Article

Perceived benefit of a telemedicine consultative service in a highly staffed intensive care unit

Department of Anesthesiology, Johns Hopkins, University School of Medicine, Armstrong Institute for Patient Safety and Quality, MD, USA.
Journal of critical care (Impact Factor: 2). 03/2012; 27(4):426.e9-16. DOI: 10.1016/j.jcrc.2011.12.007
Source: PubMed

ABSTRACT

The aim of this study was to evaluate whether a nocturnal telemedicine service improves culture, staff satisfaction, and perceptions of quality of care in a highly staffed university critical care system.
We conducted an experiment to determine the effect of telemedicine on nursing-staff satisfaction and perceptions of the quality of care in an intensive care unit (ICU). We surveyed ICU nurses using a modified version of a previously validated tool before deployment and after a 2-month experimental program of tele-ICU. Nurses in another, similar ICU within the same hospital academic medical center served as concurrent controls for the survey responses.
Survey responses were measured using a 5-point Likert scale, and results were analyzed using paired t testing. Survey responses of the nurses in the intervention ICU (n = 27) improved significantly after implementation of the tele-ICU program in the relations and communication subscale (2.99 ± 1.13 pre vs 3.27 ± 1.27 post, P < .01), the psychological working conditions and burnout subscale (3.10 ± 1.10 pre vs 3.23 ± 1.11 post, P < .02), and the education subscale (3.52 ± 0.84 pre vs 3.76 ± 0.78 post, P < .03). In contrast, responses in the control ICU (n = 11) declined in the patient care and perceived effectiveness (3.94 ± 0.80 pre vs 3.48 ± 0.86 post, P < .01) and the education (3.95 ± 0.39 pre vs 3.50 ± 0.80 post, P < .05) subscales.
Telemedicine has the potential to improve staff satisfaction and communication in highly staffed ICUs.

Full-text

Available from: Asad Latif, Aug 13, 2015
Perceived benefit of a telemedicine consultative service in
a highly staffed intensive care unit
Mark C. Romig MD
a,
, Asad Latif MD
a
, Randeep S. Gill MD
b
,
Peter J. Pronovost MD, PhD, FCCM
c
, Adam Sapirstein MD
a
a
Departments of Anesthesiology & Critical Care Medicine, Johns Hopkins, University School of Medicine,
Armstrong Institute for Patient Safety and Quality
b
Departments of Anesthesiology & Critical Care Medicine, Johns Hopkins, University School of Medicine
c
Departments of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine,
Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Nursing,
Johns Hopkins University Bloomberg School of Public Health
Keywords:
Attitude of health
personnel;
Health care surveys;
Job satisfaction;
Organizational culture
Abstract
Purpose: The aim of this study was to evaluate whether a nocturnal telemedicine service improves culture,
staff satisfaction, and perceptions of quality of care in a highly staffed university critical care system.
Methods: We conducted an experiment to determine the effect of telemedicine on nursing-staff
satisfaction and perceptions of the quality of care in an intensive care unit (ICU). We surveyed ICU nurses
using a modified version of a previously validated tool before deployment and after a 2-month
experimental program of tele-ICU. Nurses in another, similar ICU within the same hospital academic
medical center served as concurrent controls for the survey responses.
Results: Survey responses were measured using a 5-point Likert scale, and results were analyzed using
paired t testing. Survey responses of the nurses in the intervention ICU (n = 27) improved significantly
after implementation of the tele-ICU program in the relations and communication subscale (2.99 ± 1.13
pre vs 3.27 ±1.27 post, P b .01), the psychological working conditions and burnout subscale (3.10 ± 1.10
pre vs 3.23 ± 1.11 post, P b .02), and the education subscale (3.52 ± 0.84 pre vs 3.76± 0.78 post, P b .03).
In contrast, responses in the control ICU (n = 11) declined in the patient care and perceived effectiveness
(3.94 ± 0.80 pre vs 3.48 ± 0.86 post, P b .01) and the education (3.95 ± 0.39 pre vs 3.50 ± 0.80 post,
P b .05) subscales.
Conclusion: Telemedicine has the potential to improve staff satisfaction and communication in highly
staffed ICUs.
