Empirical Study of Nova Scotia Nurses’ Adoption of Healthcare Information Systems: Implications for Management and Policy-Making

Document Type: Original Article

Author

Department of Financial and Information Management, Shannon School of Business, Cape Breton University, Sydney, NSW, Canada

Abstract

Background
This paper used the Theory of Planned Behavior (TPB), which was extended, to investigate nurses’ adoption of healthcare information systems (HIS) in Nova Scotia, Canada.
 
Methods
Data was collected from 197 nurses in a survey and data analysis was carried out using the partial least squares (PLS) technique.
 
Results
In contrast to findings in prior studies that used TPB to investigate clinicians’ adoption of technologies in Canada and elsewhere, this study found no statistical significance for the relationships between attitude and subjective norm in relation to nurses’ intention to use HIS. Rather, facilitating organizational conditions was the only TPB variable that explained sampled nurses’ intention to use HIS at work. In particular, effects of computer habit and computer anxiety among older nurses were signified.
 
Conclusion
To encourage nurses’ adoption of HIS, healthcare administrators need to pay attention to facilitating organization conditions at work. Enhancing computer knowledge or competence is important for acceptance. Information presented in the study can be used by administrators of healthcare facilities in the research location and comparable parts of the world to further improve HIS adoption among nurses. The management of nursing professionals, especially in certain contexts (eg, prevalence of older nursing professionals), can make use of this study’s insights.

