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Original Research |

A National ICU Telemedicine SurveyICU Telemedicine Survey: Validation and Results FREE TO VIEW

Craig M. Lilly, MD, FCCP; Kimberly A. Fisher, MD; Michael Ries, MD , MBA, FCCP; Stephen M. Pastores, MD, FCCP; Jeffery Vender, MD, FCCP; Jennifer A. Pitts, MA; C. William Hanson, III, MD
Author and Funding Information

From the Department of Medicine (Drs Lilly and Fisher), the Department of Anesthesiology (Dr Lilly), the Department of Surgery (Dr Lilly), the Clinical and Population Health Research Program (Dr Lilly), and the Graduate School of Biomedical Sciences (Drs Lilly and Fisher), University of Massachusetts Medical School, Worcester, MA; Advocate HealthCare, Rush University Medical Center (Dr Ries), Chicago, IL; the NorthShore University Health System (Drs Ries and Vender), Chicago, IL; the Memorial Sloan-Kettering Cancer Center (Dr Pastores), New York, NY; the Feinberg School of Medicine (Dr Vender), Northwestern University, Evanston, IL; American College of Chest Physicians (Ms Pitts), Northbrook, IL; and the Hospital of the University of Pennsylvania (Dr Hanson), Philadelphia, PA.

Correspondence to: Craig M. Lilly, MD, FCCP, University of Massachusetts Medical School, UMass Memorial Medical Center, 281 Lincoln St, Worcester, MA 01605; e-mail: craig.lilly@umassmed.edu

Financial/nonfinancial disclosures: The authors have reported to CHEST the following conflicts of interest: Ms Pitts is an employee of the American College of Chest Physicians. Drs Lilly, Fisher, Ries, Pastores, Vender, and Hanson have reported that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Funding/Support: The authors have reported to CHEST that no funding was received for this study.


Funding/Support: The authors have reported to CHEST that no funding was received for this study.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2012;142(1):40-47. doi:10.1378/chest.12-0310
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Published online

Background:  A recent ICU telemedicine research consensus conference identified the need for reliable methods of measuring structural features and processes of critical care delivery in the domains of organizational context and characteristics of ICU teams, ICUs, hospitals, and of the communities supported by an ICU.

Methods:  The American College of Chest Physicians Critical Care Institute developed and conducted a survey of ICU telemedicine practices. A 32-item survey was delivered electronically to leaders of 311 ICUs, and 11 domains were identified using principal components analysis. Survey reliability was judged by intraclass correlation among raters, and validity was measured for items for which independent assessment was available.

Results:  Complete survey information was obtained for 170 of 311 ICUs sent invitations. Analysis of a subset of surveys from 45 ICUs with complete data from more than one rater indicated that the survey reliability was in the excellent to nearly perfect range. Coefficients for measures of external validation ranged from 0.63 to 1.0. Analyses of the survey revealed substantial variation in the practice of ICU telemedicine, including ICU telemedicine center staffing patterns; qualifications of providers; case sign-out, ICU staffing models, leadership, and governance; intensivist review for new patients; adherence to best practices; use of quality and safety information; and ICU physician sign out for their patients.

Conclusions:  The American College of Chest Physicians ICU telemedicine survey is a reliable tool for measuring variation among ICUs with regard to staffing, structure, processes of care, and ICU telemedicine practices.

Figures in this Article

Advances in health information technology, telecommunications, and the evolution of the patient safety movement have contributed to the growth of the ICU telemedicine movement.1 Comprehensive ICU telemedicine programs that provide continuous patient monitoring by an offsite team of critical care professionals have the ability to recognize physiologic instability and to render care that is timely and triggered by patient factors. The number of ICU telemedicine programs in the United States has grown rapidly1; > 8% of nonfederal United States hospital ICU beds are currently supported by a comprehensive ICU telemedicine program.2,3 ICU telemedicine program implementations now include installations outside of the United States. Despite this wider adoption of ICU telemedicine, relatively little has been reported about its practice and variation among programs with regard to its application and acceptance. Studies of the practice of ICU telemedicine are limited in part by the lack of reliable and practical methods for measurement of ICU and ICU telemedicine program structural and process elements.