© 2012 Elsevier Inc. All rights reserved.
Financial Support was provided by The Johns Hopkins Hospital and the Johns Hopkins Department of Anesthesiology and Critical Care Medicine.
Corresponding author. Tel.: +1 410 502 3232.
E-mail addresses: mromig1@jhmi.edu (M.C. Romig), alatif1@jhmi.edu (A. Latif), rgill15@jhmi.edu (R.S. Gill), ppronovo@jhmi.edu (P.J. Pronovost),
asapirs1@jhmi.edu (A. Sapirstein).
0883-9441/$ see front matter © 2012 Elsevier Inc. All rights reserved.
doi:10.1016/j.jcrc.2011.12.007
Journal of Critical Care (2012) 27, 426.e9426.e16
Page 1
1. Introduction
Telemedicine used in the intensive care unit (tele-ICU)
has been proposed as a bridge between the clinical needs and
availability of intensivists [1]. Highly staffed models of
intensivist provider coverage are associated with lower ICU
and hospital mortality as well as reduced ICU and hospital
length of stay, but stafng in the United States is limited by
the number of available physicians [2,3]. Currently, only
approximately 1 quarter of intensive care units (ICUs) are
considered to be highly staffed, meaning more than 80% of
the patients are managed by a full-time or consulting
intensivist [2,4,5]. Current projections indicate that stafng
issues will be compounded by the aging population, which
will use more ICU resources and exacerbate the gap between
intensivist supply and demand [4-6].
Both on-site 24-hour intensivist staf ng and telemedicine
service have been proposed to provide highly staffed ICUs
and improve provider satisfaction [7-9]. However, telemed-
icine services have the capacity to provide oversight for a far
larger number of critically ill patients than does 24-hour on-
site coverage. This is because in large part of the tele-ICU
organizational structure that permits a single physician to
serve as a consultant for over 100 patients at a time [10].
Most of the tele-ICU services are provided and used by
nurses in the telemedicine center and at the bedside,
respectively [10] . Although improving patient care through
telemedicine can potentially improve the satisfaction of
bedside staff with the overall care environment, only 1 study
has addressed perceptions of tele-ICU [11].
Multiple studies have evaluated the efcacy of tele-ICU,
and the results have been mixed [8,12-17]. Telemedicine is a
complex cultural and technical intervention, and some of the
variation in study results could be caused by the context in
which telemedicine was implemented, used, and supported
within the hospitals [18] . Tele-ICU may be perceived as a
threat to existing unit culture and care processes. Such
perceptions can affect staff buy-in and, thus, adoption of a
tele-ICU program [19]. Lack of adequate adoption and
utilization may be an important factor in studies that failed to
show efcacy [15].
Since the rst study showing outcome benetofa
tele medicine intervention in the ICU, there has been
increasing adoption of tele-ICU nationwide and several
important studies of its effects on morbidity, mortality, and
processes of care [1,8,13-17], but the staff in 1 tele-ICU
system had variable attitudes about teamwork and safety
climates as they related to tele-ICU [11]. We had previously
conducted site visits and discussions with ICU physicians
and nurses at active tele-ICUs and believed that perceptions
toward telemedicine in the ICU were an important factor in
success [10]. We hypothesized that an effective tele-ICU
could improve communication with and satisfaction of the
bedside nurse providers. Because bedside staff involvement
in the tele-ICU system is critical to its success, we
performed the rst controlled prospective study of the
perceptions of bedside staff regarding a consultative tele-
ICU system [20].
2. Materials and methods
2.1. Setting
We studied the use of a tele-ICU system over an 11-week
period from January 19, 2010, to April 3, 2010. The study
protocol was reviewed and approved by the Johns Hopkins
Institutional Review Board. No patient identiers were
collected in this study, and requirements for informed
consent were waived by the review board. The intervention
was implemented in the Weinberg Intensive Care Unit
(WICU) at the Johns Hopkins Hospital (JHH). The WICU is
a highly staffed, 16-bed general surgical ICU in a large
academic center with an open admission policy and
mandatory intensivist consultation [2]. Attending coverage
is available 24 hours a day, in 7-day shifts, with board-
eligible or board-certied intensivists on-site during the day
and the same attending physician available by call at night.
