Intensive Care Unit Telemedicine Research Articles

Bedside Nurse Acceptance of Intensive Care Unit Telemedicine Presence.

Since 2010, health care organizations have rapidly adopted telemedicine as part of their health care delivery system to inpatients and outpatients. The application of telemedicine in the intensive care unit is often referred to as tele-ICU In telemedicine, nurses, nurse practitioners, physicians, and other health care professionals provide patient monitoring and intervention from a remote location. Tele-ICU presence has demonstrated positive outcomes such as increased adherence to evidence-based care and improved perception of support at the bedside. Despite the successes, acceptance of tele-ICU varies. Known barriers to acceptance include perceptions of intrusiveness and invasion of privacy.

Screening for retinopathy of prematurity by telemedicine in a tertiary level neonatal intensive care unit in France: Review of a six-year period

To analyze the prevalence and risk factors for retinopathy of prematurity (ROP) and severe (treatment-requiring) ROP. A retrospective study was conducted in a level III neonatal unit in Bordeaux, France, from 2009 to 2015. Four hundred and nineteen preterm infants who were screened for ROP exclusively by RetCam were included. ROP of any degree was diagnosed in 27.68% of infants. Stages 1, 2, 3 and 4 ROP was found in 44%, 46%, 9% and 1% of subjects, respectively. No stage 5 ROP was observed. 28/419 infants (6.6%) were treated exclusively with laser photocoagulation. No intravitreal anti-VEGF injections or surgical treatments were performed. No infants born at>31 weeks or with BW>1110g required ROP treatment. On multivariate analysis, risk factors for ROP development were low birth weight, low gestational age at birth, high duration of invasive mechanical ventilation, shock or use of vasopressors. On multivariate analysis, risk factors for severe, treatment-requiring ROP were male gender, gestational age≤27 weeks and Apgar score at 5minutes≤7. In our 6-year series, ROP was successfully identified on screening exclusively by telemedicine, and no surgical treatment was required. This study identifies known ROP risk factors, but the Apgar score at 5minutes as a risk factor for severe ROP requires further studies in order to be confirmed.

Telemedicine Coverage of Intensive Care Units: A Narrative Review.

Telemedicine coverage of intensive care units (ICUs) is an organizational innovation that has been touted as a means to improve access to and quality of critical care. The purpose of this narrative review is to discuss the different organizational models of ICU telemedicine and factors that have influenced its adoption, and to review the existing literature to consider whether it has lived up to its promise. We conclude by suggesting future directions to fill in some of the existing gaps in the evidence.

Telemedicine Coverage of Intensive Care Units: A Narrative Review.

Telemedicine coverage of intensive care units is an organizational innovation that has been touted as a means to improve access to and quality of critical care. The purpose of this narrative review is to discuss the different organizational models of intensive care unit telemedicine and factors that have influenced its adoption and to review the existing literature to consider whether it has lived up to its promise. We conclude by suggesting future directions to fill in some of the existing gaps in the literature.

A Systematic Review of Nurses' Perspectives Toward the Telemedicine Intensive Care Unit: A Basis for Supporting Its Future Implementation in China?

Aim: The purpose of this systematic review is to critique and summarize existing research on intensive care unit (ICU) nurses' perspectives toward the telemedicine intensive care unit (Tele-ICU). The intention of this study is to explore the evidence base to support the potential future implementation of Tele-ICU program in China. Methods: We searched for published articles pertaining to Tele-ICU system with a centralized monitoring model between January 2000 and July 2017 using Cochrane Library, Academic Search Premier, Cumulative Index to Nursing and Allied Health Literature, British Education Index, MEDLINE, MLA International Bibliography, and Web of Science. Studies were coded by methodology, participants, and findings. The textual narrative synthesis method was applied to synthesize the outcomes. Results: Findings were categorized as follows: perceptions of the Tele-ICU (including the role of Tele-ICU, benefits for nurses, patients, and management); attitudes of Tele-ICU (usefulness and challenges of Tele-ICU); level of satisfaction; factors affecting acceptance of Tele-ICU. Discussion: This review has synthesized significant factors influencing optimal usage of Tele-ICU from nurses' perspectives. Also, it might make a better case for findings to support Tele-ICU future implementation into Chinese tertiary hospitals.