Among others, the leaders of the American College of Chest Physicians (ACCP) recognized the need for reliable information regarding ICU telemedicine practice and convened an expert panel to develop an ICU telemedicine survey instrument. The need for validated tools to measure ICU structure and process characteristics was clearly articulated in a published report from an Agency for Health Research and Quality-sponsored consensus conference.4 This consensus statement identified domains of organizational context and characteristics of ICU patients, ICUs, hospitals, and the communities that are supported by an ICU telemedicine program for which reliable metrics are needed. We report the validation and results of the ACCP ICU telemedicine survey that included items in each of the domains identified in the conference consensus statement.

Survey Development

A panel of expert clinicians with critical care or ICU telemedicine experience was identified by the American College of Chest Physicians Critical Care Institute. These individuals formed a workgroup that met and drafted an instrument designed to gather information about ICU telemedicine practice and structural and process elements that may have been altered by the introduction of an ICU telemedicine program. The initial draft was reviewed, edited, and formatted by the Aeffect group, a research and consulting firm with expertise in the development of social science survey instruments that also provided advice about the plan for conducting the survey. The formatted hardcopy and electronic versions of the instrument as well as the plan for conducting and validating the survey were reviewed by the staff of the Agency for Healthcare Research and Quality, made possible by a generous gift of their time and talent. After final review and approval by the committee, the hardcopy survey was translated into electronic form using QuestionPro software (QuestionPro). After successful testing, it was electronically delivered to respondents along with a letter encouraging participation from the then-current president of the ACCP, James Mathers, MD. The study was conducted with the approval of the University of Massachusetts Human Subjects Committee, which deemed it exempt from the requirement for informed consent.

Administration of the Survey

ICU telemedicine programs that used remotely located continuous monitoring technologies to manage patients using audio and video links and include the capacity to record provider orders into the patient’s medical record were sought using multiple methods. Electronic searches were conducted on June 1, 2009, using the PubMed and Google search engines with the search terms “ICU telemedicine,” “telemedicine,” “electronic ICU,” and “tele-ICU.” Requests were made to major manufacturers of electronic medical records and ICU telemedicine software to identify ICUs with active telemedicine programs. Programs were also identified using social media sites and sought at HIMSs Health IT Conference, Society of Critical Care Congress, CHEST 2008, and the 2009 meeting of the American Thoracic Society. Individual ICUs were contacted and asked to provide electronic contact information for their nurse manager, medical director, and the hospital administrator responsible for that unit. The survey was electronically delivered to 558 unique e-mail addresses on August 11, 2009, with administrative responsibility for 311 distinct ICUs. A second electronic invitation was sent to those with incomplete or missing responses on September 9, 2009, and at least one individual for each ICU that had performed a study and had not responded to either communication was contacted and asked to participate in the survey. The survey was completed on November 1, 2009. Respondents who provided contact information were reached by telephone to complete items for a small number of surveys that had no valid response for one or more items from any of the respondents for that ICU. Information about participating and nonparticipating ICUs, including geographic location, ICU type, numbers of licensed beds, and hospital and ICU teaching status, was collected by analyzing year 2009 data in publicly available health-care and quality databases.

Data Analyses

Responses for each item were recorded for each respondent. When more than one response was available for an item, the most frequently reported response was recorded into a single record for each ICU, and equally prevalent discrepant responses were resolved by having another observer from the ICU record a response. Comparisons of levels of response between groups were made using the χ2 test. Intraclass correlation coefficients were calculated to assess the reliability among raters,5 and interrater agreement was assessed using the free-marginal κ score based on the responses to the original survey items.

Factor Analyses

Responses from 32 noniterative items from 170 ICUs that provided complete survey information were subjected to a Principal Components Analysis with varimax rotation and Kaiser Normalization (SPSS version 20; SPSS Inc). Factor scores were derived by the method of Anderson-Rubin.

