Evaluating the Adoption of Health Information Systems in Mengo and Nsambya Hospitals, Kampala, Uganda
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2018 by IJCTT Journal|
|Year of Publication : 2018|
|Authors : Nahurira Enos, Annabella Habinka Basaza-Ejiri|
|DOI : 10.14445/22312803/IJCTT-V58P101|
Nahurira Enos, Annabella Habinka Basaza-Ejiri , "Evaluating the Adoption of Health Information Systems in Mengo and Nsambya Hospitals, Kampala, Uganda". International Journal of Computer Trends and Technology (IJCTT) V58(1):1-13, April 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
The adoption of Health Information systems plays a key role in improving service delivery, quality of service and improving productivity in the healthcare. In-spite of many years of extra effort by the various facilities and institutions to implement Hospital Information Systems, the adoption of these systems in the healthcare remains low. This is attributed to various adoption models of new Information and Communication Technologies (ICT) has been one of the most challenging issues in developing countries like Uganda. The implementation of new HIS innovations involves fulfilling many requirements ranging from technical to human. This study used the Unified Theory of Acceptance and Use of Technology (UTAUT) model as an evaluation model to understand the behavioural intention on acceptance and use of technology. The study was conducted at Mengo and Nsambya Hospital in Kampala, which are one of the Non-profit faith based public Hospitals in Uganda. Closed and open-ended questionnaires were administered to 150 Hospital Workers. The Staff members who were involved in the management of the targeted information systems were also interviewed. A total of 140 questionnaires were returned accounting to 80.1% response rate. The reliability yielded Cronbach’s output of 0.677. The results indicated that effort expectancy, performance expectancy, social influence, facilitating conditions and Information Systems Skill of workforce as factors affecting the behavioral intention to use Hospital Management Information System (HMIS), which ultimately affects their adoption. The model explained 58.4% of the variance of the ` behavioral intention to use HMIS
 S. M. Metev and V. P. Veiko, Laser Assisted Microtechnology, 2nd ed., R. M. Osgood, Jr., Ed. Berlin, Germany: Springer-Verlag, 1998.
 J. Breckling, Ed., The Analysis of Directional Time Series: Applications to Wind Speed and Direction, ser. Lecture Notes in Statistics. Berlin, Germany: Springer, 1989, vol. 61.
 S. Zhang, C. Zhu, J. K. O. Sin, and P. K. T. Mok, “A novel ultrathin elevated channel low-temperature poly-Si TFT,” IEEE Electron Device Lett., vol. 20, pp. 569–571, Nov. 1999.
 M. Wegmuller, J. P. von der Weid, P. Oberson, and N. Gisin, “High resolution fiber distributed measurements with coherent OFDR,” in Proc. ECOC’00, 2000, paper 11.3.4, p. 109.
 R. E. Sorace, V. S. Reinhardt, and S. A. Vaughn, “High-speed digital-to-RF converter,” U.S. Patent 5 668 842, Sept. 16, 1997.
 (2002) The IEEE website. [Online]. Available: http://www.ieee.org/
 M. Shell. (2002) IEEEtran homepage on CTAN. [Online]. Available: http://www.ctan.org/tex-archive/macros/latex/contrib/supported/IEEEtran/
 FLEXChip Signal Processor (MC68175/D), Motorola, 1996.
 “PDCA12-70 data sheet,” Opto Speed SA, Mezzovico, Switzerland.  A. Karnik, “Performance of TCP congestion control with rate feedback: TCP/ABR and rate adaptive TCP/IP,” M. Eng. thesis, Indian Institute of Science, Bangalore, India, Jan. 1999.  J. Padhye, V. Firoiu, and D. Towsley, “A stochastic model of TCP Reno congestion avoidance and control,” Univ. of Massachusetts, Amherst, MA, CMPSCI Tech. Rep. 99-02, 1999.
 Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specification, IEEE Std. 802.11, 1997.
 1. UN, Universal Sustainable Development Goals; Understanding the Transformational Challenge for Developed Countries. 2015. International Journal of Computer Trends and Technology (IJCTT) – Volume 58 Issue 1- April 2018 ISSN: 2231-2803 http://www.ijcttjournal.org Page 12
 2. Organization, W.H., World Health Statistics 2016: Monitoring Health for the SDGs Sustainable Development Goals. 2016: World Health Organization.