When Will Telemedicine Appear in the ICU?

As our population ages and the demand for high-level intensive care unit (ICU) services increase, the ICU physician supply continues to lag. In addition, hospitals, physician groups, and patients are demanding rapid access for the highest level of expertise in the care of critically ill patients. Telemedicine in the ICU combined with remote patient monitoring has been increasingly touted as a model of care to increase efficiencies and quality of care. Telemedicine in the ICU provides the potential to connect critically ill patients to sophisticated specialty care on a 24/7 basis, even for those hospitalized in rural locations where access to timely specialty consultations are uncommon. Research on the use of telemedicine in the ICU has suggested improved outcomes, such as reductions in mortality, reductions in length of stay, and greater adherence to evidence-based guidelines. Although the clinical footprint of telemedicine in ICU has grown over the past 20 years, there has been a relative slowing of implementation. This review examines the clinical evidence supporting the use of telemedicine in the ICU and discusses the impact on clinical efficacy and costs of care. Additionally, we review the current hurdles to more rapid adoption, including the significant financial investment, different models of care affecting the return on investment, and the varied cultural attitudes that impact the success and acceptance of care models using telemedicine in the ICU.

Telemedicine/Virtual ICU: Where Are We and Where Are We Going?

Intensive care unit telemedicine (tele-ICU) is technology enabled care delivered from off-site locations that was developed to address the increasing complexity of patients and insufficient supply of intensivists. Although tele-ICU deployment is increasing, it continues to cover only a small proportion of ICU patients. This is primarily due to expense, with first-year costs exceeding $50,000 per bed. Meta-analyses of outcomes indicate survival benefits and quality improvements, albeit with significant heterogeneity. Depending on the context, a wide range of estimated incremental cost-effectiveness ratios reflects variable effects on cost and outcomes, such as mortality or length of stay. Tele-ICUs may fit within a hybrid model of care to complement high-intensity ICU staff coverage. However, more research is required to foster consensus and determine best practices. This review summarizes data on tele-ICU structure, operations, outcomes, and costs. Evidence was extracted from meta-analyses, with secondary data from Cleveland Clinic's tele-ICU experience.

Identifying Strategies for Effective Telemedicine Use in Intensive Care Units: The ConnECCT Study Protocol.

Telemedicine, the use of audiovisual technology to provide health care from a remote location, is increasingly used in intensive care units (ICUs). However, studies evaluating the impact of ICU telemedicine show mixed results, with some studies demonstrating improved patient outcomes, while others show limited benefit or even harm. Little is known about the mechanisms that influence variation in ICU telemedicine effectiveness, leaving providers without guidance on how to best use this potentially transformative technology. The Contributors to Effective Critical Care Telemedicine (ConnECCT) study aims to fill this knowledge gap by identifying the clinical and organizational factors associated with variation in ICU telemedicine effectiveness, as well as exploring the clinical contexts and provider perceptions of ICU telemedicine use and its impact on patient outcomes, using a range of qualitative methods. In this report, we describe the study protocol, data collection methods, and planned future analyses of the ConnECCT study. Over the course of 1 year, the study team visited purposefully sampled health systems across the United States that have adopted telemedicine. Data collection methods included direct observations, interviews, focus groups, and artifact collection. Data were collected at the ICUs that provide in-person critical care as well as at the supporting telemedicine units. Iterative thematic content analysis will be used to identify and define key constructs related to telemedicine effectiveness and describe the relationship between them. Ultimately, the study results will provide a framework for more effective implementation of ICU telemedicine, leading to improved clinical outcomes for critically ill patients.

Selected Use of Telemedicine in Intensive Care Units Based on Severity of Illness Improves Cost-Effectiveness.