Rates of Survey Completion

We identified 311 unique ICUs that were supported by a comprehensive telemedicine program. These ICUs were located in 186 hospitals of 38 health-care systems. One hundred seventy of the ICUs returned at least one survey with complete data (ICU response rate, 55%). Two hundred seventy of 558 (48%) of the individuals who were sent electronic invitations responded to a request (Fig 1) .Individual respondents included nurse managers (50%), medical directors (40%), and administrators (10%). Two or more independent complete responses were received for 45 ICUs.

The geographic distribution of ICUs for which complete survey data were available was similar to that of those that did not participate in the survey for most regions; however, participating sites in the New England, Mid Atlantic, and South Central regions were less frequent, and those in the Pacific regions were more frequent compared with nonparticipating sites. The distributions of the types of ICU that participated were similar and not statistically different from those of ICUs that did not participate (P = .6). ICUs that did not participate in the survey less frequently supported teaching programs (residents worked in 26.9% of nonresponding and 45.3% of responding ICUs; P < .001) and were smaller than ICUs for which complete survey information was obtained, having a median size of 12 beds (interquartile range 8-18; P < .001) compared with 16 beds (interquartile range, 12-24) for those that participated.

Validation Measures

Intraclass correlation coefficients were calculated for sites with responses from two or more independent observers. The degree of concordance was substantial, with individual items having correlation coefficients that ranged from 0.567 to 1.0; 35 of 47 items had coefficients in the almost perfect agreement range, eight items had coefficients in the strong agreement range, and four items had coefficient values in the moderate agreement range. The survey items are presented in e-Table 1, and the intraclass correlation coefficients and the survey items are presented in e-Table 2.

Data for items that were obtained by methods independent of the survey were compared with survey responses. The free marginal κ score for hospital teaching status was 0.63, indicating good agreement between reported and independently measured values. Intraclass correlation coefficients for the number of licensed hospital beds was 0.76, was 0.83 for the date of implementation of the ICU telemedicine program, and was fully concordant for the number of ICU beds. Aggregated estimates of adherence to critical care best practices were similar to those measured in a 2008 sample of ICUs with telemedicine programs.2

ICU Characteristics

The telemedicine programs participating in this survey included ICUs that were dispersed with regard to geographic location, served communities with populations that ranged from small to large in size, in settings that ranged from rural to urban, and included ICUs located in critical access, community, and referral hospitals, as well as academic medical centers (Table 1). Participating ICUs were located in hospitals licensed for 25 to 1,030 beds and were diverse with respect to the participation of residents or students in the care of their critically ill patients. Nearly one-half of the participating ICUs had at least some participation of trainees in the care of their patients.

Table Graphic Jump Location
Table 1 —Characteristics of ICUs and Hospitals With Comprehensive ICU Telemedicine Programs

Data given as No. (%).

a 

US census bureau designated regions (regions 1 and 2 and 6 and 7 were combined).

b 

Includes combined ICUs.

Characteristics of the ICU Telemedicine Program

The ICU telemedicine programs reported in this survey began operation between June 2000 and March 2009. The number of ICUs that implemented ICU telemedicine programs as a function of calendar year is presented in Figure 2 and was largest in 2006. Among ICUs that provide ICU telemedicine services, nearly all of the beds in these units are equipped to provide ICU telemedicine services (3,020 of 3,211, or 94%). Weekday staffing of the ICU telemedicine center was composed of one intensivist (median, 1; range, 1-3) and three nurses (median, 3; range 1-12) and tended to increase with the number of beds being supported by the ICU telemedicine program (Table 2). On average, ICU telemedicine centers were staffed for 16.5 h (median, 16 h; range 10-24 h) during a weekday. There was a wide range of bedside personnel available to respond to off-hours medical emergencies, and a substantial number of ICUs (28.2%) reporting that no providers were available off-hours in the ICU. Among centers with 24-h telemedicine coverage, 32% reported having a structured sign-out format between outgoing and oncoming ICU telemedicine center staff.