At night, the intensivists were able to communicate with the
ICU by telephone and access the patient's medical record via
home computer using Johns Hopkins Medicine Center for
Information Services EPR v5.5.7 (Johns Hopkins Medical
Institutions, Baltimore, Md) and Sunrise Eclipsys Critical
Care v1.4M03 (Allscripts, Chicago, Ill), although they did
not have access to any real-time or telemetry data. Additional
coverage is provided 24 hours a day on-site with either a
critical care fellow or moonlighter who supervises residents
and critical care nurse practitioners. Moonlighters were
residents who had completed a minimum of 3 years of
surgical training and had spent at least 10 months training
within the ICU.
The surgical intensive care unit (SICU) at JHH was used
as the control ICU. The SICU is a 13-bed general surgical
ICU at JHH with a patient population similar to the WICU.
Physician stafng in the SICU is identical to the WICU, with
the exception that there are no advanced practice staff
employed in the SICU.
Demographic information for each ICU was collected for
both the study period and a historical period 1 year prior
(Table 1). Patient and procedural characteristics were
obtained from ICU admission logs. Aggregated mortality
and length of stay data were a vailable through ICU
administrative records. Payer mix and case mix index data
were collected from hospital billing records. The safety
attitudes questionnaire is administered on a biannual basis
independent of this study.
2.2. Intervention
We built a tele-ICU system that could be rapidly deployed
in the WICU by supplementing existing technology with
426.e10 M.C. Romig et al.
Page 2
2-way audiovisual communications and real-time physio-
logic monitoring data. The tele-ICU team consisted of 1
physician and 1 nurse who staffed the tele-ICU from 19:00 to
07:00 hours. The system was staffed every night during the
study period with the exception of two 3-day periods in
February when services were suspended because of snow
emergencies. The tele-ICU system was limited to a
consultative service in which the tele-ICU staff had no
order writing authority. Communication was bidirectional,
and consultations could be initiated by any staff member in
the ICU or the tele-ICU system. During the intervention, we
added new technologies to the tele-ICU system in 2-week
intervals, with full functionality being available by the end of
the rst month.
During the rst 2 weeks of the study, only baseline data
for a separate research study were obtained. Clinical
engineering and information technology resources were
used to access the patient electronic data record. Historical
patient information was available with the Johns Hopkins
Medicine Center for Information Services EPR v5.5.7,
Sunrise Eclipsys Critical Care v1.4M03, and Eclipsys
Sunrise Clinical Manager v5.8 SP3 (Allscripts, Chicago,
Ill). Electronic nursing ow sheets were available in Eclipsys
Sunrise Critical Care v1.4M03. Physician orders could be
accessed through Sunrise Eclipsys Clinical Manager v5.8
SP3. Radiographic images were available through Emageon
Enterprise Visual Medical System Advanced Visualization
v5.30.7.26 (Emageon, Birmingham, Ala). Telephony ser-
vices were used for all communication during this time.
During the sec ond 2 weeks, we added audiovisual
communication with the use of the RP7 robot (InTouch
Health, Santa Barbara, Calif). The RP7 is a self-propelled
device that was controlled from a remote workstation by the
tele-ICU staff. Both the RP7 and the workstation had a
camera and video monitor, which allowed bidirectional
audiovisual communications. From this point forward, the
RP7 was the primary mode for communication with the ICU
staff, although telephone communications were available.
Real-time hemodynamic monitoring was also added
during the second 2 weeks using the Bernoulli real-time
clinical data system (Cardiopulmonary Corp, Greenwich,
Conn). The Bernoulli interface allowed access to the
numerical hemodynamic parameters such as pulse,
invasive and noninvasive blood pressure, respiratory rate,
and temperature. This system provided the tele-ICU with
independent, customizable alarms and an interface that
allowed simultaneous monitoring of all patients within the
ICU. After the nal rollout period, live and trended
waveform data were also available using the Bernoulli
interface. During the study period, no new technologies
or changes in care patterns were implemented in the
control ICU.