Telemedicine in the intensive care unit (tele-ICU) is expected to address geographic health disparities through more efficient resource allocation. Our previous economic evaluation demonstrated tele-ICU to be cost-effective in most cases and cost saving in some cases, compared to conventional intensive care unit (ICU) care without adequate intensivist coverage. This study's objective is to examine how to optimize the cost-effectiveness of tele-ICU use by selecting highest risk (i.e., both highest mortality and highest cost) subpopulations. We also explore potential cost savings. We conducted simulation analyses among a hypothetical adult ICU patient cohort defined by the literature, distinguishing four types of hospitals: urban tertiary (primary analysis), urban community, rural tertiary, and rural community. The selected tele-ICU use was assumed to affect per-patient ICU cost and hospital mortality among highest risk subpopulations (10-100% of all ICU patients), defined by an established illness-severity measure. We found a U-shaped relationship between the economic efficiency and selected tele-ICU use among all 4 hospital types. Optimal cost-effectiveness was achieved when tele-ICU was applied to the 30-40% highest risk patients among all ICU patients (incremental cost-effectiveness ratio = $25,392 [2014 U.S. dollars] per extending a quality-adjusted life year) in urban tertiary hospitals (primary analysis). Our break-even analyses indicated that cost saving seems more feasible when reducing ICU medical care cost, rather than lowering the cost to operate telemedicine alone. A selected use of tele-ICU based on severity of illness is likely to improve tele-ICU cost-effectiveness. To achieve cost saving, tele-ICU must reduce more than just telemedicine-related cost.

Using electronic medical record notes to measure ICU telemedicine utilization.

Given the complexity of high-acuity health care, designing an effective clinical note template can be beneficial to both document patient care and clarify how telemedicine is used. We characterized documented interactions via a standardized note template between bedside intensive care unit (ICU) providers and teleintensivists in 2 Veterans Health Administration ICU telemedicine support centers. All ICUs linked to support centers and providing care from October 2012 through September 2014 were considered. Interactions were assessed based on initiation site, bedside initiator, contact type, and patient care change. Of 14 511 ICU admissions with teleintensivist access, teleintensivist interaction was documented in 21.6% (N = 3136). In particular, contacts were primarily initiated by bedside staff (74.4%), use increased over time, and of contacts resulting in changes in patient care, most were initiated by a bedside nurse (84.3%). Given this variation, future research necessitates inclusion of utilization in evaluation of Tele-ICU and patient outcomes.

Telemedizin: Chancen und Grenzen in der Intensivmedizin

Intensive care unit (ICU) telemedicine is one option to improve clinical relevant outcomes in terms of mortality, length of stay and morbidity. Telemedicine combines the advantage of locally available intensive medical care with the shared expertise of specialized centers by data and information exchange. The article describes the organizational and technical feasibility of different options, as well as the effects and limitations of ICU telemedicine.

Bedside Critical Care Staff Use of Intensive Care Unit Telemedicine: Comparisons by Intensive Care Unit Complexity.

Effects of Intensive Care Unit (ICU) telemedicine on patient and staff outcomes are mixed. Variation in utilization is potentially driving these differences. ICU telemedicine utilization is understudied, with existing research focusing on telemedicine staff. We assess ICU telemedicine utilization from the perspective of the end user-ICU staff-to better understand how telemedicine use is conceptualized and practiced at the bedside. We conducted a thematic content analysis of semistructured interviews with bedside ICU staff. Staff were interviewed at seven ICUs in six Veterans Health Administration facilities, representing varying ICU complexities and points in time (2 and 12 months postimplementation of ICU telemedicine). Fifty-eight bedside ICU staff described instances of telemedicine use, which were categorized into three types: Urgent ICU Patient Care, Clinical Decision-Making and Support, and General ICU Patient Care. The most commonly described use was General ICU Patient Care and the least common was Urgent ICU Patient Care. ICU staff from lower complexity ICUs had fewer descriptions of use compared to staff at higher complexity ICUs. At 12 months postimplementation, staff recounted more instances of all three utilization types. It is important to understand how telemedicine is being used within ICUs to evaluate its impact. The presence of three types of use, variability in use by ICU complexity, and change in use over time suggest the need for comprehensive measures of utilization to evaluate effectiveness. ICU telemedicine needs to develop an agreed upon typology for documenting ICU telemedicine utilization and incorporate these measures into models of its effect on clinical outcomes.

