210
Views
6
CrossRef citations to date
0
Altmetric
Articles

Assessing the risk of hospital information system implementation using IVIF FMEA approach

ORCID Icon &
Pages 676-689 | Received 18 Nov 2018, Accepted 25 Oct 2019, Published online: 06 Jan 2020

References

  • Chiasson MW, Davidson E. Pushing the contextual envelope: developing and diffusing IS theory for health information systems research. Inf Organ. 2004;14(3):155–188.
  • Chau PY, Hu PJ-H. Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories. Inform Manage. 2002;39(4):297–311.
  • Wager KA, Lee FW, Glaser JP. Managing? health care information systems: a practical approach for health care executives. San Francisco: John Wiley & Sons; 2005.
  • Eslami Andargoli A, Scheepers H, Rajendran D, et al. Health information systems evaluation frameworks: A systematic review. Int J Med Inform. 2017;97:195–209.
  • Mohamadali NA, Ab Aziz NF. The technology factors as barriers for sustainable health information systems (HIS)–A Review. Procedia Comput Sci. 2017;124:370–378.
  • Choi E, Bahadori MT, Song L, et al. GRAM: graph-based attention model for healthcare representation learning). Proceedings of the 23rd ACM SIGKDD International Conference on knowledge Discovery and data Mining; 2017. ACM.
  • Farzandipur M. Factors affecting successful implementation of hospital information systems. Acta Inform Med. 2016;24(1):51.
  • Ammenwerth E, Ehlers F, Hirsch B, et al. HIS-Monitor: an approach to assess the quality of information processing in hospitals. Int J Med Inform. 2007;76(2–3):216–225.
  • Effken J, McGonigle D, Mastrian K. The human-technology interface. nursing informatics and the foundation of knowledge. 3rd ed. Burlington: Jones & Bartlett Publishers; 2014; p. 201–216.
  • Hajeer SaI. Critical risk factors for information system (IS) projects (IS) projects between Sink and Swim. Int J Comput Sci Eng Technol. 2012;2(6):1270–1279.
  • Amin IM, Hussein SS, Isa W. Assessing user satisfaction of using hospital information system (HIS) in Malaysia. People. 2011;12:13.
  • Tabibi J, Nasiripour AA, Kazemzadeh RB, et al. Effective factors on hospital information system acceptance: A confirmatory study in Iranian hospitals. Middle-East J Sci Res. 2011;9(1):95–101.
  • Ismail A, Jamil AT, Rahman AFA, et al. The implementation of hospital information system (HIS) in tertiary hospitals in Malaysia: a qualitative study. Malaysian J Public Health Med. 2010;10(2):16–24.
  • Samy GN, Ahmad R, Ismail Z. Threats to health information security. 2009 Fifth International Conference on information Assurance and Security; 2009. IEEE.
  • Robertson ID, Saveraid T. Hospital, radiology, and picture archiving and communication systems. Vet Radiol Ultrasound. 2008;49:S19–S28.
  • Sligo J, Gauld R, Roberts V, et al. A literature review for large-scale health information system project planning, implementation and evaluation. Int J Med Inform. 2017;97:86–97.
  • Kimiafar KH, Moradi GR, Sadoughi F, et al. A study on the user's views on the quality of teaching hospitals information system of Mashhad University of medical Sciences-2006; 2007.
  • Sulaiman H, Wickramasinghe N. Assimilating healthcare information systems in a Malaysian hospital. Commun Assoc Info Syst. 2014;34:Article 77.
  • Ahmadi H, Nilashi M, Ibrahim O. Organizational decision to adopt hospital information system: an empirical investigation in the case of Malaysian public hospitals. Int J Med Inform. 2015;84(3):166–188.
  • Chen R-F, Hsiao J-L. An investigation on physicians’ acceptance of hospital information systems: a case study. Int J Med Inform. 2012;81(12):810–820.
  • Ammenwerth E, Brender J, Nykänen P, et al. Visions and strategies to improve evaluation of health information systems: Reflections and lessons based on the HIS-EVAL workshop in Innsbruck. Int J Med Inform. 2004;73(6):479–491.
  • Carvalho JV, Rocha Á, van de Wetering R, et al. A Maturity model for hospital information systems. J Bus Res. 2019;94:388–399.
  • Borzekowski R. Measuring the cost impact of hospital information systems: 1987–1994. J Health Econ. 2009;28(5):938–949.