Table 1 Comparison of ICU characteristics during study period and 1 year prior
Study ICU Control ICU
Study period Historic period Study period Historic period
Total admissions 403 390 307 305
Age (y), mean (SD) 58.9 (15.2) 60.3 (13.5) 53.3 (18.5) 53.4 (18.4)
Male sex 200 (50%) 199 (51%) 157 (57%) 194 (64%)
Admitting diagnosis
Abdominal 189 (47%) 193 (49%) 48 (16%) 59 (19%)
Gynecologic 22 (5%) 18 (5%) 2 (b1%) 5 (2%)
Orthopedic 21 (5%) 19 (5%) 51 (17%) 33 (11%)
Otolaryngologic 51 (13%) 26 (7%) 7 (2%) 0
Renal 13 (3%) 27 (7%) 8 (3%) 8 (3%)
Thoracic 95 (24%) 101 (26%) 5 (2%) 15 (5%)
Transplant 3 (b1%) 1 (b1%) 33 (11%) 50 (16%)
Trauma 0 0 77 (25%) 57 (19%)
Vascular 0 3 (b1%) 54 (18%) 46 (15%)
Other 9 (2%) 2 (b1%) 22 (7%) 31 (10%)
Total patient days 1542 1543 1044 1045
Total mortality (mortality rate) 14 (3.5%) 6 (1.5%) 14 (4.6%) 15 (4.9%)
Mean daily census (patients) 12.85 ± 3.03 12.86 ± 3.32 8.70 ± 1.87 8.71 ± 1.33
Mean length of stay (d) 3.8 3.9 4.5 5.1
Case-mix index 2.74 3.15 3.61 3.96
Payor mix
Private 42% 35% 49% 26%
Medicare 4% 8% 5% 11%
Medicaid 52% 54% 38% 52%
Other 3% 3% 8% 11%
SAQ job satisfaction score 76 N/A 34 N/A
SAQ indicates safety attitudes questionnaire.
426.e11Telemedicine consultative service in a highly staffed ICU
Page 3
2.3. Data collection and analysis
In consultation with research methods experts, we
modied a previously published, validated survey that was
used to assess provider perceptions when a 24-hour stafng
model was implemented [7,21]. The survey instrument was
obtained from and used with permission of the primary
author of the previous study. Questions were organized into
5 domains, which included perceived effectiveness, com-
munication and relations within the unit, psychological
working conditions and burnout, and job satisfaction and
intention to quit. Modications to the questions addressed
local cultural terminology (eg, intensivist vs consultant), and
no changes were made to the content of the questions. Our
nal survey instrument contained 26 questions that were
measured using a 5-point Likert scale. The written surveys
were administered simultaneously to nurses who worked in
either the WICU or the SICU before and after the tele-ICU
intervention (Fig. 1). Survey responses were condential,
and respondents were assigned a numeric identier to allow
pre-post survey matching. No respondent identiers were
retained after distribution of the second survey.
Responses were collected in an Access 2007 database
(Microsoft, Redmond, Wash), and Prism v5.03 (Graphpad
Software, La Jolla, Calif) software was used for statistical
analysis. The means of preintervention and postintervention
responses were compared within each ICU. In addition, the
means of the individual differences between the preinterven-
tion and postintervention responses were calculated for each
question, and results were compared between the study and
control ICU. Responses to individual questions and question
subgroups and the calculated change in response over time
were compared using paired Student t test or Wilcoxon
signed rank test, where appropriate, and used 95%
condence intervals. P values of less th an .0 5 were
considered to be statistically signicant.
3. Results
A total of 710 patients were admitted to the ICUs during
the study period. Although there are some demographic
differences noted between the 2 ICUs, the composition of
each ICU did not change when compared with a historical
control period. Specically, differences were noted in total
admissions, age, sex, total patient days, length of stay, and
case mix index, which likely reect differences in admitting
surgical diagnosis. Differences in mean censuses were noted,
which represents the difference in ICU capacities. The payer
mix changed in both ICUs when compared with historical
data, but the payer mix is similar in both ICUs during each
period. The Johns Hopkins Hospital performs a safety
attitudes questionnaire (SAQ) on a biannual basis, and we
note that the scores differed between the 2 ICUs for the
survey that was performed during the year of this study [22].
