These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Intensive care telemedicine: evaluating a model for proactive remote monitoring and intervention in the critical care setting.
    Author: Groves RH, Holcomb BW, Smith ML.
    Journal: Stud Health Technol Inform; 2008; 131():131-46. PubMed ID: 18305328.
    Abstract:
    Historically, telemedicine has focused on the application of traditional physician-to-patient (and physician-to-physician) interactions enhanced by two-way video and audio capability. This "one-on-one" interaction via a telemedicine link can dramatically extend a physician's or other caregiver's geographic range and availability. However, this same telemedicine model is most often implemented "on-demand" for a specified time-limited encounter. The remote Intensive Care Unit (ICU) model to be described similarly expands the geographic range of ICU physicians, but also allows a single specialist to simultaneously monitor multiple patients on a continuous basis by leveraging computerized "intelligent" algorithms and an electronic medical record interface. This new application of telemedicine wedded to computer technology facilitates maximum leveraging of specialists' cognitive skills but also mandates significant process changes in how ICU services are provided. In short, the remote ICU represents a "re-engineering" of how ICU care is delivered and establishes a new paradigm for the field of telemedicine, expanding the reach, scope and availability of intensivist specialty expertise.The re-engineering occurs through a number of ways. First, the telemedicine connection is continuously available in a pro-active fashion that can be provided 24 hours a day, 7 days a week (24/7). Secondly, the system utilizes computerized clinical intelligence algorithms with direct electronic links to physiologic, laboratory and lab/pharmacy data as well as patient diagnoses to focus attention on potential adverse outcomes or trends in individual patients and notify caregivers before trends manifest as adverse outcomes. Third, the traditional physician, nurse, and patient relationship is substantially augmented when there is an ICU physician immediately available to address issues in patient care, particularly at night when physicians are less likely to be present at the bedside. The current preliminary data suggest that this system can be quite effective in improving ICU quality of care, thus leading to reductions in the cost of ICU care, ICU patient mortality, ICU patient outliers, and ICU length of stay (LOS). Given the extensive data showing improved ICU outcomes with daily ICU physician participation in care of critically ill patients, and the national shortage of ICU physicians, nurses, and ancillary staff; the electronic ICU system is gaining popularity as an alternative paradigm for the expansion of an ICU team's expertise in the care of the severely ill. Interestingly, internal Quality Improvement (QI) data from several healthcare systems have shown that improved outcomes occur even when remote ICU telemedicine is applied to a pre-existing 24/7 in-house intensivist care model. The reasons for this remain speculative at this point, but pro-active and hourly remote "virtual rounds" on the most critically-ill patients, and use of computerized algorithms in triaging ICU physicians' attention may contribute to the success of this system. Also, we will show how the system supports key elements of error reduction theory even in well-staffed critical care units. Multiple challenges remain before remote ICU systems become more broadly accepted and applied. These include cost of implementation of the system, resistance to the system by ICU physicians and nurses, and integration of data systems and clinical information into the remote electronic ICU model. In this chapter, we will provide background information on error reduction theory and the role of the remote ICU model, review current data supporting use of the remote ICU system, address the current obstacles to effective implementation, and look to the future of the field for solutions to these challenges.
    [Abstract] [Full Text] [Related] [New Search]