  • Sharifian R, Askarian F, Nematolahi M, et al. Factors influencing nurses’ acceptance of hospital information systems in Iran: application of the unified theory of acceptance and use of technology. Health Information Management Journal. 2014;43(3):23–28.
  • Nauman AB, Aziz R, Ishaq A. Information systems development failure: a case study to highlight the IS development complexities in simple, low risk projects in developing countries). The Second International Conference on Innovations in information technology; Dubai: UAE University. 2005.
  • Segismundo A, Augusto Cauchick Miguel P. Failure mode and effects analysis (FMEA) in the context of risk management in new product development: a case study in an automotive company. Int J Qual Reliab Manage. 2008;25(9):899–912.
  • Ireson WG, Coombs Jr CF, Moss RY. Handbook of reliability engineering and management 2/E. McGraw Hill Professional; 1995.
  • Zaman MB, Kobayashi E, Wakabayashi N, et al. Fuzzy FMEA model for risk evaluation of ship collisions in the Malacca Strait: based on AIS data. J Simulat. 2014;8(1):91–104.
  • Abdelgawad M, Fayek AR. Risk management in the construction industry using combined fuzzy FMEA and fuzzy AHP. J Constr Eng Manag. 2010;136(9):1028–1036.
  • Wessiani NA, Sarwoko SO. Risk analysis of poultry feed production using fuzzy FMEA. Procedia Manufact. 2015;4:270–281.
  • Tooranloo HS, sadat Ayatollah A. A model for failure mode and effects analysis based on intuitionistic fuzzy approach. Appl Soft Comput. 2016;49:238–247.
  • Kumru M, Kumru PY. Fuzzy FMEA application to improve purchasing process in a public hospital. Appl Soft Comput. 2013;13(1):721–733.
  • Thakare V, Khire G. Role of emerging technology for building smart hospital information system. Procedia Econom Finan. 2014;11:583–588.
  • Bahadori M, Hosseini SM, Teymourzadeh E, et al. A supplier selection model for hospitals using a combination of artificial neural network and fuzzy VIKOR. Int J Healthc Manag. 2017: 1–9. doi: 10.1080/20479700.2017.1404730
  • Ratnaningtyas DD, Surendro K. Information quality improvement model on hospital information system using six sigma. Procedia Technology. 2013;9:1166–1172.
  • Khalifa M, Alswailem O. Hospital information systems (HIS) acceptance and satisfaction: a case study of a tertiary care hospital. Procedia Comput Sci. 2015;63:198–204.
  • Shortliffe EH, Barnett GO. Biomedical data: their acquisition, storage, and use. In: Shortliffe EH, Cimino JJ, editors. Biomedical informatics. Health informatics. New York (NY): Springer; 2006. p. 46–79.
  • Handayani PW, Hidayanto AN, Ayuningtyas D, et al. Hospital information system institutionalization processes in Indonesian public, government-owned and privately owned hospitals. Int J Med Inform. 2016;95:17–34.
  • Reichertz PL. Hospital information systems—past, present, future. Int J Med Inform. 2006;75(3-4):282–299.
  • Vegoda PR. Introduction to hospital information systems. Int J Clin Monit Comput. 1987;4(2):105–109.
  • Liu C, Yang P, Yeh Y, et al. The impacts of smart cards on hospital information systems — an investigation of the first phase of the national health insurance smart card project in Taiwan. Int J Med Inform. 2006;75(2):173–181.
  • Breton M, Lamothe L, Denis J-L. How healthcare organisations can act as institutional entrepreneurs in a context of change. J Health Organ Manag. 2014;28(1):77–95.
  • Ransom E. The healthcare quality book: vision strategy, and tools. Chicago (IL): Health Administration Press; 2005.
  • Özogul CO, Karsak EE, Tolga E. A real options approach for evaluation and justification of a hospital information system. J Syst Softw. 2009;82(12):2091–2102.
  • Hillestad R, Bigelow J, Bower A, et al. Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. Health Aff. 2005;24(5):1103–1117.
  • Nilashi M, Ahmadi H, Ahani A, et al. Determining the importance of hospital information system adoption factors using fuzzy analytic network process (ANP). Technol Forecast Soc Change. 2016;111:244–264.
  • Lee HW, Ramayah T, Zakaria N. External factors in hospital information system (HIS) adoption model: a case on Malaysia. J Med Syst. 2012;36(4):2129–2140.
  • Triantaphyllou E, Shu B, Sanchez SN, et al. Multi-criteria decision making: an operations research approach. Encyclopedia Electr Electron Eng. 1998;15:175–186.