Keywords

Main Subjects


  1. Villalba-Mora E, Casas I, Lupiañez-Villanueva F, Maghiros I. Adoption of health information technologies by physicians for clinical practice: the Andalusian case. Int J Med Inform. 2015;84(7):477-485. doi:10.1016/j.ijmedinf.2015.03.002
  2. Top M, Gider Ö. Nurses’ views on electronic medical records (EMR) in Turkey: an analysis according to use, quality and user satisfaction. J Med Syst. 2012;36:1979-1988.
  3. Hsiao SJ, Li YC, Chen YL, Ko HC. Critical factors for the adoption of mobile nursing information systems in Taiwan: the nursing department administrators' perspective. J Med Syst. 2009;3(5):369-377.
  4. Hung MC, Jen WY. The adoption of mobile health management services: an empirical study. J Med Syst. 2012;36(3):1381-1388.
  5. Scott RE. e-Records in health—preserving our future. Int J Med Inform. 2007;76:427-431.
  6. 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. doi:10.1016/j.ijmedinf.2007.06.006
  7. Ifinedo P. The moderating effects of demographic and individual characteristics on nurses' acceptance of information systems: a Canadian study. Int J Med Inform. 2016;87:27-35. doi:10.1016/j.ijmedinf.2015.12.012
  8. Poon EG, Jha AK, Christino M, et al. Assessing the level of healthcare information technology adoption in the United States: a snapshot. BMC Med Inform Decis Mak. 2006; 6:1. doi:10.1186/1472-6947-6-1
  9. NSHIS  - Nova Scotia hospital information system (NSHIS) project (2015). https://oag-ns.ca/sites/default/files/publications/2005%20-%20June%20-%20Ch%2006%20-%20NS%20Health%20Info%20Sys.pdf. Accessed August 9, 2017. Published 2015.
  10. Borzekowski R. Measuring the cost impact of hospital information systems: 1987-1994. J Health Econ. 2009;28(5):938-949. doi:10.1016/j.jhealeco.2009.06.004
  11. Jahanbakhsh M, Sharifi M, Ayat M. The status of hospital information systems in Iranian hospitals. Acta Inform Med. 2014;22(4):268–275.
  12. Abandoned NHS IT system has cost £10bn so far. The Guardian. September 18, 2013. https://www.theguardian.com/society/2013/sep/18/nhs-records-system-10bn.
  13. Karsh B-T. Beyond usability: designing effective technology implementation systems to promote patient safety. Qual Saf Health Care. 2004;13:388-394.
  14. Rouleau G, Gagnon M-P, Côté J. Impacts of information and communication technologies on nursing care: an overview of systematic reviews (protocol). Syst Rev. 2015;4:75. doi:10.1186/s13643-015-0062-y
  15. Lee T. Nurses’ perceptions of their documentation experiences in a computerized nursing care planning system. J Clin Nurs. 2006;15:376-382.
  16. Simpson G, Kenrick M. Nurses’ attitudes toward computerization in clinical practice in a British general hospital. Comput Nurs. 1997;15(1):37-42.
  17. Timmons S. Nurses resisting information technology. Nurs Inq. 2003;10:257-269.
  18. Alquraini H, Alhashem AM, Shah MA, Chowdhury RI. Factors influencing nurses’ attitudes towards the use of computerized health information systems in Kuwaiti hospitals. J Adv Nurs. 2007;57(4):375-381.
  19. Gonen A, Sharon D, Offir A, Lev-Ari L. How to enhance nursing students' intention to use information technology: the first step before integrating it in nursing curriculum. Comput Inform Nurs. 2014;32(6):286-293. doi:10.1097/CIN.0000000000000064
  20. Zhang H, Cocosila M, Archer N. Factors of adoption of mobile information technology by homecare nurses: a technology acceptance model 2 approach. Comput Inform Nurs. 2010;28(1):49-56. doi:10.1097/NCN.0b013e3181c0474a
  21. Leblanc G, Gagnon MP, Sanderson D. Determinants of primary care nurses' intention to adopt an electronic health record in their clinical practice. Comput Inform Nurs. 2012;30(9):496-502. doi:10.1097/NXN.0b013e318257db17
  22. Maillet É, Mathieu L, Sicotte C. Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an electronic patient record in acute care settings: an extension of the UTAUT. Int J Med Inform. 2015;84(1):36-47.
  23. Malo C, Neveu X, Archambault PM, Emond M, Gagnon MP. Exploring nurses' intention to use a computerized platform in the resuscitation unit: Development and validation of a questionnaire based on the theory of planned behavior. Interact J Med Res. 2012;1(2):e5. doi:10.2196/ijmr.2150
  24. Gagnon MP, Orruño E, Asua J, Ben Abdeljelil A, Emparanza J. Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system. Telemed J E Health. 2012;18(1):54-59.
  25. Kipturgo MK, Kivuti-Bitok LW, Karani AK, et al. Attitudes of nursing staff towards computerisation: a case of two hospitals in Nairobi, Kenya. BMC Med Inform Decis Mak. 2014;14:35. doi:10.1186/1472-6947-14-35
  26. Javadi M, Kadkhodaee M, Yaghoubi M, Maroufi M, Shams A. Applying theory of planned behavior in predicting of patient safety behaviors of nurses. Mater Sociomed. 2013;25(1):52-55. doi:10.5455/msm.2013.25.52-55
  27. Vanneste D, Vermeulen B, Declercq A. Healthcare professionals' acceptance of BelRAI, a web-based system enabling person-centred recording and data sharing across care settings with interRAI instruments: a UTAUT analysis. BMC Med Inform Decis Mak. 2013,13:129. doi:10.1186/1472-6947-13-129
  28. Ifinedo P, Griscti O, Bailey J, Profit S. Nova Scotia nurses’ acceptance of healthcare information systems: focus on technology characteristics and related factors. Can J Nurs Inform. 2016;11(2):1-13.
  29. Ifinedo P. Using an extended theory of planned behavior to study nurses' adoption of healthcare information systems in Nova Scotia. International Journal of Technology Diffusion. 2017;8(1): 1-17.
  30. Ibbitson J. How the Maritimes became Canada’s incredible shrinking region. The Globe and Mail. https://www.theglobeandmail.com/news/national/how-the-maritimes-became-canadas-incredible-shrinking-region/article23554298/. Published 2015.
  31. Fraser L. Nova Scotia registered nurses oldest in Canada, report says. Herald News. http://thechronicleherald.ca/novascotia/1221311-nova-scotia-registered-nurses-oldest-in-canada-report-says. Published 2014.
