Factors influencing adoption of antidote tracking system among healthcare providers in Malaysian hospital setting

References

• Digital technology: the antidote to the health industry’s supply chain woes? – Unipart logistics. Unipart Group; 2020. Available from: https://www.unipart.com/logistics/digital-technology-the-antidote-to-the-health-industrys-supply-chain-woes/
   Google Scholar
• Aboelmaged M, Hashem G. RFID application inpatient and medical asset operations management: a technology, organizational and environmental (TOE) perspective into key enablers and impediments. Int J Med Inf. 2018;118:58–64. DOI:10.1016/j.ijmedinf.2018.07.009
   PubMed Web of Science ®Google Scholar
• Fisher JA, Monahan T. Tracking the social dimensions of RFID systems in hospitals. Int J Med Inf. 2008;77(3):176–183. DOI:10.1016/j.ijmedinf.2007.04.010
   PubMed Web of Science ®Google Scholar
• Mahmood N, Shah A, Waqas A, et al. RFID based smart hospital management system: a conceptual framework. 2014 the 5th International Conference on Information and Communication Technology for the Muslim World, ICT4M 2014; 2014 Feb; 2015. DOI:10.1109/ICT4M.2014.7020594
   Google Scholar
• Tsai MH, Pan CS, Wang CW, et al. RFID medical equipment tracking system based on a location-based service technique. J Med Biol Eng. 2019;39(1):163–169. DOI:10.1007/s40846-018-0446-2
   Web of Science ®Google Scholar
• Ritchie H, Roser M. Causes of death. Our World in Data; 2019. Available from: https://ourworldindata.org/causes-of-death
   Google Scholar
• Antidotes market – global industry trends and forecast to 2027. Data Bridge Market Research; 2020. Available from: https://www.databridgemarketresearch.com/reports/global-antidotes-market
   Google Scholar
• Ministry of Health. Functional requirement brief hospital information system. Vol. FRB/HIS/Ph. Ministry of Health; 2006. ISBN: 983-9417-53-3.
   Google Scholar
• APHM. Member hospitals. Association of Private Hospitals of Malaysia; 2020. Available from: https://hospitals-malaysia.org/member-hospitals/
   Google Scholar
• Ministry of Health. Portal Rasmi Kementerian Kesihatan Malaysia; 2020. Available from: https://www.moh.gov.my/
   Google Scholar
• Ahmadi H, Nilashi M, Shahmoradi L, et al. Hospital information system adoption: expert perspectives on an adoption framework for Malaysian public hospitals. Comput Human Behav. 2017;67:161–189. DOI:10.1016/j.chb.2016.10.023
   Web of Science ®Google Scholar
• Chang IC, Hwang HG, Yen DC, et al. Critical factors for adopting PACS in Taiwan: views of radiology department directors. Decis Support Syst. 2006;42(2):1042–1053. DOI:10.1016/j.dss.2005.08.007
   Web of Science ®Google Scholar
• Soliman KS, Janz BD. An exploratory study to identify the critical factors affecting the decision to establish internet-based interorganizational information systems. Inf Manage. 2004;41(6):697–706. DOI:10.1016/j.im.2003.06.001
   Web of Science ®Google Scholar
• Lian JW, Yen DC, Wang YT. An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital. Int J Inf Manage. 2014;34(1):28–36. DOI:10.1016/j.ijinfomgt.2013.09.004
   Web of Science ®Google Scholar
• Alam MGR, Masum AKM, Beh LS, et al. Critical factors influencing decision to adopt human resource information system (HRIS) in hospitals. PLoS One. 2016;11(8):1–22. DOI:10.1371/journal.pone.0160366
   Web of Science ®Google Scholar
• Hu PJH, Chau PYK, Liu Sheng OR. Adoption of telemedicine technology by health care organizations: an exploratory study. J Org Comput Electron Commer. 2002;12(3):197–221. DOI:10.1207/S15327744JOCE1203_01
   Web of Science ®Google Scholar
• Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. United States of America: Lawrence Erlbaum Associates; 1988.
   Google Scholar
• Nunnally JC. Psychometric theory. New York (NY): McGraw-Hill; 1967.
   Google Scholar
• Hair JF, Black WC, Babin BJ, et al. Multivariate data analysis. 7th ed. Upper Saddle River (NJ): Prentice Hall; 2010.
   Google Scholar
• Gefen D, Straub DW, Boudreau MC. Structural Equation Modeling Technique and regression: Guidelines for Research Practices. Communications for AIS. 2000;7.
   Google Scholar
• Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18:39–50.
   Web of Science ®Google Scholar
• Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci. 2015;43(1):115–135. DOI:10.1007/s11747-014-0403-8
   Web of Science ®Google Scholar
• Hair JF, Hult GTM, Ringle CM, et al. A primer on partial least squares structural equation modeling (PLS-SEM). Third Edition. United States: Sage; 2013.
   Google Scholar
• Fornell C, Cha J. Partial least squares. In: Bagozzi RP, editor. Advanced methods of marketing research. Cambridge: Blackwell; 1994. p. 52–78.
   Google Scholar
• Yazici HJ. An exploratory analysis of hospital perspectives on real time information requirements and perceived benefits of RFID technology for future adoption. Int J Inf Manage. 2014;34(5):603–621. DOI:10.1016/j.ijinfomgt.2014.04.010
   Web of Science ®Google Scholar
• Qu X, Simpson LT, Stanfield P. A model for quantifying the value of RFID-enabled equipment tracking in hospitals. Adv Eng Inf. 2011;25(1):23–31. DOI:10.1016/j.aei.2010.05.005
   Web of Science ®Google Scholar
• Alrahdi DASR. Motivators and barriers impacting the healthcare information technology adoption; 2019.
   Google Scholar
• Sulaiman H. Healthcare information systems assimilation: the Malaysian experience. RMIT University; 2011 July. p. 208.
   Google Scholar
• Hsiao SJ, Li YC, Chen YL, et al. Critical factors for the adoption of mobile nursing information systems in Taiwan: the nursing department administrators’ perspective. J Med Syst. 2009;33(5):369–377. DOI:10.1007/s10916-008-9199-8
   PubMed Web of Science ®Google Scholar
• Lin HF. Understanding the determinants of electronic supply chain management system adoption: using the technology-organization-environment framework. Technol Forecast Soc Change. 2014;86:80–92. DOI:10.1016/j.techfore.2013.09.001
   Web of Science ®Google Scholar
• Malik MA, Khan HR, Astrahan MM, et al. Understanding the implementation of an electronic hospital information system in a developing country: a case study from Pakistan. Technology. 2009;97(Hikm):31–36.
   Google Scholar
• Sulaiman H, Wickramasinghe N. Assimilating healthcare information systems in a Malaysian hospital. Commun Assoc Inf Syst. 2014;34(1):1291–1318. DOI:10.17705/1cais.03477
   Google Scholar
• Arumugam T. Budget for health significantly increased, not reduced [NSTTV]. New Straits Times; 2020. Available from: https://www.nst.com.my/news/nation/2020/11/639435/budget-health-significantly-increased-not-reduced-nsttv
   Google Scholar
• Rogers EM, Singhal A, Quinlan MM. Diffusion of innovations. In: An integrated approach to communication theory and research. 2016 Dec. 3rd ed. New York: Routledge; 2019. p. 415–433. DOI:10.4324/9780203710753-35.
   Google Scholar