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External Factors in Hospital Information System (HIS) Adoption Model: A Case on Malaysia

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Abstract

Studies related to healthcare ICT integration in Malaysia are relatively little, thus this paper provide a literature review of the integration of information and communication technologies (ICT) in the healthcare sector in Malaysia through the hospital information system (HIS). Our study emphasized on secondary data to investigate the factors related to ICT integration in healthcare through HIS. Therefore this paper aimed to gather an in depth understanding of issues related to HIS adoption, and contributing in fostering HIS adoption in Malaysia and other countries. This paper provides a direction for future research to study the correlation of factors affecting HIS adoption. Finally a research model is proposed using current adoption theories and external factors from human, technology, and organization perspectives.

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Abbreviations

ICT:

Information and Communication Technologies

MSC:

Multimedia Super Corridor

LHP:

Lifetime Health Plan

HIS:

Hospital Information System

EMR:

Electronic Medical Records

CPOE:

Computerised Physician Order Entry

MOH:

Ministry of Health Malaysia

CME:

Continuing Medical Education

PLHP:

Personalised Lifetime Health Plan

CSS:

Clinical Support System

HIMSS:

Healthcare Information Management and Support Services

THIS:

Total Hospital Information System

IHIS:

Intermediate Hospital Information System

BHIS:

Basic Hospital Information System

ICU:

Intensive Care Unit

CCU:

Cardiac Care Unit

NICU:

Neonatal Intensive Care Unit

MCPHIE:

Mass Customized Personalised Health Information and Education

References

  1. Mechanic, D., Physician discomfort challenges and opportunity. J. Am. Med. Assoc. 290(7):941–946, 2003.

    Article  Google Scholar 

  2. Kassirer, J. P., Patients, physicians, and the internet. Health Aff. 19(6):115–123, 2000.

    Article  Google Scholar 

  3. Meyers, S., Concierge medicine: Who really pays for gold standard access to doctors? Trustee 56(1):13–15, 2003.

    Google Scholar 

  4. Menachemi, N., Burke, D. E., and Ayers, D. J., Factors affecting the adoption of telemedicine: A multiple adopter perspective. J. Med. Syst. 28:617–632, 2004.

    Article  Google Scholar 

  5. Stone, K., How many physicians are using Electronic Medical Records (EMR)? Flesh & StoneWeb, 2010 http://www.fleshandstone.net/healthandsciencenews/1863.html. Accessed 14 October 2010.

  6. Ashish, K. J., DesRoches, C. M., Campbell, E. G., Donelan, K., Rao, S. R., Ferris, T. G., et al., Use of electronic health records in U.S. hospitals. N. Engl. J. Med. 360:1628–1638, 2009.

    Article  Google Scholar 

  7. Anastassopoulos, G. C., Danielides, V., Konstantinidis, G., Karakos, A. S., and Anagnostou, E., A user-centered, object-oriented methodology for developing health information systems: A clinical information system (CIS) example. J. Med. Syst. 2010. doi:10.1007/s10916-010-9488-x.

  8. Ministry of Health Malaysia, Health facts 2005. Ministry of Health Malaysia, Kuala Lumpur, 2005.

    Google Scholar 

  9. Ministry of Health Malaysia, Health facts 2006. Ministry of Health Malaysia, Kuala Lumpur, 2006.

    Google Scholar 

  10. Ministry of Health Malaysia, Health facts 2007. Ministry of Health Malaysia, Kuala Lumpur, 2007.

    Google Scholar 

  11. Ministry of Health Malaysia, Health facts 2008. Ministry of Health Malaysia, Kuala Lumpur, 2008.

    Google Scholar 

  12. Ministry of Health Malaysia, Health facts 2009. Ministry of Health Malaysia, Kuala Lumpur, 2009.

    Google Scholar 

  13. World Health Organization, The world health report 2006—working together for health. WHO, Geneva, 2006.

    Google Scholar 

  14. Warne, T., and McAndrew, S., The mental health practitioner: An oxymoron? J. Psychiatr. Ment. Health Nurs. 11:179–184, 2002.