  • Kensing F, Sigurdardottir H, Stoop A. MUST-a participatory method for designing sustainable health IT in Medinfo 2007. Proceedings of the 12th World Congress on health (medical) Informatics; Building sustainable health systems; 2007. IOS Press.
  • Meli P. Perspectives of health information management faculty use of an e-learning laboratory and technology acceptance; 2008. Electronic Theses and Dissertations. 3557. Available from: https://stars.library.ucf.edu/etd/3557.
  • Karsh B-T, Weinger MB, Abbott PA, et al. Health information technology: fallacies and sober realities. J Am Med Inform Assoc. 2010;17(6):617–623.
  • Yusof MM, Stergioulas L, Zugic J. Health information systems adoption: findings from a systematic review. Stud Health Technol Inform. 2007;129(1):262.
  • Koivunen M. Acceptance and use of information technology among nurses in psychiatric hospitals. Turku: Department of Nursing Science, University of Turku; 2009.
  • Yu P, Li H, Gagnon M-P. Health IT acceptance factors in long-term care facilities: a cross-sectional survey. Int J Med Inform. 2009;78(4):219–229.
  • Wilkins MA. Factors influencing acceptance of electronic health records in hospitals. Perspectives in Health Information Management/AHIMA. 2009;6(Fall):1–20. American Health Information Management Association.
  • Hamidfar M, Limayem M, Zegordi SH. Using the UTAUT model to Explore Iranian physicians and nurses’ Intention to adopt Electronic patient records). CSREA EEE; 2008.
  • Giuse DA, Kuhn KA. Health information systems challenges: the Heidelberg conference and the future. Int J Med Inform. 2003;69(2–3):105–114.
  • Aarts J, Gorman P. IT in health care: sociotechnical approaches” to err is system”. Int J Med Inform. 2007;76(Suppl. 1):S1–S3.
  • Selder A. Physician reimbursement and technology adoption. J Health Econ. 2005;24(5):907–930.
  • Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: a comparison of two theoretical models. Manage Sci. 1989;35(8):982–1003.
  • Beuscart-Zéphir MC, Anceaux F, Crinquette V, et al. Integrating users’ activity modeling in the design and assessment of hospital electronic patient records: the example of anesthesia. Int J Med Inform. 2001;64(2-3):157–171.
  • Littlejohns P, Wyatt JC, Garvican L. Evaluating computerised health information systems: hard lessons still to be learnt. Br Med J. 2003;326(7394):860–863.
  • Laudon K, Laudon J. Information systems management: organization and technology. International conference. Hershey, (PA): Prentice Hall; 2001.
  • Chatzoglou PD, Vraimaki E, Diamantidis A, et al. Computer acceptance in Greek SMEs. J Small Bus Enterprise Dev. 2010;17(1):78–101.
  • McGinn CA, Grenier S, Duplantie J, et al. Comparison of user groups’ perspectives of barriers and facilitators to implementing electronic health records: a systematic review. BMC Med. 2011;9(1):46.
  • Lyytinen K, Mathiassen L, Ropponen J. Attention shaping and software risk—a categorical analysis of four classical risk management approaches. Inf Syst Res. 1998;9(3):233–255.
  • Jiang JJ, Klein G. Information system project-selection criteria variations within strategic classes. IEEE Trans Eng Manage. 1999;46(2):171–176.
  • Murray-Webster R, Thiry M. Managing programmes of projects. In: Gower handbook of project management, Vol. 3. Aldershot: Gower; 2000. p. 47–64.
  • Schmidt R, Lyytinen K, Keil M, et al. Identifying software project risks: an international Delphi study. J Manage Inf Syst. 2001;17(4):5–36.
  • Yardley D. How to ensure your next It project Is a success: learning the Lessons of project failure. Boston (MA): Addison-Wesley Longman Publishing; 2002.
  • Smith DR, Wei N, Zhang Y-J, et al. Musculoskeletal complaints and psychosocial risk factors among physicians in mainland China. Int J Ind Ergon. 2006;36(6):599–603.
  • Kappelman LA, McKeeman R, Zhang L. Early warning signs of IT project failure: The dominant dozen. Inf Syst Manage. 2006;23(4):31–36.
  • Yucel G, Cebi S, Hoege B, et al. A fuzzy risk assessment model for hospital information system implementation. Expert Syst Appl. 2012;39(1):1211–1218.