Impact of a telemedicine eICU cart on sepsis management in a community hospital emergency department

Introduction Intensivist involvement for patients with sepsis is associated with decreased complications and mortality, and lower hospital resource utilization, but few studies have evaluated outcomes for patients exposed to electronic intensive care unit (eICU) telemedicine sepsis management in the emergency department (ED). In this study, we assess whether eICU cart exposure in the ED improved compliance with components of the 2010 Surviving Sepsis Campaign bundles, length of stay (LOS), disposition and hospital costs. Methods An institutional review board-approved, retrospective cohort study was completed on patients with confirmed sepsis who presented to our ED from July 2010 through February 2013. Results Of 711 patient ED encounters, 314 cases met criteria for analysis (95 exposed and 219 non-exposed). Patient cohorts had similar demographics and comorbid International Classification of Diseases, Ninth Edition (ICD-9) diagnoses. The exposed cohort received antibiotics more quickly (122.3 minutes ±83.3 versus 163.4 minutes ±204.4, p = 0.043) and were more likely to have lactic acid levels drawn within six hours (98.9% vs. 90%, p = 0.019). The exposed cohort had a shortened ED LOS (in days) 0.08 ± 0.28 versus 0.16 ± 0.37, p = 0.036. Hospital LOS, disposition and death were similar in both cohorts. Total hospital costs for the exposed cohort were lower and less variable (US$19,713 ± 16,550 vs. US$24,364 ± 25068), but this was not significant (p = 0.274). Discussion Our findings suggest that in individuals with confirmed sepsis, ED exposure to a telemedicine-based eICU cart impacted adherence to aspects of the Surviving Sepsis Campaign recommended bundle, but did not impact overall survival and medical costs.

Telemedicine coverage for post-operative ICU patients

Introduction There is an increased demand for intensive care unit (ICU) beds. We sought to determine if we could create a safe surge capacity model to increase ICU capacity by treating ICU patients in the post-anaesthesia care unit (PACU) utilizing a collaborative model between an ICU service and a telemedicine service during peak ICU bed demand. Methods We evaluated patients managed by the surgical critical care service in the surgical intensive care unit (SICU) compared to patients managed in the virtual intensive care unit (VICU) located within the PACU. A retrospective review of all patients seen by the surgical critical care service from January 1st 2008 to July 31st 2011 was conducted at an urban, academic, tertiary centre and level 1 trauma centre. Results Compared to the SICU group (n = 6652), patients in the VICU group (n = 1037) were slightly older (median age 60 (IQR 47–69) versus 58 (IQR 44–70) years, p = 0.002) and had lower acute physiology and chronic health evaluation (APACHE) II scores (median 10 (IQR 7–14) versus 15 (IQR 11–21), p < 0.001). The average amount of time patients spent in the VICU was 13.7 + /–9.6 hours. In the VICU group, 750 (72%) of patients were able to be transferred directly to the floor; 287 (28%) required subsequent admission to the surgical intensive care unit. All patients in the VICU group were alive upon transfer out of the PACU while mortality in the surgical intensive unit cohort was 5.5%. Discussion A collaborative care model between a surgical critical care service and a telemedicine ICU service may safely provide surge capacity during peak periods of ICU bed demand. The specific patient populations for which this approach is most appropriate merits further investigation.