    Article  Google Scholar 

  15. Cruez, A. F., Your Health: When Florence Nightingales Come A-Knockin, 2006. The New Straits Times Malaysia website: http://www.nib.com.my./cross-search/search/_1282141078/. Accessed 15 May 2010.

  16. Zang, J., Patel, V. L., and Johnson, T. R., Medical error: Is solution medical or cognitive? J. Am. Med. Inform. Assoc. 9:75–77, 2002.

    Article  Google Scholar 

  17. Ministry of Health Malaysia, Vision and Mission: Ministry of Health Malaysia, 2010. Ministry of Health Malaysia website. http://www.moh.gov.my/v/visi_mis. Accessed 1 November 2010.

  18. Ministry of Health Malaysia, Telemedicine flagship application: Malaysia telemedicine blue print—leading healthcare into information age. Goverment of Malaysia, Kuala Lumpur, 1997.

    Google Scholar 

  19. Abidi, S. S., Goh, A., and Yusoff, Z., Telemedicine and medical informatics in the multimedia super corridor: the Malaysian vision. In: Cernik, B., McCray, A., and Scherrer, J. (Eds.), MedInfo’98 (9th World Congress on Medical Informatics, August 18–22, Seoul). IOS, Amsterdam, 1999.

    Google Scholar 

  20. Wilhelm, K., Hospital Information System. Springer-Verlag, 1, 2008.

  21. Günther, G., and Thomas, G., Hospital Information System/Electronic Health Record (HIS/HER) and clinical research. Springer, Berlin Heidelberg, 2008.

    Google Scholar 

  22. Hassan, G., Managing a Multiple Hospital HIS Implementation Project. E-Health Asia Conference. Kuala Lumpur, 2004.

  23. Hadis, R., and Hashim, M. A., Telehealth: The Way Forward. E-Health Asia Conference. Kuala Lumpur, 2004.

  24. Hameed, S. A., Mustapha, S., Mardhiyah, A., and Miho, V., Electronic medical record for effective patient monitoring database. International Conference on Computer and Communication Engineering. IEEE Xplore, Kuala Lumpur, pp. 373–378, 2008.

    Google Scholar 

  25. Leong, F. K., THIS: Does it improve nursing care. J. Hosp. Putrajaya 5(4):1–20, 2005.

  26. Multitech, Multitech-Healthcare Enterprise Data Management, 2010. Multitech solutions website.http://www.mulsol.com/solutions.htm. Accessed 1 November 2010.

  27. Sapiah, S., and Rose, A. A., Information ethics in Malaysia paperless hospital. Proceedings of the Postgraduate Annual Research Seminar. Universiti Teknologi Malaysia, Kuala Lumpur, pp. 314–318, 2006.

    Google Scholar 

  28. Thompson, T., and Brailer, D., U.S. Department of Health and Human Service, (2004, July 21). Retrieved November 12, 2010, from The Decade of Health Information Technology: Delivering Consumer-centric and Information-rich Health Care: http://www.hhs.gov/healthit/documents/hitframework.pdf.

  29. Holden, R. J., and Karsh, B. T., The technology acceptance model: Its past and its future in health care. J. Biomed. Inform. 43:159–172, 2010.

    Article  Google Scholar 

  30. England, I., and Stewart, D., Executive management and IT innovation in health: Identifying the barriers to adoption. Health Inform. J. 13:75–87, 2007.

    Article  Google Scholar 

  31. Vishwanath, A., and Scamurra, S. D., Barriers to the adoption of electronic health records: Using concept mapping to develop a comprehensive empirical model. Health Inform. J. 13:119–134, 2007.