Figure Jump LinkFigure 2. ICU telemedicine program implementation date by year.Grahic Jump Location
Table Graphic Jump Location
Table 2 —Characteristics of the ICU Telemedicine Program

Data given as No. (%) unless otherwise indicated. IS = information systems.

a 

Affiliate practitioners includes nurse practitioners and physician assistants.

b 

Percent of 170 ICUs marking the response along with others that apply.

Integration of ICU Telemedicine and Bedside Critical Care Staff

Analyses of the proportion of ICU telemedicine program providers that also worked at the bedside in the ICUs supported by the ICU telemedicine program detected variation in practice. More than 10% of programs reported that their staff did not work in the ICUs that were supported by the ICU telemedicine program. These analyses also revealed variation with regard to case handoff and after-hours coverage; less than one-half of bedside providers signed their services in or out when leaving or coming to the ICU. An integrated approach to documentation was uncommon; less than one-half of the ICUs used the same form of documentation in the ICU telemedicine center and at the bedside, and less than one-quarter had all disciplines using the same system (Table 3).

Table Graphic Jump Location
Table 3 —Integration of ICU Telemedicine and Bedside Clinicians
Critical Care Structure and Processes of Care

Survey analyses detected substantial heterogeneity with regard to structural and process elements among the ICUs (Table 4). Most ICUs did not use a “closed” physician staffing model, and only 32% used a high-intensity staffing model that required intensivist consultation or mandated that the intensivist serve as the attending physician of record. There was also significant variability with regard to the role of the ICU medical director; full-time directors were infrequent, and despite regulatory imperatives, nearly 9% of units were not able to fill this position at the time of the survey. Nearly all of the ICUs surveyed reported effective ICU governance, with 87% of ICUs reporting moderately or highly effective committees that reviewed performance data at least quarterly. Heterogeneity with regard to intensivist review for new cases was also reported; less than one-half of programs reviewed > 75% of cases within 1 h of ICU admission. There was also substantial variability with regard to adherence to a set of well-established ICU best practices,2 for which the ICU leadership received quarterly reporting, and with regard to the frequency of interdisciplinary rounds (Table 4).

Table Graphic Jump Location
Table 4 —ICU Staffing, Structure, and Processes of ICU Telemedicine Programs
ICU Telemedicine Survey Domains

We identified 11 independent domains that explained 67.3% of the total variance among the responses to the 32 survey items. These domains were assigned names based on the thematic relations among the individual survey items with dominant factor scores. The survey items are grouped into three sections based on Donobedian constructs3: (1) characteristics of the community, hospital, and ICU; (2) integration and teamwork; and (3) program structure and processes of care. The name of each domain is preceded by the survey section name of the dominant survey items from which it was derived. The survey domains are presented in descending order of the fraction of the total variance that each explained: (1) Characteristics: demographics. (2) Teamwork and integration: documentation. (3) Structure: ICU telemedicine center staff size and hours of operation. (4) Structure: physician leadership. (5) Teamwork and integration: sign-in and sign-out. (6) Teamwork and integration: staffing model (critical care certification and staff that works both at the bedside and in the ICU telemedicine center). (7) Processes of care: alert response times. (8) Teamwork and integration: best practices, reporting, and performance review. (9) Structure: ICU type and information system support. (10) Structure: ICU telemedicine experience and leadership. (11) Characteristics: ICU bed number. Factor scores for each of these domains were derived that are independent of one another and have a mean of 0 and an SD of 1.