ICU Telemedicine and Critical Care Mortality

Intensive care unit (ICU) telemedicine is an increasingly common strategy for improving the outcome of critical care, but its overall impact is uncertain. To determine the effectiveness of ICU telemedicine in a national sample of hospitals and quantify variation in effectiveness across hospitals. We performed a multicenter retrospective case-control study using 2001-2010 Medicare claims data linked to a national survey identifying US hospitals adopting ICU telemedicine. We matched each adopting hospital (cases) to up to 3 nonadopting hospitals (controls) based on size, case-mix, and geographic proximity during the year of adoption. Using ICU admissions from 2 years before and after the adoption date, we compared outcomes between case and control hospitals using a difference-in-differences approach. A total of 132 adopting case hospitals were matched to 389 similar nonadopting control hospitals. The preadoption and postadoption unadjusted 90-day mortality was similar in both case hospitals (24.0% vs. 24.3%, P=0.07) and control hospitals (23.5% vs. 23.7%, P<0.01). In the difference-in-differences analysis, ICU telemedicine adoption was associated with a small relative reduction in 90-day mortality (ratio of odds ratios=0.96; 95% CI, 0.95-0.98; P<0.001). However, there was wide variation in the ICU telemedicine effect across individual hospitals (median ratio of odds ratios=1.01; interquartile range, 0.85-1.12; range, 0.45-2.54). Only 16 case hospitals (12.2%) experienced statistically significant mortality reductions postadoption. Hospitals with a significant mortality reduction were more likely to have large annual admission volumes (P<0.001) and be located in urban areas (P=0.04) compared with other hospitals. Although ICU telemedicine adoption resulted in a small relative overall mortality reduction, there was heterogeneity in effect across adopting hospitals, with large-volume urban hospitals experiencing the greatest mortality reductions.

Reliability of Circulatory and Neurologic Examination by Telemedicine in a Pediatric Intensive Care Unit

To test the hypothesis that telemedicine can reliably be used for many aspects of circulatory and neurologic examinations of children admitted to a pediatric intensive care unit (PICU). A prospective, randomized study in a 14-bed PICU in a tertiary care, academic-affiliated institution. Eligible patients were >2 months or <19 years of age, not involved in a concurrent study, had parents/guardian able to sign an informed consent form, were not at end-of-life, and had an attending who not only deemed them medically stable, but also felt that the study would not interrupt their care. Other than the Principal Investigator, 6 pediatric intensivists and 7 pediatric critical care fellows were eligible study providers. Two physician providers were randomly assigned to perform circulatory and neurologic examinations according to the American Heart Association/Pediatric Advanced Life Support guidelines in-person and via telemedicine. Findings were recorded on a standardized data collection form and compared. One hundred ten data collection forms were completed. For many aspects of the circulatory and neurologic examinations, outcomes showed substantial to perfect agreement between the in-person and telemedical care providers (kappa = 0.64-1.00). However, assessments of muscle tone had a kappa = 0.23, with a kappa = 0.37 for skin color. Telemedicine can reliably identify normal and abnormal findings of many aspects of circulatory and neurologic examinations in PICU patients. This finding opens the door to further studies on the use of telemedicine across other disciplines.

Rethinking cancer clinical trials for the future.

