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A Structural Equation Modeling Approach for the Adoption of Cloud Computing to Enhance the Malaysian Healthcare Sector

  • Systems-Level Quality Improvement
  • Published:
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Abstract

The investments and costs of infrastructure, communication, medical-related equipments, and software within the global healthcare ecosystem portray a rather significant increase. The emergence of this proliferation is then expected to grow. As a result, information and cross-system communication became challenging due to the detached independent systems and subsystems which are not connected. The overall model fit expending over a sample size of 320 were tested with structural equation modelling (SEM) using AMOS 20.0 as the modelling tool. SPSS 20.0 is used to analyse the descriptive statistics and dimension reliability. Results of the study show that system utilisation and system impact dimension influences the overall level of services of the healthcare providers. In addition to that, the findings also suggest that systems integration and security plays a pivotal role for IT resources in healthcare organisations. Through this study, a basis for investigation on the need to improvise the Malaysian healthcare ecosystem and the introduction of a cloud computing platform to host the national healthcare information exchange has been successfully established.

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References

  1. Bakshi SMH, M. S., A study on hospital information system at a tertiary teaching. Global Journal of Computer Science and Technology 12(10), 2012.

  2. Duan, W., Gu, B., and Whinston, A. B., Informational cascades and software adoption on the internet: an empirical investigation. MIS Quarterly 33(1), 2009.

  3. Ismail NI, Abdullah NH An Overview of Hospital Information System (HIS) Implementation In Malaysia. In: 3rd International Conference On Business & Economic Research (3rd ICBER 2012), 2010. pp 1176–1182

  4. Facts, H., Ministry of health Malaysia. Lumpur, Kuala, 2012.

    Google Scholar 

  5. Zhang, J., Patel, V. L., and Johnson, T. R., Medical error: is the solution medical or cognitive? J Am Med Inform Assoc 6(1):75–77, 2002.

    Article  Google Scholar 

  6. Ratnam, K. A., Accelerating MSC telehealth flagship application through adoption of knowledge anagement: making medical knowledge available with windows communication foundation. KMICE, Penang, 2008.

    Google Scholar 

  7. Lee, H. W., Thurasamy, R., and Zakaria, N., External factors in hospital information system (HIS) adoption model: a case on Malaysia. Journal of Medical Systems 36(4):2129–2140, 2012.

    Article  PubMed  Google Scholar 

  8. Deborah, B., Healthy transformation. Intel Corporation, San Francisco, 2011.

    Google Scholar 

  9. Gartner Inc, Top 10 predictions. Gartner Inc, Orlando, 2009.

    Google Scholar 

  10. Cruickshank, B., The cloud changing the business ecosystem. KPMG International Inc, Amstelveen, 2011.

    Google Scholar 

  11. Ton, A. M. S., Cynthia, L., and Ken, T., Back to the future of IT adoption and evaluation in healthcare. International Journal of Healthcare Technology and Management 85(109):85–109, 2011.

    Google Scholar 

  12. Thiri N, Zainuddin Y, Zailani S Determinants of Information System Adoptions in Private Hospitals in Malaysia. In: Information and Communication Technologies: From Theory to Applications, 2008. ICTTA 2008. 3rd International Conference on, 7–11 April 2008. pp 1–2. doi:10.1109/ICTTA.2008.4529931

  13. Horowitz BT (2011) Cloud Computing Brings Challenges for Health Care Data Storage, Privacy. E-Week.

  14. Terry K (2012) Cloud Computing In Healthcare: The Question Is Not If, But When. FierceHealthIT

  15. Chen, Y.-Y., Lu, J.-C., and Jan, J.-K., A secure EHR system based on hybrid clouds. Journal of Medical Systems 36(5):3375–3384, 2012. doi:10.1007/s10916-012-9830-6.

    Article  PubMed  Google Scholar 

  16. Muir E (2011) Challenges of cloud computing in healthcare integration. ZDNET.

  17. Low, C., and Chen, Y., Criteria for the evaluation of a cloud-based hospital information system outsourcing provider. Journal of Medical Systems 36(6):3543–3553, 2012. doi:10.1007/s10916-012-9829-z.

    Article  PubMed  Google Scholar 

  18. J Craig M Cloud Computing: Opportunities and Challenges for Australia. In, 2010. The australian academy of Technological sciences and engineering (aTse),

  19. Elsami, S. K., and Abu Hanna, A., The impact of ComputerisedPhysician order entry in hospitalized patients - a systematic review. International Journal of Medical Informatics 77(6):365–376, 2008.

    Article  Google Scholar 

  20. Fernández-Cardeñosa, G., Torre-Díez, I., López-Coronado, M., and Rodrigues, J. P. C., Analysis of cloud-based solutions on EHRs systems in different scenarios. Journal of Medical Systems 36(6):3777–3782, 2012. doi:10.1007/s10916-012-9850-2.

    Article  PubMed  Google Scholar 

  21. Weston R, Gore Jr. PA (September 2006) A Brief Guide to Structural Equation Modelling. The Counseling Psychologist

  22. Steiger, J. H., Structural model evaluation & modification: an interval estimation approach. Multivariate Behavioural Research 25:173–180, 1990.