The primary aim of this effort is to make available a validated instrument to measure elements in the domains of the patient, the ICU, the hospital, the community, and the organizational context in which ICU telemedicine programs operate. A secondary aim was to identify variance in the practice of ICU telemedicine. The overarching goal was to make a useful tool for measuring the structural features, processes of care, and outcomes of alternative ICU telemedicine care delivery models that will be useful to researchers.4 The ICU telemedicine survey instrument that was developed by the American College of Chest Physicians Critical Care Institute and refined with the help of experts in measures of health safety and quality was found to be highly reliable. Measures that were tested for external validity performed well. More than one-quarter of the ICUs had complete data from more than one independent observer, and 83% of the items had intraclass correlation coefficients in the strong or almost perfect range of agreement (e-Table 2). The response rate to the electronic invitation for the survey of 55% indicates that this is a practical tool that can be applied effectively to busy bedside ICU medical directors and nurse managers. The high reliability of the instrument and acceptable levels of the return of completed surveys provides important context for interpreting its findings.

The geographic distribution of the ICUs included in the survey sample is similar to that reported for 2008; both the American Hospital Association survey6 and a nationwide patient safety culture survey available from the Agency for Healthcare Research and Quality reported geographic distributions of ICUs that are similar to that of this survey.7 The proportion of hospitals with 301 to 750 licensed beds that have implemented an ICU telemedicine program was larger and the proportion of hospitals having < 300 beds was smaller than that reported by the American Hospital Association for 2008.6 This may reflect a greater ability of midsized than small hospitals to invest in patient safety programs.

One key theme of the survey analyses is the considerable variability with regard to ICU-telemedicine practices. Differences in specific aspects of ICU telemedicine program implementation, including staffing models, technical support, and integration with bedside ICU providers, have been cited as potential explanations1,47 for the divergent findings of the impact of ICU telemedicine programs on outcomes.813 Making this survey instrument available is important because it enables research that seeks to define the optimal characteristics of ICU telemedicine program staffing, structure, and processes.14 The availability of reliable and practical measures of ICU process, structure, documentation, and governance are also important because they can be applied to ICUs that are not supported by telemedicine programs.

Analyses of the survey data also revealed variation among ICUs with regard to their staffing and governance models. Variation that was detected with regard to whether the physicians that are available in the ICU telemedicine support center also work at the bedside is important, because it has recently been identified as a key factor that determines whether bedside nurses will request ICU telemedicine services for their patients.15 Two-thirds of ICUs that are supported by ICU telemedicine programs do not employ a “high-intensity” physician staffing model that has been associated with improved patient outcomes.16 It is possible that implementation of an ICU telemedicine program may be one way to achieve some of the benefits of a high-intensity staffing model for ICUs that are not able to recruit enough intensivists because of their limited supply.17 The majority of ICUs using ICU telemedicine services reported effective ICU governance and regular performance data review, elements which have been associated with improved patient outcomes.18 The survey also reported significant gaps in physician leadership with nearly 10% of programs not having a medical director and < 10% of ICUs having a full-time medical director. The implementation of an ICU telemedicine program did not ensure timely intensivist case review, prompt responses to alerts and alarms for physiologic instability, high rates of adherence to critical care best practices, interdisciplinary rounds, or interactive hand-off communications. This is surprising, because perfecting these processes that are associated with improved patient outcomes1923 is one important impetus for implementing a comprehensive ICU telemedicine program. The inability of some ICU telemedicine programs to optimize basic processes of critical care delivery suggests that differences in how programs are implemented could affect their impact on patient outcomes.

This survey of ICU telemedicine practice has several important limitations that should be taken into account when interpreting its findings. Its focus on programs providing comprehensive services that allow activation with and without requests from bedside personnel limits its ability to provide information about programs that use systems that are available intermittently or technologies that are activated only after bedside physician request. The survey used indirect measures of shared responsibility for patient care, such as patient sign-out and shared documentation, and may be less sensitive than an approach that uses a direct measure of the degree of autonomy granted to ICU telemedicine center physicians by bedside providers. The survey may underrepresent ICUs from hospitals with small numbers of licensed beds. Its focus on structure and processes may not have included other important factors, such as the degree of executive support for the program. Finally, the instrument may have omitted some details or aspects of critical care that may prove important for studies with a more targeted focus.

We present the results of a validated instrument for assessing ICU structural and process of care elements in domains that were identified as important for ICU telemedicine research. Analyses of the survey data reveal variation among ICU telemedicine and bedside practices with regard to staffing, case sign-out, review of new cases, adherence to critical care best practices, and response times to alerts and alarms.