  32.  Ifinedo P. An empirical analysis of factors influencing internet/e-business technologies adoption by SMEs in Canada. Int J Inf Technol Decis Mak. 2011;10(4):731-766. 
  33. Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179-211.
  34. Triandis HC. Nebraska symposium on motivation, 1979: beliefs, attitudes and values. In: Page MM, ed. Values, attitudes and interpersonal behavior. Lincoln: University of Nebraska Press; 1980.
  35. Godin G, Bélanger-Gravel A, Eccles M, Grimshaw J. Healthcare professionals' intentions and behaviours: a systematic review of studies based on social cognitive theories. Implement Sci. 2008;3:36.
  36. Holden RJ, Karsh B. The technology acceptance model: its past and its future in health care. J Biomed Inform. 2010;43(1):159-172.
  37. Kivuti L, Chepchirchir A. Computerization readiness. Online Journal of Nursing Informatics. 2011;15(1). http://ojni.org/issues/?p=178.  
  38. Kaya, N. Factors affecting nurses' attitudes toward computers in healthcare. Comput Inform Nurs. 2011;29(2):121-129.
  39. Chung MH, Ho CH, Wen HC. Predicting intentions of nurses to adopt patient personal health records: A structural equation modeling approach. Comput Methods Programs Biomed. 2016.136:45-53. doi:10.1016/j.cmpb.2016.08.004
  40. Asua J, Orruño E, Reviriego E, Gagnon MP. Healthcare professional acceptance of telemonitoring for chronic care patients in primary care. BMC Med Inform Decis Mak. 2012;12:139. doi:10.1186/1472-6947-12-139
  41. Shoham S, Gonen A. Intentions of hospital nurses to work with computers: based on the theory of planned behavior. Comput Inform Nurs. 2008;26(2):106-116.
  42. Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: Toward a unified view. MIS Quart. 2003;27(3):425-478.
  43. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart. 1989;13(3):319-339.
  44. Chau PYK, Hu PJH. Investigating healthcare professionals’ decisions to accept telemedicine technology: An empirical test of competing theories.  Inform Manage. 2002;39:297–311.
  45. Strudwick G, Booth R, Mistry K. Can social cognitive theories help us understand nurses' use of Electronic Health Records? Comput Inform Nurs. 2016;34(4):169-174. doi:10.1097/CIN.0000000000000226
  46. Griebel L, Sedlmayr B, Prokosch HU, Criegee-Rieck M, Sedlmayr M. Key factors for a successful implementation of personalized e-health services. Stud Health Technol Inform. 2013;192:965.
  47. Bozionelos N. Computer anxiety: relationship with computer experience and prevalence. Comput Human Behav. 2001;17:213-224. doi:10.1016/S0747-5632(00)00039-X
  48. Limayem M, Cheung CMK. Understanding information systems continuance: The case of Internet-based learning technologies. Inform Manage. 2008;45:227-232.
  49. Huryk LA. Factors influencing nurses' attitudes towards healthcare information technology. J Nurs Manag. 2010;18:606-612.
  50. Kjerulff KH, Pillar B, Mills ME, Lanigan J. Technology anxiety as a potential mediating factor in response to medical technology. J Med Syst.1992;16:7-13.
  51. Gonen A, Sharon D, Offir A, Lev-Ari L. How to enhance nursing students' intention to use information technology: the first step before integrating it in nursing curriculum. Compu Inform Nurs. 2014;32(6):286-293.
  52. Top M, Yılmaz A. Computer anxiety in nursing: an investigation from Turkish nurses. J Med Syst. 2015; 39(1):1-11.
  53. Vincent C, Reinharz D, Deaudelin I, Garceau M, Talbot LR. Understanding personal determinants in the adoption of telesurveillance in elder home care by community health workers. Journal of Community Practice. 2007;15(3):99-118.
  54. Armitage CJ, Conner M. Efficacy of the theory of planned behaviour: A meta-analytic review. Br J Soc Psychol. 2001;40:471-499.
  55. Canada Nurses Association. 2011 Workforce Profile of Nurse Practitioners in Canada.  https://www.cna-aiic.ca/~/media/cna/files/en/2011_np_work_profiles_e.pdf?la=en. Published 2017.
  56. Compeau DR, Higgins CA, Huff S. Social cognitive theory and individual reactions to computing technology: a longitudinal study. MISQ Q. 1999; 23(2):145-158.
  57. Henseler J, Hubona G Ray PA. Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems. 2016;116(1):2-20. doi:10.1108/IMDS-09-2015-0382
  58. Hair J, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis. 7th ed. Upper saddle River, New Jersey: Pearson Education International; 2010.
  59. Kock N. Advanced mediating effects tests, multi-group analyses, and measurement model assessments in PLS-based SEM. Laredo, TX: ScriptWarp Systems; 2015.
  60. Fornell C, Larcker DF. Evaluating structural equations models with unobservable variables and measurement error. J Mark Res. 1981;8(1):39-50.
  61. Petter S, Straub D, Rai A. Specifying formative constructs in information systems research. MIS Q. 2007;31(4):623-656.
  62. Falk R, Miller NB. A primer for soft-modeling. University of Akron, Ackron, Ohio; 1992.
  63. de Veer AJ, Francke AL. Attitudes of nursing staff towards electronic patient records: a questionnaire survey. Int J Nurs Stud. 2010;47(7):846-854.
  64. Farokhzadian J, Khajouei R, Ahmadian L. Information Seeking and Retrieval Skills of Nurses: Nurses Readiness for Evidence Based Practice in Hospitals of a Medical University in Iran. Int J Med Inform. 2015;84:570-577.
  65. Ketikidis P, Dimitrovski T, Lazuras L, Bath P. Acceptance of health information technology in health professionals: an application of the revised technology acceptance model. Health Inform J. 2012;18:124-134. doi:10.1177/1460458211435425
  66. Kuo KM, Liu CF, Ma CC. An investigation of the effect of nurses’ technology readiness on the acceptance of mobile electronic medical record systems. BMC Med Inform Decis Mak. 2013;13:88. doi:10.1186/1472-6947-13-88
  67. Hsu H-M, Hou Y-H, Chang I-C, Yen DC. 2009. Factors influencing computer literacy of Taiwan and South Korea nurses. J Med Syst. 2009;33(2):133-139.
  68. Matsuda LM, Évora YDM, Higarashi IH, Gabriel CS, Inoue KC. Nursing informatics: unveiling the computer use by nurses. Texto Contexto Enferm. 2015;24(1):178-186. doi:10.1590/0104-07072015002760013