Telemedicine Intensive Care Unit Nursing Interventions to Prevent Failure to Rescue

Am J Crit Care. 2019 Jan;28(1):64-75. doi: 10.4037/ajcc2019577.

Abstract

Background: Although telemedicine intensive care unit (tele-ICU) nurses are integral to the tele-ICU model of care, few studies have explored the influence of tele-ICU nursing interventions on preventing failure to rescue in critically ill patients.

Objective: To determine how tele-ICU nurses characterize their interventions to prevent failure to rescue.

Methods: This qualitative interpretive study recruited a purposive sample from 11 tele-ICU centers across the United States for structured open-ended interviews. An inductive and deductive approach suitable for health services qualitative research was adapted to further explain and extend a relevant conceptual framework for tele-ICU nursing practice.

Results: Of 33 nurses practicing in tele-ICUs who responded to a recruitment email, 19 participated in this study. Findings included 4 major interrelated themes: (1) fundamental attributes of the tele-ICU nurse, (2) proactive clinical practice, (3) effective collaborative relationships, and (4) strategic use of advanced technology.

Conclusion: A conceptual framework extending the American Association of Critical-Care Nurses model of success for tele-ICU nursing practice is proposed to prevent failure to rescue. Tele-ICU nurses use systems thinking and integration of complex factors in their practice to prevent failure to rescue. Tele-ICU nurses' perception of their role in preventing failure to rescue and emotional intelligence competence are key to building and maintaining effective relationships with the ICU. Tele-ICU nurses' intentional use of advanced technology, rather than the technology itself, supports and enhances proactive tele-ICU practice to prevent failure to rescue.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Critical Care Nursing / methods*
  • Failure to Rescue, Health Care / statistics & numerical data*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Qualitative Research
  • Telemedicine / methods*
  • United States