Factors influencing nurses' intentions toward the use of mobile electronic medical records

CIN - Computers Informatics Nursing

Volumn 31, Issue 3, 2013, Pages 124-132

  Hsu, Su Chen ^a,b   Liu, Chung Feng ^c   Weng, Rhay Hung ^c   Chen, Chia Jung ^b  

^a CHUNG HWA UNIVERSITY OF MEDICAL TECHNOLOGY   (Taiwan)

^b CHI MEI MEDICAL CENTER   (Taiwan)

^c CHIA NAN UNIVERSITY OF PHARMACY AND SCIENCE   (Taiwan)

Author keywords

Diffusion of Innovations; Mobile electronic medical records; Nurses

Indexed keywords

ARTICLE; CROSS-SECTIONAL STUDY; ELECTRONIC MEDICAL RECORD; HEALTH PERSONNEL ATTITUDE; HUMAN; MASS COMMUNICATION; NURSING STAFF; PSYCHOLOGICAL ASPECT; QUESTIONNAIRE; TAIWAN;

ATTITUDE OF HEALTH PERSONNEL; CROSS-SECTIONAL STUDIES; DIFFUSION OF INNOVATION; HUMANS; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; NURSING STAFF, HOSPITAL; QUESTIONNAIRES; TAIWAN;

EID: 84876153810     PISSN: 15382931     EISSN: 15389774     Source Type: Journal    
DOI: 10.1097/NXN.0b013e318270100b     Document Type: Article

References (44)