    Article  Google Scholar 

  32. Ruxwana, N. L., Herselman, M. E., and Conradie, D. P., ICT applications as e-health solutions in rural healthcare in the Eastern Cape Province of South Africa. Health Inf. Manage. J. 39:17–29, 2010.

    Google Scholar 

  33. Bramble, J. D., Siracuse, M. V., Galt, K. A., Rule, A. M., Clark, B. E., and Paschal, K. A., Examining Barriers to Health Information Technology Adoption (Vol. 7). NA: Emerald Group Publishing Limited, 2008.

  34. Whetstone, M., and Goldsmith, R., Factors influencing intention to use personal health records. Int. J. Pharm. Healthc. Mark. 3(1):8–25, 2009.

    Article  Google Scholar 

  35. James, D. B., Siracuse, M. V., Galt, K. A., Rule, A. M., Clark, B. E., and Pascal, K. A., Examing barrier to health information technology adoption. Adv. Health Care Manag. 7:191–209, 2008.

    Article  Google Scholar 

  36. Han, S., Mustonen, P., and Kallio, M., Does fragmenting of working time and working space influence the acceptance of mobile technology? A case of Finnish physicians. Turku Centre for Computer Science, 2005.

  37. Paré, G., Sicotte, C., and Jacques, H., The effects of creating psychological ownership on physicians’ acceptance of clinical information system. J. Am. Med. Inform. Assoc. 13(2):197–205, 2006.

    Article  Google Scholar 

  38. Chismar, W. G., and Wiley-Patton, S., Test of the technology acceptance model for the internet in pediatrics. Proceedings of the American Medical Informatics Association Symposium, (pp. 155–159), 2002.

  39. Schaper, L. K., and Pervan, G. P., ICT and OTs: A model of information and communication technology acceptance and utilisation by occupational therapists. Int. J. Med. Inform. 17:212–221, 2007.

    Article  Google Scholar 

  40. Hoving, C., Mudde, A. N., and Vries, H. D., Intention to implement a smoking cessation intervention in Dutch general practice. Health Educ. 107(3):307–315, 2007.

    Article  Google Scholar 

  41. Xue, L. S., Yen, C. C., Choolani, M., and Chan, H. C., The perception and intention to adopt female-focused healthcare applications (FHA): A comparison between healthcare workers and non-healthcare workers. Int. J. Med. Inform. 78:248–258, 2009.

    Article  Google Scholar 

  42. Chang, I. C., Hwang, H. G., Hung, W. F., and Li, Y. C., Physicians’ acceptance of pharmacokinetics-based clinical decision support systems. Expert Syst. Appl. 33:296–333, 2007.

    Article  Google Scholar 

  43. Zakaria, N., Mohd Yusof, S. A., and Zakaria, N., Managing ICT in healthcare organization: culture, challenges, and issues of technology adoption and implementation. IGI Global, Hershey, 2010.

    Google Scholar 

  44. Hu, P. J., Chau, P. Y., Liu Sheng, O. R., and Tam, K. Y., Examining the technology acceptance model using physician acceptance of telemedicine technology. J. Manag. Inform. Syst. 16(2):91–112, 1999.

    Google Scholar 

  45. Kilmann, R. H., Saxton, M. J., and Serpa, R., Gaining Control of the Corporate Culture. San Francisco, 1985.

  46. Charles, W. L., and Gareth, R. J., Strategic management. Houghton Mifflin, 2001.

  47. Zakaria, N., and Mohd Yusof, S., The role of human and organization culture in the context of technological change. Proceedings of IEMC Change Management and the New Industrial Revolution. IEEE Xplore, New York, pp. 83–87, 2001.

    Google Scholar 

  48. Jean Lee, S. K., and Yu, K., Corporate culture and organizational performance. J. Manag. Psychol. 19(4):340–359, 2004.

    Article  Google Scholar 

  49. Farquhar, J. D., and Surry, D. W., Adoption analysis: An additional tool for instructional developers. Educ. Train. Tech. Int. 31(1):19–25, 1994.