The tele-ICU intervention took place in the WICU, which
has a dedicated nursing staff of 70, whereas the control ICU
(SICU) has a staff of 65 nurses. Details of each ICU are
presented in the Methods section. Before implementation
of the tele-ICU program, 32 WICU nurses and 23 SICU
nurses completed surveys. Upon completion of the tele-ICU
program, we obtained paired surveys from 27 WICU nurses
(completion rate, 39% off all and 84% of those who
completed the presurvey) and 11 SICU nurses (completion
rate, 18% of all and 48% of those who completed the
presurvey). After the study, demographic information was
collected fo r bo th ICUs during the study per iod and
compared with the same dates 1 year prior (Table 1). In
both ICUs, there were no differences observed in the total
admissions, total patient days, average daily census, and
average length of stay when the study period was compared
with the historical period. There was a noted increase in the
absolute WICU mortality during the study period. The
WICU had a shorter length of stay, a larger average daily
census, more admissions, and more total patient days when
compared with the control ICU (Table 1). This may indicate
some difference in the operations of the 2 ICUs.
Of the 26 questions in the nursing survey, the composite
responses from the WICU trended favorably for the tele-ICU
care model in 17 questions, unchanged in 4 questions, and
unfavorably in only 5 questions (Fig. 2). Negative responses
were only observed within the patient care and perceived
effectiveness questions and psychological conditions and
burnout questions; however, none of the negatively trended
responses reached statistical signicance. Within these same
question sets, there was a preponderance of positively
Fig. 1 Nursing enrollment and study administration timeline.
426.e12 M.C. Romig et al.
Page 4
trended re sponses, some of which reached statistical
signicance (P b .05). Responses within the relations and
communications subgroup were overwhelmingly positive
with statistical signicance reached in 2 of the 3 questions
(P b .05). When questions within the subgroups were
aggregated and analyzed, all subgroups were either
unchanged or showed improvement, with the improvement
in the relations and communications subgroup (P = .01)
and education subg roup (P = .02) showing statistical
signicance (Data not shown).
In the control ICU, only 6 questions had favorable trends,
whereas 20 were unfavorable during the study period. Of
interest, the only question that reached a negative statistical
signicance (P = .01) was The intensivists are readily
available and participate in the care of patients. Questions
relating to patient care and perceived effectiveness, job
satisfaction and intention to quit, and education all trended
negatively. When the questions were aggregated and
analyzed as subgroups, all showed a decline over the study
period with statistical signicance achieved in the patient
care and perceived effectiveness (P = .01) and education
subgroups (P = .04) (Data not shown).
As expected, the baseline (p reinte rvention) responses
varied between the 2 ICUs. We reasoned that a c omparison
of th e change in sur vey scor es between the con trol and
intervention ICUs would likely represent the effects of the
tele-ICU system. We calculated the differences between
values for ea ch re sponse before and after implementatio n of
the tele-ICU and compared this value for the intervention
ICU (WICU) to the control ICU (SICU). Study ICU
responses trended better than those in the control ICU in all
but 5 questions and demonstrated statistically signicant
improvement for 5 of the 26 questions (Fig. 3). When
questions within the subgroups were aggreg ated and
analyzed, all subgroups favored the study ICU, and
statistical signicance was reached in the job satisfaction
subgroup (P b .05 ) and the relatio ns and communications
subgroup (P = .04) (data not shown) .
4. Discussion
Although several studies have looked at the association of
tele-ICU to various patient outcome measures, few studies
have actively addressed staff perceptions. Staff perceptions
of tele-ICU may be an underappreciated variable of program
success, as perceptions and culture are tightly tied to
successful adoption [15,19]. To date, ours is the only study
Fig. 2 Summary of nurse responses within the study ICU.
426.e13Telemedicine consultative service in a highly staffed ICU
Page 5
that measures bedside staff perceptions with simultaneous
comparison with a control ICU. These results demonstrate
that nursing staff perceived benet from a tele-ICU in a
highly staffed ICU.