1. Hwang JI, Park HA. Factors associated with nurses' informatics competency. Comput Inform Nurs. 2011;29(4):256-262.
2. Toofany S. Nursing and information technology. Nurs Manag. 2006;13(7):18-19.
3. Timmons S. Feature nurses resisting information technology. Nurs Inq. 2003;10(4):257-269. (Pubitemid 37524172)
4. Hsieh SH, Hou IC, Cheng PH, et al. Design and implementation of web-Based mobile electronic medication administration record. J Med Syst. 2010;34(5):947-958.
5. Ammenwerth E, Buchauer A, Bludau B, Haux R. Mobile information and communication tools in the hospital. Int J Med Inform. 2000;57(1):21-40. (Pubitemid 30069904)
6. Choi J, Chun J, Lee K, et al. Mobile Nurse: hand-held information system for point of nursing care. Comput Methods Programs Biomed. 2004;74(3):245-254. (Pubitemid 38591636)
7. Rogers EM. Diffusion of Innovation. 5th ed. New York: Free Press; 2003.
8. CPRI Work Group on CPR Description. Computer-based Patient Record Description of Content. Schaumburg, IL: Computer-based Patient Record Institute; 1996.
9. Institute of Medicine. The Computer-Based Patient Record: An Essential Technology for Health Care. Washington, DC: National Academy Press; 1997.
10. Department of Health and Human Services. The National Alliance for Health Information Technology report to the Office of the National Coordinator for Health Information Technology on defining key health information technology terms. 2008.
11. Ying A. Mobile physician order entry. J Healthc Inf Manag. 2003;17(1):58-63.
12. Prgomet M, Georgiou A, Westbrook JI. The impact of mobile handheld technology on hospital physicians' work practices and patient care: a systematic review. J Am Med Inform Assoc. 2009; 16(6):792-801.
13. Wu RC, Orr MS, Chignell M, et al. Usability of a mobile electronic medical record prototype: a verbal protocol analysis. Inform Health Soc Care. 2008;33(2):139-149.
14. Agarwal R, Prasad J. The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decis Sci. 1997;28(3):557-582. (Pubitemid 128000880)
15. Slyke CV, Belanger F, Comunale CL. Factors influencing the adoption of web-based shopping: the impact of trust. ACM SIGMIS Database. 2004;35(2):32-49.
16. Tsai MC, Lee W, Wu HC. Determinants of RFID adoption intention: evidence from Taiwanese retail chains. Inf Manage. 2010; 47(5-6):255-261.
17. Chew F, Grant W, Tote R. Doctors on-line: using Diffusion of Innovations Theory to understand Internet use. Fam Med. 2004; 36(9):645-650. (Pubitemid 39336622)
18. Di Pietro TMNRN, Coburn GMNRN, Dharamshi NMNRN, et al. What nurses want: diffusion of an innovation. J Nurs Care Qual. 2008;23(2):140-146.
19. Putzer GJ, Park Y. The effects of innovation factors on smartphone adoption among nurses in community hospitals. Perspect Health Inf Manag. 2010;7:1b.
20. Lee TT. Nurses' adoption of technology: application of Rogers' innovation-diffusion model. Appl Nurs Res. 2004;17(4):231-238.
21. Schubart JR, Einbinder JS. Evaluation of a data warehouse in an academic health sciences center. Int J Med Inform. 2000;60(3):319-333. (Pubitemid 32007957)
22. Sleutel M, Guinn M. As good as it gets? Going online with a clinical information system. Comput Nurs. 1999;17(4):181-185.
23. Stricklin ML, Bierer X, Struk C. Home care nurses' attitudes toward computers: a confirmatory factor analysis of the Stronge and Brodt instrument. Comput Inform Nurs. 2003;21(2):103-111.
24. Wu SC, Huang WR, Sun CC, Goo YS, Chu WC. A preliminary analysis of factors influencing the acceptance of nursing staff on the implementation of informationized medication administration system. Tzu Chi Nurs J. 2010;9(5):71-79.
25. Moore GC, Benbasat I. Development of an instrument to measure the perceptions of adopting an information technology innovation. Inf Syst Res. 1991;2(3):192-222.
26. Rogers EM. Diffusion of Innovation. 3rd ed. London: Free Press; 1983.
27. Bradford M, Florin J. Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems. Int J Acc Inform Sys. 2003;4(3):205-225. (Pubitemid 36946047)
28. Hsu CL, Lu HP, Hsu HH. Adoption of the mobile Internet: an empirical study of multimedia message service (MMS). Omega. 2007;35(6):715-726.
29. Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: a comparison of two theoretical models. Manage Sci. 1989;35(8):982-1003.
30. Hair JF, Anderson RE, Tatham RL, et al. Multivariate Data Analysis. 5th ed. Upper Saddle River, NJ: Prentice Hall; 1998.
31. Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18:39-50.
32. Bentler P. EQS Structural Equations Program Manual. Los Angeles: BMDP Statistical Software Links; 1989.
33. Hu L, Bentler P. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1-55.
34. Yi MY, Fiedler KD, Park JS. Understanding the role of individual innovativeness in the acceptance of IT-based innovations: comparative analyses of models and measures. Decis Sci. 2006;37(3):393-426. (Pubitemid 44521312)
35. Palm JM, Dart T, Dupuis I, et al. Clinical Information System Post-Adoption Evaluation at the Georges Pompidou University Hospital. AMIA Annual Symposium Proceedings. Bethesda, MD: American Medical Informatics Association; 2010:582-586.
36. Lee TT, Lee TY, Lin KC, et al. Factors affecting the use of nursing information systems in Taiwan. J Adv Nurs. 2005;50(2):170-178.
37. Tung FC, Chang SC, Chou CM. An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry. Int J Med Inform. 2008;77(5):324-335.
38. Menachemi N, Burke DE, Ayers DJ. Factors affecting the adoption of telemedicine-a multiple adopter perspective. J Med Syst. 2004;28(6):617-632. (Pubitemid 39388730)
39. Kowitlawakul YPRN. The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU). Comput Inform Nurs. 2011;29(7):411-418.
40. Zhang HP, Cocosila MP, Archer NP. Factors of adoption of mobile information technology by homecare nurses: a technology acceptance model 2 approach. Comput Inform Nurs. 2010;28(1): 49-56.
41. Lee TT. Nurses' concerns about using information systems: analysis of comments on a computerized nursing care plan system in Taiwan. J Clin Nurs. 2005;14(3):344-353.
42. Delone WH, McLean ER. The DeLone and McLean model of information systems success: a ten-year update. J Manage Inform Syst. 2003;19(4):9-30.
43. Venkatesh V, Morris MG, Davis GB, et al. User acceptance of information technology: toward a unified view. MIS Q. 2003; 27(3):425-478.
44. Goodhue DL. Understanding user evaluations of information systems. Manage Sci. 1995;41(12):1827-1844.