Author contributions: Dr Lilly had full access to the data and takes responsibility for its integrity and the accuracy of the analyses.

Dr Lilly: contributed to study concept and design; study supervision; acquisition, analysis, and interpretation of data; statistical analysis; drafting of the manuscript; and critical revision of the manuscript for important intellectual content.

Dr Fisher: contributed to study supervision, analysis and interpretation of data, statistical analysis, and critical revision of the manuscript for important intellectual content.

Dr Ries: contributed to study concept and design, analysis and interpretation of data, and critical revision of the manuscript for important intellectual content.

Dr Pastores: contributed to study concept and design, analysis and interpretation of data, and critical revision of the manuscript for important intellectual content.

Dr Vender: contributed to study concept and design, analysis and interpretation of data, and critical revision of the manuscript for important intellectual content.

Ms Pitts: contributed to study supervision; acquisition of data; critical revision of the manuscript for important intellectual content; and administrative, technical, or material support.

Dr Hanson: contributed to study concept and design and critical revision of the manuscript for important intellectual content; and administrative, technical, or material support.

Financial/nonfinancial disclosures: The authors have reported to CHEST the following conflicts of interest: Ms Pitts is an employee of the American College of Chest Physicians. Drs Lilly, Fisher, Ries, Pastores, Vender, and Hanson have reported that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Other contributions: We thank Katherine Crosson, MPH; William B. Munier, MD; and Steven B. Cohen, PhD, of the Agency for Health Quality and Research for their thoughtful review of the survey instrument. We also thank Michael M. Bourisaw, BA, of the American College of Chest Physicians for coordinating the efforts of the survey development group.

Additional information: The e-Tables can be found in the “Supplemental Materials” area of the online article.

ACCP

American College of Chest Physicians

Lilly CM, Thomas EJ. Tele-ICU: experience to date. J Intensive Care Med. 2010;25(1):16-22. [PubMed] [CrossRef]
 
Lilly CM, Zuckerman IH, Badawi O, Riker RR. Benchmark data from more than 240,000 adults that reflect the current practice of critical care in the United States. Chest. 2011;140(5):1232-1242.
 
Donabedian A. The quality of care. How can it be assessed? JAMA. 1988;260(12):1743-1748.
 
Shahpori R, Kushniruk A, Hebert M, Zuege D. Tele-ICU-a Canadian review. Stud Health Technol Inform. 2011;164:420-424.
 
Young LB, Chan PS, Cram P. Staff acceptance of tele-ICU coverage: a systematic review. Chest. 2011;139(2):279-288.
 
Nguyen YL, Wunsch H, Angus DC. Critical care: the impact of organization and management on outcomes. Curr Opin Crit Care. 2010;16(5):487-492.
 
Ries M. Tele-ICU: a new paradigm in critical care. Int Anesthesiol Clin. 2009;47(1):153-170.
 
Lilly CM, Cody S, Zhao H, et al;; University of Massachusetts Memorial Critical Care Operations Group University of Massachusetts Memorial Critical Care Operations Group. Hospital mortality, length of stay, and preventable complications among critically ill patients before and after tele-ICU reengineering of critical care processes. JAMA. 2011;305(21):2175-2183.
 
Thomas E, Wueste L, Lucke JF, Weavind L, Patel B. Impact of a Tele-ICU on mortality, complications, and length of stay in six ICUs. Crit Care Med. 2007;35suppl 12:A8.
 
Morrison JL, Cai Q, Davis N, et al. Clinical and economic outcomes of the electronic ICU: results from two community hospitals. Crit Care Med. 2010;38(1):2-8.
 
Breslow MJ, Rosenfeld BA, Doerfler M, et al. Effect of a multiple-site ICU telemedicine program on clinical and economic outcomes: an alternative paradigm for intensivist staffing. Crit Care Med. 2004;32(1):31-38.
 
