The Effects of Health Information Technology Change Over Time: A Study of Tele-ICU Functions

Summary

Objective: Longitudinal studies exploring the evolution of health information technology functions provide valuable information about how technology systems are integrated and exploited in situ. This study reports changes in the distribution of functions for a specific health information technology, the tele-ICU, over time. The studied tele-ICU provided care to six remote ICUs within a local geographic region in the same state and had nursing staff around the clock.

Methods: The intervention logs of tele-ICU nurses were collected during two discrete times and coded into nine emergent functional categories, who initiated the intervention and, if required, subsequent escalation. All coded functional categories were investigated for significant changes over time in the nursing logged interventions.

Results: A total of 1927 interventions were coded into the nine emergent functional categories. Seven of the nine categories (78%) were significantly different between 2005 and 2007. The functions of the tele-ICU system continue to change and develop over time.

Conclusion: These findings suggest that the tele-ICU increased support when ICU nurses were off the unit, inter-hospital coordinating and adherence to best practices, while simultaneously decreasing real-time support for ICU nurses. This research suggests that sustaining safety features in a new technology over time have post-conditions after implementation.

Keywords

Medical informatics applications - telemedicine - patient care - intensive care

 

Conflicts of interest

The authors have no conflicts of interest in the research to declare.

• References

• 1 Misono AS. et al. Healthcare information technology interventions to improve cardiovascular and diabetes medication adherence. Am J Managed Care 2010; 16 12 Suppl. HIT SP82.
• 2 Greenhalgh T. et al. Diffusion of innovations in service organizations: systematic review and recommendations. Milbank Q 2004; 82: 581-629.
• 3 Bates DW. et al. Patient risk factors for adverse drug events in hospitalized patients. ADE Prevention Study Group. Arch Intern Med 1999; 159: 2553-2560.
• 4 Hollnagel E, Woods DD, Leveson N. (Eds). Resilience engineering: Concepts and precepts. Burlington: Ash-gate; 2006
• 5 Orlikowski WJ, Hofman JD. An improvisational model for change management: the case of groupware technologies. Sloan management review 1997; 38: 11-22.
• 6 Cook RI, Woods DD. Adapting to new technology in the operating room. Hum Factors 1996; 38: 593-613.
• 7 Woods D, Roesler A. Connecting design with cognition at work. In: Product experience. Schifferstein H, Hekkert P. (Eds). Amsterdam: Elsevier; 2007
• 8 Bhattacherjee A, Premkumar G. Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Q 2004; 28: 229-254.
• 9 Beckley E. VISICU to the rescue. Mod Physician 2003; 7: 24.
• 10 Breslow M. et al. Effect of a multiple-site intensive care unit telemedicine program on clinical and economic outcomes: an alternative paradigm for intensivist staffing. Crit Care Med 2004; 32: 31-38.
• 11 Celi L. et al. The e-ICU: It’s not just telemedicine. Crit Care Med 2001; 29: 183-189.
• 12 Leape LL. et al. Systems analysis of adverse drug events. JAMA 1995; 274: 35-43.
• 13 Valentin A. et al. Errors in adminstration of parenteral drugs in intensive care units: Multinational prospective study. Brit Med J 2009; 338: b814.
• 14 Rothschild J. et al. The critical care safety study: The incidence and nature of adverse events and serious medical errors in intensive care. Crit Care Med 2005; 33: 1694-1700.
• 15 Sapirstein A. et al. Tele ICU: Paradox or panacea. Best Pract & Res Clin Aneasth 2009; 23: 115-126.
• 16 Lilly C. et al Hospital mortality, length of stay, and preventable complications among critically ill patients before and after tele-ICU reenigneering of critical care processes. JAMA 2011; 305: 2175-2175.
• 17 Morrison J. et al Clinical and economic outcomes of the electronic intensive care unit: Results from two community hospitals. Crit Care Med 2010; 38: 2-2.
• 18 Dickhaus D. Delivering intensivist services to patients in multiple states using telemedicine. Crit Care Med 2006; 34: A24.
• 19 Kohl BA, Sites FD, Gutsche JT, Kim P. Economic impact of eICU implementation in an academic surgical ICU. Crit Care Med 2007; 35: A26.
• 20 Thomas EJ. et al. Association of telemedicine for remote monitoring of intensive care patients with mortality, complications, and length of stay. JAMA 2009; 302: 2671.
• 21 Zawada Jr ET. et al. Impact of an intensive care unit telemedicine program on a rural health care system. Postgrad Med 2009; 121: 160-170.
• 22 Aspden P, Corrigan J, Wolcott J, Erickson S. (Eds). Patient safety: Achieving a new standard for care. Washington, DC: National Academies Press; 2004
• 23 Lilly C, Thomas E. Tele-ICU: Experience to date. J Inten Care Med. 2009 (e-pub) 1-7.
• 24 Patterson E. et al. Barriers and facilitatories to increasing access to care with an Electronic Intensive Care Unit (e-ICU). Orlando, FL: AMIA Spring Congress; 2009
• 25 Anders S. et al. Projecting trajectories for a new technology based on cognitive task analysis and archetypal patterns: The electronic ICU. 8th Annual Naturalistic Decision Making Conference 2007. Asilomar, CA: 2007
• 26 Woods DD, Hollnagel E. Joint cognitive systems: Patterns in cognitive systems engineering. Boca Raton, FL: Taylor & Francis; 2006