 3. UN, https://unstats.un.org/sdgs/report/2016/. 2016.
 4. Egiebor, O., e-Health and Telemedicine in Nigeria. Available on http://www. jidaw. com. Accessed on 12th August, 2008.
 5. McClure, D., e-Health and Americaâ€™s Broadband Networks An Examination of How Broadband Services Enhance Health Care In America. US: US Internet Industry Association, 2007.
 6. Ancker, J.S., et al., Patient activation and use of an electronic patient portal. Informatics for Health and Social Care, 2015. 40(3): p. 254-266.
 7. Schoen, C., et al., On the front lines of care: primary care doctorsâ€™ office systems, experiences, and views in seven countries. Health Affairs, 2006. 25(6): p. w555-w571.
 8. Jha, A.K., et al., The use of health information technology in seven nations. International journal of medical informatics, 2008. 77(12): p. 848-854.
 9. Mugo, D.M. and D. Nzuki, Determinants of Electronic Health in Developing Countries. 2012.
 10. Cruickshank, J., C. Packman, and J. Paxman, Personal Health Records: Putting Patients in Control? 2012: 2020health. org.
 11. Chen, H.-R. and H.-F. Tseng, Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Evaluation and program planning, 2012. 35(3): p. 398-406.
 12. Ajami, S. and T. Bagheri-Tadi, Barriers for adopting electronic health records (EHRs) by physicians. Acta Informatica Medica, 2013. 21(2): p. 129.
 13. Muathe, S., N. Wawire, and G. Ofafa, An Empirical Study on the Relationship between Organizational Factors and Adoption of ICT among Health Related SMEs in Nairobi, Kenya. 2013.
 14. Organization, W.H., The health of the people: the African regional health report. 2006: World Health Organization.
 15. Amanyire, G., et al., Client and provider perspectives of the efficiency and quality of care in the context of rapid scale-up of antiretroviral therapy. AIDS patient care and STDs, 2010. 24(11): p. 719-727.
 16. Namakula, S. and G. Kituyi, Examining health information systems success factors in Ugandaâ€™s Healthcare System. The Journal of Global Health Care Systems, 2014. 4(1).
 17. Isabalija, S.R., et al., Factors affecting adoption, implementation and sustainability of telemedicine information systems in Uganda. Journal of Health Informatics in Developing Countries, 2011. 5(2).
 18. Jha, A.K., et al., Use of electronic health records in US hospitals. New England Journal of Medicine, 2009. 360(16): p. 1628-1638.
 19. Bonney, W., Impacts and risks of adopting clinical decision support systems. 2011: INTECH Open Access Publisher.
 20. Thiri, N., Factors Influencing The Adoption Of Information System In Private Hospitals In Malaysia. 2006, USM.
 21. Heeks, R., Health information systems: Failure, success and improvisation. International journal of medical informatics, 2006. 75(2): p. 125-137.
 22. Mbarika, V.W. and I. Mbarika, Africa calling [African wireless connection]. IEEE Spectrum, 2006. 43(5): p. 56-60.
 23. Khalifa, M., Barriers to health information systems and electronic medical records implementation. A field study of Saudi Arabian hospitals. Procedia Computer Science, 2013. 21: p. 335-342.
 24. Venkatesh, V. and H. Bala, Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 2008. 39(2): p. 273-315.
 25. Gagnon, M.-P., et al., m-Health adoption by healthcare professionals: a systematic review. Journal of the American Medical Informatics Association, 2016. 23(1): p. 212-220.
 26. Buntin, M.B., et al., The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health Affairs, 2011. 30(3): p. 464-471.
 27. Aggelidis, V.P. and P.D. Chatzoglou, Using a modified technology acceptance model in hospitals. International journal of medical informatics, 2009. 78(2): p. 115-126.
 28. Benson, M. and A. Cole, Hospital information systems in Nigeria: a review of literature. The Journal of Global Health Care Systems, 2011. 1(3).
 29. Almalki, M., G. FitzGerald, and M. Clark, Health care system in Saudi Arabia: an overview/AperÃ§u du systÃ¨me de santÃ© en Arabie saoudite. Eastern Mediterranean health journal, 2011. 17(10): p. 784.