Rosenfeld BA, Dorman T, Breslow MJ, et al. Intensive care unit telemedicine: alternate paradigm for providing continuous intensivist care. Crit Care Med. 2000;28(12):3925-3931.
 
McCambridge M, Jones K, Paxton H, Baker K, Sussman EJ, Etchason J. Association of health information technology and teleintensivist coverage with decreased mortality and ventilator use in critically ill patients. Arch Intern Med. 2010;170(7):648-653.
 
Kahn JM, Hill NS, Lilly CM, et al. The research agenda in ICU telemedicine: a statement from the Critical Care Societies Collaborative. Chest. 2011;140(1):230-238.
 
Mullen-Fortino M, DiMartino J, Entrikin L, Mulliner S, Hanson CW, Kahn JM. Bedside nurses’ perceptions of ICU telemedicine. Am J Crit Care. 2012;21(1):24-31.
 
Pronovost PJ, Angus DC, Dorman T, Robinson KA, Dremsizov TT, Young TL. Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review. JAMA. 2002;288(17):2151-2162.
 
Angus DC, Shorr AF, White A, Dremsizov TT, Schmitz RJ, Kelley MA; Committee on Manpower for Pulmonary and Critical Care Societies (COMPACCS) Committee on Manpower for Pulmonary and Critical Care Societies (COMPACCS). Critical care delivery in the United States: distribution of services and compliance with Leapfrog recommendations. Crit Care Med. 2006;34(4):1016-1024.
 
Zimmerman JE, Alzola C, Von Rueden KT. The use of benchmarking to identify top performing critical care units: a preliminary assessment of their policies and practices. J Crit Care. 2003;18(2):76-86.
 
Kim MM, Barnato AE, Angus DC, Fleisher LA, Kahn JM. The effect of multidisciplinary care teams on ICU mortality. Arch Intern Med. 2010;170(4):369-376.
 
Engoren M. The effect of prompt physician visits on ICU mortality and cost. Crit Care Med. 2005;33(4):727-732.
 
Phillips J. Clinical alarms: complexity and common sense. Crit Care Nurs Clin North Am. 2006;18(2):145-156.
 
Sinuff T, Cook D, Giacomini M, Heyland D, Dodek P. Facilitating clinician adherence to guidelines in the ICU: A multicenter, qualitative study. Crit Care Med. 2007;35(9):2083-2089.
 
Catalano K. Hand-off communication does affect patient safety. Plast Surg Nurs. 2009;29(4):266-270.
 

Figures

Figure Jump LinkFigure 2. ICU telemedicine program implementation date by year.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 —Characteristics of ICUs and Hospitals With Comprehensive ICU Telemedicine Programs

Data given as No. (%).

a 

US census bureau designated regions (regions 1 and 2 and 6 and 7 were combined).

b 

Includes combined ICUs.

Table Graphic Jump Location
Table 2 —Characteristics of the ICU Telemedicine Program

Data given as No. (%) unless otherwise indicated. IS = information systems.

a 

Affiliate practitioners includes nurse practitioners and physician assistants.

b 

Percent of 170 ICUs marking the response along with others that apply.

Table Graphic Jump Location
Table 3 —Integration of ICU Telemedicine and Bedside Clinicians
Table Graphic Jump Location
Table 4 —ICU Staffing, Structure, and Processes of ICU Telemedicine Programs

References

Lilly CM, Thomas EJ. Tele-ICU: experience to date. J Intensive Care Med. 2010;25(1):16-22. [PubMed] [CrossRef]
 
Lilly CM, Zuckerman IH, Badawi O, Riker RR. Benchmark data from more than 240,000 adults that reflect the current practice of critical care in the United States. Chest. 2011;140(5):1232-1242.
 
Donabedian A. The quality of care. How can it be assessed? JAMA. 1988;260(12):1743-1748.
 
Shahpori R, Kushniruk A, Hebert M, Zuege D. Tele-ICU-a Canadian review. Stud Health Technol Inform. 2011;164:420-424.
 