Future OncologyVol. 10, No. 9 OpinionRethinking cancer clinical trials for the futureMatthew D GalskyMatthew D GalskySearch for more papers by this authorPublished Online:22 Aug 2014https://doi.org/10.2217/fon.14.95AboutSectionsView ArticleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInReddit View articleKeywords: accrualcancerclinical trialstelemedicine References1 Murthy VH, Krumholz HM, Gross CP. Participation in cancer clinical trials: race-, sex-, and age-based disparities. JAMA 291(22), 2720–2726 (2004).Crossref, Medline, CAS, Google Scholar2 Stensland KD, McBride R, Wisnivesky JP et al. Premature termination of genitourinary cancer clinical trials. J. Clin. Oncol. 32(Suppl. 4), Abstract 288 (2014).Crossref, Google Scholar3 Kasenda B, von Elm E, You J et al. Prevalence, characteristics, and publication of discontinued randomized trials. JAMA 311(10), 1045–1051 (2014).Crossref, Medline, CAS, Google Scholar4 English R, Lebovitz Y, Griffin R. Transforming Clinical Research in the United States: Challenges and Opportunities: Workshop Summary. The National Academies Press, Washington DC, USA (2010).Google Scholar5 Meropol NJ, Buzaglo JS, Millard J et al. Barriers to clinical trial participation as perceived by oncologists and patients. J. Natl Compr. Canc. Netw. 5(8), 655–664 (2007).Crossref, Medline, Google Scholar6 Kaplan CP, Nápoles AM, Dohan D et al. Clinical trial discussion, referral, and recruitment: physician, patient, and system factors. Cancer Causes Control 24(5), 979–988 (2013).Crossref, Medline, Google Scholar7 Jacoby I. Geographic distribution of physician manpower: the GMENAC (Graduate Medical Education National Advisory Committee) legacy. J. Rural Heal. 7(Suppl. 4), 427–436 (1991).Medline, CAS, Google Scholar8 Ricketts TC. Geographic Methods for Health Services Research: a Focus on the Rural–Urban Continuum. University Press of America, Lanham, MD, USA (1994).Google Scholar9 Galsky MD, Latif A, Stensland KD et al. Distribution and geographic accessibility of prostate cancer clinical trials in the United States. J. Clin. Oncol. 32(Suppl. 4), Abstract 59 (2014).Crossref, Google Scholar10 Breslow MJ. Remote ICU care programs: current status. J. Crit. Care. 22(1), 66–76 (2007).Crossref, Medline, Google Scholar11 PatientsLikeMe. www.patientslikeme.com Google Scholar12 Young LB, Chan PS, Lu X, Nallamothu BK, Sasson C, Cram PM. Impact of telemedicine intensive care unit coverage on patient outcomes: a systematic review and meta-analysis. Arch. Intern. Med. 171(6), 498–506 (2011).Crossref, Medline, Google Scholar13 Breslow MJ, Rosenfeld BA, Doerfler M et al. Effect of a multiple-site intensive care unit telemedicine progr Am. on clinical and economic outcomes: an alternative paradigm for intensivist staffing. Crit. Care Med. 32(1), 31–38 (2004).Crossref, Medline, Google Scholar14 Christensen CM. The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Harper Business, NY, USA (2000).Google Scholar15 Wicks P, Vaughan TE, Massagli MP, Heywood J. Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm. Nat. Biotechnol. 29(5), 411–414 (2011).Crossref, Medline, CAS, Google ScholarFiguresReferencesRelatedDetails Vol. 10, No. 9 eToC Sign up Follow us on social media for the latest updates Metrics Downloaded 79 times History Published online 22 August 2014 Published in print July 2014 Information© Future Medicine LtdKeywordsaccrualcancerclinical trialstelemedicine Financial & competing interests disclosureMD Galsky is supported by a Prostate Cancer Foundation Young Investigator Award. MD Galsky has served as a consultant for Astellas, Dendreon, Jannsen, GlaxoSmithKline and BioMotiv. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.PDF download

Impact of an intensive care unit telemedicine program on patient outcomes in an integrated health care system.

Intensive care unit (ICU) telemedicine (TM) programs have been promoted as improving access to intensive care specialists and ultimately improving patient outcomes, but data on effectiveness are limited and conflicting. To examine the impact of ICU TM on mortality rates and length of stay (LOS) in an integrated health care system. Observational pre-post study of patients treated in 8 "intervention" ICUs (7 hospitals within the US Department of Veterans Affairs health care system) during 2011-2012 that implemented TM monitoring during the post-TM period as well as patients treated in concurrent control ICUs that did not implement an ICU TM program. Implementation of ICU TM monitoring. Unadjusted and risk-adjusted ICU, in-hospital, and 30-day mortality rates and ICU and hospital LOS for patients who did or did not receive treatment in ICUs equipped with TM monitoring. Our study included 3355 patients treated in our intervention ICUs (1708 in the pre-TM period and 1647 in the post-TM period) and 3584 treated in the control ICUs during the same period. Patient demographics and comorbid illnesses were similar in the intervention and control ICUs during the pre-TM and post-TM periods; however, predicted ICU mortality rates were modestly lower for admissions to the intervention ICUs compared with control ICUs in both the pre-TM (3.0% vs 3.6%; P = .02) and post-TM (2.8% vs 3.5%; P < .001) periods. Implementation of ICU TM was not associated with a significant decline in ICU, in-hospital, or 30-day mortality rates or LOS in unadjusted or adjusted analyses. For example, unadjusted ICU mortality in the pre-TM vs post-TM periods were 2.9% vs 2.8% (P = .89) for the intervention ICUs and 4.0% vs 3.4% (P = .31) for the control ICUs. Unadjusted 30-day mortality during the pre-TM vs post-TM periods were 7.7% vs 7.8% (P = .91) for the intervention ICUs and 12.0% vs 10.2% (P = .08) for the control ICUs. Evaluation of interaction terms comparing the magnitude of mortality rate change during the pre-TM and post-TM periods in the intervention and control ICUs failed to demonstrate a significant reduction in mortality rates or LOS. We found no evidence that the implementation of ICU TM significantly reduced mortality rates or LOS.