A previous study by Gajic et al [7] gauged the perceptions
of st aff working within an ICU with 24-hour on-site
intensivist availability. Given the similarities of their on-
site model and our telemedicine model, we used a modied
version of t heir original survey to ol in our s tudy.
Modications were necessary to account for variations in
local hospital culture (eg, consultant vs intensivist); however,
the meaning of the questions was unchanged. Decisions
regarding ICU stafng may require a choice between on-site
physician coverage and telemedicine coverage. By using this
survey, we are able to compare the nursing responses
between these models.
In previous studies of ICU telemedicine, the tele-ICU was
deployed as part of a greater information technology and
ICU management change program. For example, McCam-
bridge et al [17] characterized the tele-ICU as one component
of a coordinated health care information technology bundle.
The governance structure of ICU care within the University
of MassachusettsMemorial health care system was restruc-
tured and centralized before a tele-ICU implementation [3].
In our work, we limited changes within the ICU to 2-way
audiovisual communication and tele-ICU stafng. During
the study period, there were no other quality or cultural
improvement interventions implemented in either the study
or control ICU. Thus, we conclude that benet suggested by
our results is caused directly by the enhanced tele-ICU
services and not implementation of other technologies (eg,
electronic health record, data management, etc).
Telemedicine is a complex sociotechnical intervention,
and the context regarding how it is implemented and
supported and the type of organizations in which it is used
may inuence its impact Young et al [3]. We chose to use a
consultative care model so that it could be uniformly
applied to all patients in the test ICU. Previous studies in
tele-ICU have suffered from an inability to standardize
practice to all patients in the covered ICUs [12,15].In
contrast, in centers where tele-ICU interventions were
mandatory and uniform, a mortality benet was demon-
strated [8,17] . We found that, by limiting the tele-ICU team
to consultative care, bedside providers were more accepting
and that the primary surgical teams allowed all of their
patients to participate.
Although each of the ICUs is a general surgical ICU, there
were some demographic differences noted, which is likely a
function of preferentially triaging certain admitting diagno-
ses to one or the other ICU. Patient age and sex were
different between the 2 ICUs, and this is likely a result of the
number of trauma patients in the control ICU, a population
Fig. 3 Comparison of the change in Likert score from the preintervention period to the postintervention period: intervention vs control ICU.
426.e14 M.C. Romig et al.
Page 6
that tended to be younger and male. Complex vascular and
transplant cases were also primarily triaged to the control
ICU, which may be reected in the increased case mix index
and length of stay. The baseline ICU mortality in the WICU
is extremely low (1.5% of admissions during the historical
period), and the increase during the study period (3.5 %)
likely represents random variation in this low level. Analysis
of mortality using χ
2
testing showed that this change was not
statistically signicant. Based on this low mortality, the short
study period, and the effect size of tele-ICU in other studies,
we predicted that the current study was not powered to
investigate changes in mortality or other patient outcomes.
The SAQ was used by the hospital to measure job
satisfaction in both ICUs during the year of, but was
independent of, our study. Job satisfaction was notably
higher in the study ICU, which is consistent with our survey
ndings, and may be a function of the cultural impact of
telemedicine. However, the SAQ did not explicitly study the
impact of our telemedicine intervention, so conclusions
about this measurement are limited.
Our study showed a perceived benet of telemedicine by
nursing staff even within a highly staffed ICU. Despite
numerous studies of staff satisfaction, none have shown
a direct correlation between nursing perceptions of care
and patient outcomes. However, perceptions of improved
job satisfaction and communication among nurses have
been identied in ICUs that produce results in improving
safety [23].
Our result is similar to the ndings of Chu-Weininger et al
[11], in which nurses in a tele-ICU showed improvement in
perceptions of safety and teamwork climate. In addition, our
study showed that the perception of care in the control unit
actually worsened during the time of study. Work load
factors can negatively impact staff perceptions of safety and
communication culture. The survey results in the control unit
may suggest that such stressors were present in the hospital
system during the implementation period. The fact that
WICU perceptions of safety and communications improved
during a pe rio d of perceive d str ess suggests t hat the
telemedicine intervention had a signicant effect in this
area. We expect that this effect would be enhanced in a lesser
staffed ICU or by implementing a more intensive interven-
tion (eg, order writing).