Young LB, Chan PS, Cram P. Staff acceptance of tele-ICU coverage: a systematic review. Chest. 2011;139(2):279-288.
 
Nguyen YL, Wunsch H, Angus DC. Critical care: the impact of organization and management on outcomes. Curr Opin Crit Care. 2010;16(5):487-492.
 
Ries M. Tele-ICU: a new paradigm in critical care. Int Anesthesiol Clin. 2009;47(1):153-170.
 
Lilly CM, Cody S, Zhao H, et al;; University of Massachusetts Memorial Critical Care Operations Group University of Massachusetts Memorial Critical Care Operations Group. Hospital mortality, length of stay, and preventable complications among critically ill patients before and after tele-ICU reengineering of critical care processes. JAMA. 2011;305(21):2175-2183.
 
Thomas E, Wueste L, Lucke JF, Weavind L, Patel B. Impact of a Tele-ICU on mortality, complications, and length of stay in six ICUs. Crit Care Med. 2007;35suppl 12:A8.
 
Morrison JL, Cai Q, Davis N, et al. Clinical and economic outcomes of the electronic ICU: results from two community hospitals. Crit Care Med. 2010;38(1):2-8.
 
Breslow MJ, Rosenfeld BA, Doerfler M, et al. Effect of a multiple-site ICU telemedicine program on clinical and economic outcomes: an alternative paradigm for intensivist staffing. Crit Care Med. 2004;32(1):31-38.
 
Rosenfeld BA, Dorman T, Breslow MJ, et al. Intensive care unit telemedicine: alternate paradigm for providing continuous intensivist care. Crit Care Med. 2000;28(12):3925-3931.
 
McCambridge M, Jones K, Paxton H, Baker K, Sussman EJ, Etchason J. Association of health information technology and teleintensivist coverage with decreased mortality and ventilator use in critically ill patients. Arch Intern Med. 2010;170(7):648-653.
 
Kahn JM, Hill NS, Lilly CM, et al. The research agenda in ICU telemedicine: a statement from the Critical Care Societies Collaborative. Chest. 2011;140(1):230-238.
 
Mullen-Fortino M, DiMartino J, Entrikin L, Mulliner S, Hanson CW, Kahn JM. Bedside nurses’ perceptions of ICU telemedicine. Am J Crit Care. 2012;21(1):24-31.
 
Pronovost PJ, Angus DC, Dorman T, Robinson KA, Dremsizov TT, Young TL. Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review. JAMA. 2002;288(17):2151-2162.
 
Angus DC, Shorr AF, White A, Dremsizov TT, Schmitz RJ, Kelley MA; Committee on Manpower for Pulmonary and Critical Care Societies (COMPACCS) Committee on Manpower for Pulmonary and Critical Care Societies (COMPACCS). Critical care delivery in the United States: distribution of services and compliance with Leapfrog recommendations. Crit Care Med. 2006;34(4):1016-1024.
 
Zimmerman JE, Alzola C, Von Rueden KT. The use of benchmarking to identify top performing critical care units: a preliminary assessment of their policies and practices. J Crit Care. 2003;18(2):76-86.
 
Kim MM, Barnato AE, Angus DC, Fleisher LA, Kahn JM. The effect of multidisciplinary care teams on ICU mortality. Arch Intern Med. 2010;170(4):369-376.
 
Engoren M. The effect of prompt physician visits on ICU mortality and cost. Crit Care Med. 2005;33(4):727-732.
 
Phillips J. Clinical alarms: complexity and common sense. Crit Care Nurs Clin North Am. 2006;18(2):145-156.
 
Sinuff T, Cook D, Giacomini M, Heyland D, Dodek P. Facilitating clinician adherence to guidelines in the ICU: A multicenter, qualitative study. Crit Care Med. 2007;35(9):2083-2089.
 
Catalano K. Hand-off communication does affect patient safety. Plast Surg Nurs. 2009;29(4):266-270.
 
NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).
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  • CHEST Journal
    Print ISSN: 0012-3692
    Online ISSN: 1931-3543