    Article  Google Scholar 

  50. Rogers, E. M., Diffusion of innovations. Free Press, New York, 1983.

    Google Scholar 

  51. Benjamin, R. I., and Levinson, E., A framework for managing IT-enabled change. Sloan Manage. Rev. 23:33, 1993.

    Google Scholar 

  52. Kounalakis, D. K., Lionis, C., Okkes, I., and Lamberts, H., Developing an appropriate EPR system for the Greek primary care setting. J. Med. Syst. 27(3):239–246, 2003.

    Article  Google Scholar 

  53. Fishbein, M., and Ajzen, I., Belief, attitude, intention and behavior: an introduction to theory and research. Addison-Wesley, Reading, 1975.

    Google Scholar 

  54. Han, S., Individual Adoption of Information Systems in Organisations: A Literature Review of the intention-based Theories. TUCS Technical Report No.539, 2003.

  55. Hale, J. L., Householder, B. J., and Greene, K. L., The theory of reasoned action. In: Dillard, J. P., and Pfau, M. (Eds.), The Persuasion Handbook: Developments in Theory and Practice. Sage, Thousand Oaks, 2003.

    Google Scholar 

  56. Fishbein, M., A reasoned action approach to health promotion. Med. Decis. Mak. 28:834–844, 2008.

    Article  Google Scholar 

  57. Bozionelos, G., and George, B., The theory of planned behaviour as predictor of exercise: The moderating influence of beliefs and personality variables. J. Health Psychol. 4(4):517–529, 1999.

    Article  Google Scholar 

  58. Bandura, A., Self-efficacy: Toward a unifying theory of. Psychol. Rev. 84:191–215, 1997.

    Article  Google Scholar 

  59. Weber, J., and Gillespie, J., Differences in ethical beliefs, intentions and behavior: The role of beliefs and intentions in ethical research revisited. Next Phase Bus. Ethics 3:265–283, 2001.

    Article  Google Scholar 

  60. Tolma, E. L., Reininger, B. M., Evans, A., and Ureda, J., Examining the theory of planned behavior and the construct of self-efficacy to predict mammography intention. Health Educ. Behav. 33(2):233–251, 2006.

    Article  Google Scholar 

  61. Davis, F., Bagozzi, R., and Warshaw, P., User acceptance of computer technology: A comparison of two. Manage. Sci. 35(8):982–1004, 1989.

    Article  Google Scholar 

  62. Ma, Q., and Liu, L., The technology acceptance model: A meta analysis of empirical findings. J. Organ. End User Comput. 43(8):59–72, 2004.

    Article  Google Scholar 

  63. Mathieson, K., Peacock, E., and Chin, W., Extending the technology acceptance model: The influence of perceived user resources. Database Adv. Inf. Syst. 32(3):86–113, 2001.

    Article  Google Scholar 

  64. Yarbrough, A. K., and Smith, T. B., Technology acceptance among physician: A new take on TAM. Med. Care Res. Rev. 64(6):650–672, 2007.

    Google Scholar 

  65. Zheng, K., Padman, R., Johnson, M. P., and Diamond, H. S., Evaluation of healthcare IT applications: The user acceptance perspective. Stud. Comput. Intell. 65:49–78, 2007.

    Article  Google Scholar 

  66. Venkatesh, V., Morris, G. M., Davis, B. G., and Davis, D. F., User acceptance of information technology: Toward a unified view. MIS Quarterly 27:425–478, 2003.

    Google Scholar 

  67. Simon, S. J., and Paper, D., User acceptance of voice recognition technology: An empirical extension of the technology acceptance model. J. Organ. End User Comput. 19(1):24–50, 2007.

    Article  Google Scholar 

  68. Lai, V. S., and Li, H., Technology acceptance model for internet banking: An invariance analysis. Inf. Manage. 42(2):373–386, 2005.