    Article  Google Scholar 

  23. Bollen, K. A., and Long, J. S., Testing structural equation models. Sage Publications, New York, 1993.

    Google Scholar 

  24. Byrne, B. M., Structural equation modeling with EQS and EQS/windows. Publications Sage, New York, 1994.

    Google Scholar 

  25. Schumacker, R. E., and Lomax, R. G., A Beginner’s guide to structural equation modeling, Second editionth edition. Lawrence Erlbaum Associates, New Jersey, 2004.

    Google Scholar 

  26. Schulz, W., Ainley, J., and Fraillon, J., ICCS 2009 technical report. International Association for the Evaluation of Educational Achievement (IEA), Amsterdam, 2011.

    Google Scholar 

  27. Fornell C, Larcker DF (1981) Evaluating Structural Equation Models With Unobservable Variables & Measurement Error. Journal of Marketing Research:39–50

  28. Carlson KD, Herdman AO (2010) Understanding the Impact of Convergent on Research Results. Organisational Research Methods:17–32

  29. Chin WW, Gopal A, Salisbury WD (1997) Advancing the Theory of Adaptive Structuration: The Development of a Scale to Measure Faithfulness of Appropriation. Information Systems Research:342–367

  30. Gefen, D., Straub, D. W., and Boudreau, M.-C., Structural equation modelling and regression: guidelines for research practice. Communications of the Association for Information Systems 4(7):1–70, 2000.

    Google Scholar 

  31. Bentler PM, Bonett DG (1980) Significant tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin

  32. Hair, J. F., Black, B. C., and Babin, B. J., Multivariate data analysis, 6th edition. Pearson International, London, 2006.

    Google Scholar 

  33. Buhi, E. R., Goodson, P., and Neilands, T. B., Structural equation modeling: a primer for health behavior researchers. American Journal of Health Behavior 31(1):74–85, 2007.

    Article  PubMed  Google Scholar 

  34. Lovis C (2011) Clinical information systems: cornerstone for an efficient hospital management. Journal of Health Information Technology:69–75

  35. Zarour, K., A coherent architectural framework for the development of hospital information systems. Journal of Applied Medical Informatics 31(4):33–41, 2012.

    Google Scholar 

  36. Crounse, B., Improving efficiency in healthcare. Incorporated Microsoft, Washington, 2010.

    Google Scholar 

  37. Nepal S, Zic J, Jaccard F (2007) A Trusted System for Sharing Patient Electronic Medical Records in Autonomous Distributed Health Care Systems. International Journal of Healthcare Information Systems and Informatics (IJHISI):18–33

  38. Montazemi, A. R., Pittaway, J. J., and Keshavjee, K., State of integration in the context of patient-centered care: a network analysis and research directions. International Journal of Healthcare Information Systems and Informatics 6:11–19, 2011.

    Article  Google Scholar 

  39. Wickramasinghe, N., The competitive forces facing E-health. Int J of Healthcare Information Systems and Informatics 1(4):68–81, 2006.

    Article  Google Scholar 

  40. Sobol, M., Adoption, usage and efficiency: benchmarking healthcare IT in private practices. International Journal of Healthcare Information Systems and Informatics (IJHISI) 6:15–30, 2011.

    Google Scholar 

  41. Reddy, M. C., Bardram, J., and Bardram, P., CSCW research in healthcare: past, present, and future. Microsoft Research Inc, Washington, 2010.

    Google Scholar 

  42. Hecle, R. R., and Lutters, W. G., Tensions of network security and collaborative work practice: understanding a single sign-on deployment in a regional hospital. International Journal of Medical Informatics 80(8):49–61, 2011.

    Article  Google Scholar 

  43. Sekhri, N. K., Managed care transactions. Streamling the Refferal Process, World Health Organisation, 2010.

    Google Scholar 

  44. Ransom G (2012) Insurance ‘prior authorisation’ wastes time, money. The Baltimore Sun

  45. Tuppin P (2010) French national health insurance information system and the permanent beneficiaries sample. Journal of Epidemiology and Public Health:286–290

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Acknowledgments

We gratefully acknowledge the support and generosity of The Ministry of Health Malaysia for providing input towards the survey, without which the present study could not be completed. Many thanks goes to the respondents who participated in this survey.

Statement on conflict of interest

The authors whose names are listed immediately below certify that they have NO affiliations with or involvement in any organisation or entity with any financial interest.

Authors contributions

Kalai Anand Ratnam (Main Author): Design, developing, analyzing, interpreting and drafting article.

Dr P. D. D. Dominic: Revising parts of the article including conclusion, final approval.

Prof. T. Ramayah: Refining the fitness of the Structural Equation Model, final approval.

Author information

Authors and Affiliations

  1. Department of Computers and Information Science, Universiti Teknologi PETRONAS, 31750, Tronoh, Perak, Malaysia

    Kalai Anand Ratnam & P. D. D. Dominic

  2. School of Management, Universiti Sains Malaysia, Minden, 11800, Penang, Malaysia

    T. Ramayah

Authors
  1. Kalai Anand Ratnam
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  2. P. D. D. Dominic
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  3. T. Ramayah
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Corresponding author

Correspondence to Kalai Anand Ratnam.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

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Ratnam, K.A., Dominic, P.D.D. & Ramayah, T. A Structural Equation Modeling Approach for the Adoption of Cloud Computing to Enhance the Malaysian Healthcare Sector. J Med Syst 38, 82 (2014). https://doi.org/10.1007/s10916-014-0082-5

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