  • Chang K-H, Cheng C-H. A risk assessment methodology using intuitionistic fuzzy set in FMEA. Int J Syst Sci. 2010;41(12):1457–1471.
  • Kahraman C, Kaya İ, Şenvar Ö. Healthcare failure mode and effects analysis under fuzziness. Human Ecol Risk Assess. 2013;19(2):538–552.
  • Chanamool N, Naenna T. Fuzzy FMEA application to improve decision-making process in an emergency department. Appl Soft Comput. 2016;43:441–453.
  • Liu H-C, Liu L, Lin Q-L. Fuzzy failure mode and effects analysis using fuzzy evidential reasoning and belief rule-based methodology. IEEE Trans Reliab. 2013;62(1):23–36.
  • Oraee K, Yazdani-Chamzini A, Basiri MH . Evaluating underground mining hazards by fuzzy FMEA). 2011 SME Annual Meeting & Exhibit and CMA 113th national Western Mining Conference” Shaping a strong Future through Mining”; 2011. Society for Mining, Metallurgy & Exploration.
  • Meng Tay K, Peng Lim C. Fuzzy FMEA with a guided rules reduction system for prioritization of failures. Int J Qual Reliab Manage. 2006;23(8):1047–1066.
  • Liu H-C, Liu L, Liu N. Risk evaluation approaches in failure mode and effects analysis: a literature review. Expert Syst Appl. 2013;40(2):828–838.
  • Rivera SS, Mc Leod JEN. Recommendations generated about a discontinuous distillation plant of biofuel). Proceedings of the World Congress on Engineering; 2009. WCE London UK.
  • Kutlu AC, Ekmekçioğlu M. Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Syst Appl. 2012;39(1):61–67.
  • Rafie M, Namin FS. Prediction of subsidence risk by FMEA using artificial neural network and fuzzy inference system. Int J Mining Sci Technol. 2015;25(4):655–663.
  • Atanassov K. Review and new results on intuitionistic fuzzy sets. preprint IM-MFAIS-1-88, sofia; 1988. 5. p. l.
  • Atanassov K, Gargov G. Elements of intuitionistic fuzzy logic. Part I. Fuzzy Sets Syst. 1998;95(1):39–52.
  • Wu J, Huang H-b, Cao Q-w. Research on AHP with interval-valued intuitionistic fuzzy sets and its application in multi-criteria decision making problems. Appl Math Model. 2013;37(24):9898–9906.
  • Xu Z. Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making. Control Decis. 2007;22(2):215–219.
  • Chaojie L, Hongli J. Selection of social Security Fund investment manager based on ER. Journal of Xidian University (Social Science Edition). 2011;(4):2.
  • Keil M, Cule PE, Lyytinen K, et al. A framework for identifying software project risks. Vol. 41. New York: Association for Computing Machinery; 1998.
  • Smith SC, Allen J, Blair SN, et al. AHA/ACC guidelines for secondary prevention for patients with coronary and other atherosclerotic vascular disease: 2006 update: endorsed by the national Heart, Lung, and Blood institute. J Am Coll Cardiol. 2006;47(10):2130–2139.
  • Yardley J, Leroy BP, Hart-Holden N, et al. Mutations of VMD2 splicing regulators cause nanophthalmos and autosomal dominant vitreoretinochoroidopathy (ADVIRC). Invest Ophthalmol Vis Sci. 2004;45(10):3683–3689.
  • Flowers S. Software failure, management failure: amazing stories and cautionary tales. Chichester: John Wiley; 1996.
  • McFarlan F, McKenney J. Information systems planning: a Contingent focus. Harvard Business School Case. 1981;181:128.
  • Boehm BW. Software risk management: principles and practices. IEEE Softw. 1991;8(1):32–41.
  • McFarlan FW. Portfolio approach to information systems. In: Boehm BW., editor. Software risk management. Piscataway (NJ): IEEE Press; 1989. p. 17–25.
  • Barki H, Rivard S, Talbot J. Toward an assessment of software development risk. J Manage Inf Syst. 1993;10(2):203–225.
  • Ewusi-Mensah K. Critical issues in abandoned information systems development projects. Commun ACM. 1997;40(9):74–80.
  • Zmud RW. Management of large software development efforts. MIS Q. 1980;4(2):45–55.
  • Lærum H, Karlsen TH, Faxvaag A. Use of and attitudes to a hospital information system by medical secretaries, nurses and physicians deprived of the paper-based medical record: a case report. BMC Med Inform Decis Mak. 2004;4(1):18.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.