    Article  Google Scholar 

  69. Yu, J., Ha, I., Choi, M., and Rho, J., Extending the TAM for t-commerce. Inf. Manage. 42(7):965–976, 2005.

    Article  Google Scholar 

  70. Venkatesh, V., and Davis, F. D., A theoretical extension of the technology acceptance model: Four longitudinal field studies. Manage. Sci. 46(2):186–204, 2000.

    Article  Google Scholar 

  71. King, W. R., and He, J., A meta-analysis of the technology acceptance model. Inf. Manage. 43(6):740–755, 2006.

    Article  Google Scholar 

  72. Burten-Jones, A., and Hubona, G., The mediation of external variables in the technology acceptance model. Inf. Manage. 43(6):706–718, 2006.

    Article  Google Scholar 

  73. James, T., Pirim, T., Boswell, K., Reithel, B., and Barkhi, R., Determining the intention to use bio-metrics devices: An application and extention of the technology acceptance model. Organ. End User Comput. 18(3):1–24, 2006.

    Article  Google Scholar 

  74. McKechnie, S., Winklhofer, H., and Ennew, C., Applying the technology acceptance model to the online retailing of financial services. Int. J. Retail Distrib. Manag. 34(4):388–410, 2006.

    Article  Google Scholar 

  75. Yi, M. Y., Jackson, J. D., Park, J. S., and Probst, J. C., Understanding information technology acceptance by individual professionals: Towards an integrative view. Inf. Manage. 43(3):350–363, 2006.

    Article  Google Scholar 

  76. Zhang, X., Prybutok, V. R., and Koh, C., The role of impulsiveness in a TAM-based online purchasing behavior model. Inf. Resour. Manage. J. 19(2):54–68, 2006.

    Article  Google Scholar 

  77. Conner, M., and Norman, P., Predicting health behaviour: research and practice with social cognition models. Open University Press, Buckingham, 1996.

    Google Scholar 

  78. Hardeman, W., Johnston, M., Johnston, D. W., Bonetti, D., Wareham, N., and Kinmonth, A. L., Application of the theory of planned behaviour in behaviour change interventions: A systematic review. Psychol. Health 17:123–158, 2002.

    Article  Google Scholar 

  79. Shimp, T., and Kavas, A., The theory of reasoned action applied to coupon usage. J. Consum. Res. 11:795–809, 1984.

    Article  Google Scholar 

  80. Taylor, S., and Todd, P., Decomposition and crossover effects in the theory of planned behavior: a study of consumer adoption intentions. Int. J. Res. Mark. 12:137–155, 1995.

    Article  Google Scholar 

  81. Van Raaij, E. M., and Schepers, J. J., The acceptance and use of a virtual learning environment in China. Comput. Educ. 50(3):838–852, 2008.

    Article  Google Scholar 

  82. Lee, W. L., Malaysia Forecast To Be ‘Young and Poor’ by 2030, 2010. The Malaysian Insider website. http://www.themalaysianinsider.com/malaysia/article/malaysia-forecast-to-be-young-and-poor-by-2030. Accessed 2 August 2010.

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Acknowledgements

We would like to express profound gratitude to our University, Universiti Sains Malaysia for the invaluable support, encouragement, supervision and useful suggestions throughout this paper. The moral support and continuous guidance enabled us to complete our work successfully.

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  1. School of Management, Universiti Sains Malaysia, 11800, Penang, Malaysia

    Heng Wei Lee & Thurasamy Ramayah

  2. School of Computer Sciences, Universiti Sains Malaysia, 11800, Penang, Malaysia

    Nasriah Zakaria

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  1. Heng Wei Lee
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Lee, H.W., Ramayah, T. & Zakaria, N. External Factors in Hospital Information System (HIS) Adoption Model: A Case on Malaysia. J Med Syst 36, 2129–2140 (2012). https://doi.org/10.1007/s10916-011-9675-4

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