 30. Bah, S., et al., Annual survey on the level and extent of usage of electronic health records in government-related hospitals in Eastern Province, Saudi Arabia. Perspect Health Inf Manag, 2011. 8(Fall): p. 1b.
 31. Williams, F. and S.A. Boren, The role of electronic medical record in care delivery in developing countries. International Journal of Information Management, 2008. 28(6): p. 503-507.
 32. Mutale, W., et al., Improving health information systems for decision making across five sub-Saharan African countries: implementation strategies from the African Health Initiative. BMC health services research, 2013. 13(2): p. S9.
 33. Haughom, J., S. Kriz, and D.R. McMillan, Overcoming barriers to EHR adoption: one health system managed its organizationwide patient health data exchange by first gaining input from clinicians and working cooperatively with competitors. Healthcare Financial Management, 2011. 65(7): p. 96-101.
 34. Gunasekaran, A., et al., An expert diagnosis system for the benchmarking of SMEs` performance. Benchmarking: An International Journal, 2006. 13(1/2): p. 106-119.
 35. Tondeur, J., et al., ICT integration in the classroom: Challenging the potential of a school policy. Computers & Education, 2008. 51(1): p. 212-223.
 36. Boonstra, A. and M. Broekhuis, Barriers to the acceptance of electronic medical records by physicians from systematic review to taxonomy and interventions. BMC health services research, 2010. 10(1): p. 231.
 37. Bhatti, T., Exploring factors influencing the adoption of mobile commerce. The Journal of Internet Banking and Commerce, 2015. 2007.
 38. Holden, R.J., What stands in the way of technology-mediated patient safety improvements? A study of facilitators and barriers to physicians` use of electronic health records. Journal of patient safety, 2011. 7(4): p. 193.
 39. Delone, W.H. and E.R. McLean, The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 2003. 19(4): p. 9-30.
 40. Cresswell, K. and A. Sheikh, Organizational issues in the implementation and adoption of health information technology innovations: an interpretative review. International journal of medical informatics, 2013. 82(5): p. e73-e86.
 41. Venkatesh, V., et al., User acceptance of information technology: Toward a unified view. MIS quarterly, 2003: p. 425-478.
 42. Al-Qeisi, K.I., Analyzing the use of UTAUT model in explaining an online behaviour: Internet banking adoption. 2009, Brunel University Brunel Business School PhD Theses. International Journal of Computer Trends and Technology (IJCTT) – Volume 58 Issue 1- April 2018 ISSN: 2231-2803 http://www.ijcttjournal.org Page 13
 43. Schaper, L.K. and G.P. Pervan, ICT and OTs: A model of information and communication technology acceptance and utilisation by occupational therapists. International journal of medical informatics, 2007. 76: p. S212-S221.
 44. Trochim, W.M., Qualitative validity. Research methods knowledge base, 2006: p. 1-3.
 45. Creswell, J.W., et al., Advanced mixed methods research designs. Handbook of mixed methods in social and behavioral research, 2003: p. 209-240.
 46. Cronbach, L.J., Coefficient alpha and the internal structure of tests. psychometrika, 1951. 16(3): p. 297-334.
 47. Nunnally, J. and I. Bernstein, Psychometric Theory McGraw-Hill New York Google Scholar. 1978.
 48. Hair, J.F., et al., Multivariate data analysis, 6. BaskÄ±. Upper Saddle River, NJ: Pearson Prentice Hall). Hambrick, Donald C., Sydney Finkelstein, Theresa S. Cho ve Eric M. Jackson (2005),â€oeIsomorphism in Reverse: Institutional Theory as an Explanation for Recent Increases in Intraindustry Heterogeneity and Managerial Discretion,â€• Research in Organizational Behavior, 2006. 26: p. 307-350. 
HIMSS-Health Information Management systems Society, HIS-Health Information Systems, IT- Information Technology, ICT-Information Communication Technology, IDT-Innovation of Diffusion Theory, UTAUT-Unified Theory of Acceptance and Use of Technology, WHO-World Health Organization, SDG-Sustainable Development Goal, TAM -Technology Acceptance Model