares. Information Technology Theory And Application, 11, 5-40.

Venkatesh, V. & Davis, F. D. 2000. A Theoretical Extension Of The Technology Acceptance Model:Four Longitudinal Field Studies Management Science, 46, 186-204.

Wu, I. L., Li, J. Y. & Fu, C. Y. 2011. The Adoption Of Mobile Healthcare By Hospital's Professionals:An Integrative Perspective. Decision Support Systems 51 587-596.

Yamane, T. 1967. Statistics, An Introductory Analysis, New York.

Yu, P., Li, H. & Gagnon, M.-P. 2009. Health It Acceptance Factors In Long-Term Care Facilities:A Cross-Sectional Survey. International Journal Of Medical Informatics, 78, 219–229.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.