Staff acceptance of a telemedicine intensive care unit program: A qualitative study

PurposeWe conducted an evaluation to identify factors related to intensive care unit (ICU) staff acceptance of a telemedicine ICU (Tele-ICU) program in preimplementation and postimplementation phases. MethodsIndividual or group semistructured interviews and site observations were conducted with staff from the Veterans Affairs Midwest Health Care Network Tele-ICU and affiliated ICUs. A qualitative content analysis of preimplementation and postimplementation transcripts and field notes was undertaken to identify themes positively and negatively influencing Tele-ICU acceptance. ResultsTelemedicine ICU training, Tele-ICU understanding, perceived need, and organizational factors emerged as influencing acceptance of the Tele-ICU before implementation. After implementation, Tele-ICU understanding, impact on work systems, perceived usefulness, and relationships were factors influencing acceptance and utilization. Barriers to implementation included confusion about how to use the Tele-ICU, disruptions to communication and workflows, unmet expectations, and discomfort with being monitored. Facilitators included positive experiences, discovery of new benefits, and recognition of Tele-ICU staff as complementing bedside care. ConclusionsTelemedicine ICU implementation is complex. Time and resources should be allocated for local coordination, continuous needs assessment for Tele-ICU support, staff training, developing interpersonal relationships, and systems design and evaluation. Such efforts are likely to be rewarded with more rapid staff acceptance of this new technology.

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Introduction: Demand for intensive care unit (ICU) resources is predicted to expand as the population ages and life support technologies improve. Intensivists frequently must arbitrate ICU beds to the most acutely ill patients leaving little room for those less sick. Hypothesis: We hypothesized collaborative care between a Surgical Critical Care Service (SCCS) and a Telemedicine ICU Service (TIS) could provide virtual ICU (VICU) coverage for postoperative patients managed in Post-Anesthesia Care Unit (PACU) beds during times of peak ICU bed demand. Methods: We performed a retrospective review of all patients seen by the SCCS from 01/08-07/11. Patients were divided into two groups: those admitted directly to the SICU vs. those admitted to a VICU bed. The VICU group was managed jointly by a SCCS and a TIS, utilizing four PACU beds at a location remote from the SICU for ‘surge capacity’. VICU patients were managed by a SCCS nurse practitioner and an in-house intensivist from 07:00-18:59 and by a TIS from 19:00-06:59. Patients with lower-intensity postoperative needs were preferentially boarded in VICU. Patients were boarded in VICU beds until SICU beds became available or until patients’ critical care needs resolved. Groups were compared using Kruskal-Wallis or Chi squared as appropriate. Statistical significance was set at p=0.05. Results: Compared to those in the SICU group (n=6932), patients in the VICU group (n=1046) were slightly older (median age 60 (IQR47-69) vs. 58 (IQR 44-70) years, p = 0.01) but had lower APACHE II scores (median 10 (IQR7-14) vs. 15 (IQR 11-21), p <0.001). The average time VICU patients spent in PACU was 13.7 +/- 9.6 hours. In the VICU group, 761 (72.5%) of patients were able to be transferred directly to the ward from the PACU; 288 (27.5%) required subsequent SICU admission. All patients in the VICU group were alive upon ICU discharge or transfer to the floor; mortality in the SICU cohort was 5.3%. Conclusions: A collaborative care model between SCCS and TIS may safely provide surge capacity during peak periods of ICU bed demand. The specific patient populations for which this approach is most appropriate merits further investigation.