We recognize that our study has limitations. First, we did
not have sufcient power to measure patient outcomes.
Based on our extremely low mortality, we recognized that
achieving adequate power to measure mortality outcomes
was beyond the scope of this study and would require a
permanent telemedicine installation. However, communica-
tion problems are a common source of errors and preventable
harm, and we believe that our results demonstrate that
enhanced communication and oversight have the potential to
improve patient outcomes. Second, this study was conducted
over a relatively short period, and we cannot know if the
improvements would persist. However, if the study had been
carried out for a longer period, other factors could have
inuenced staff perceptions and potentially biased our
results. Third, we did not formally validate our survey
instrument. We used a previously published and validated
survey instrument and modi ed some questions to t our
culture and nomenclature. The modi cations made to the
survey were minor and not likely to signicantly bias the
results. In addition, the intensivists and many of the nurses
stafng the tele-ICU routinely work in the study ICU. Staffs
in both ICUs were able to freely communicate, and staff in
the control ICU was aware of project progress within the
study ICU. It is reasonable to infer that positive perceptions
of the project were communicated to the control ICU. This
may have inadvertently inuenced responses within the
control ICU resulting in a greater depression of attitudes and
perceptions than would have been seen if no project was
underway. Along these lines, postsurvey completion rates in
the study ICU appear to be much higher than the control
ICU. This may be a function of the enthusiasm for the project
in study ICU, which was not experienced in the control ICU.
Finally, both the test and control ICUs are part of a large
academic teaching hospital in which participation in process
improvement projects is an expectation. As a result our
results may not be generalizable.
5. Conclusion
Telemedicine has traditionally been thought of as a means
to bring intensivist resources to understaffed ICUs, typically
in rural or community hospitals, or to provide nocturnal
coverage in ICUs that only have a daytime intensivist. Our
study showed that the introduction of tele-ICU services in a
highly staffed academic ICU was associated with an
improvement in nursing perceptions of working conditions
and communications. We believe that this study demon-
strates the ability of telemedicine to improve the nursing
perceptions of care and processes in the ICU.
Acknowledgments
The authors would like to thank Dr John Ulatowski, the
Johns Hopkins Department of Anesthesiology and Critical
Care Medicine, Alex Nason, Johns Hopkins International,
Steve Mandel, Johns Hopkins Information Services,
Samantha Young, Judy Schroeder, Gail Biba, Christina
Lundquist, Stephanie Swanson, and Marie Diener-West for
their help and support of this project.
References
[1] Fifer S, Everett W, Adams M, Vincequere J. Critical care, critical
choices: the case for tele-ICU's in intensive care. Mass Technol Collab
N Engl Healthcare Inst 2010.
426.e15Telemedicine consultative service in a highly staffed ICU
Page 7
[2] 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):
2151-62.
[3] Young LB, Chan PS, Cram P. Staff acceptance of tele-ICU coverage.
Chest 2011;139(2):279-88.
[4] U.S. department of health and human resources report to congress: the
critical care workforce: a study of the supply and demand for critical
care physicians. Health Resour Serv Admin 2006.
[5] Angus D, Shorr A, White A, Dremsizov T, Schmitz R, Kelley M, et al.
Critical care delivery in the united states: distribution of services and
compliance with leapfrog recom mendations. Crit Care Med
2006;34(4):1016-24.
[6] Angus DC, Kelley MA, Schmitz RJ, White A, Popovich Jr J, for the
Committee on Manpower for Pulmonary and Critical Care Societies.
Current and projected workforce requirements for care of the critically
ill and patients with pulmonary disease: can we meet the requirements
of an aging population? JAMA 2000;284(21):2762-70.
[7] Gajic O, Afessa B, Hanson AC, Krpata T, Yilmaz M, Mohamed SF,
et al. Effect of 24-hour mandatory versus on-demand critical care
specialist presence on quality of care and family and provider
satisfaction in the intensive care unit of a teaching hospital. Crit Care
Med. 2008;36(1):36-44.
[8] Lilly CM, Cody S, Zhao H, Landry K, Baker SP, McIlwaine J, et al.
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):2175-83.
[9] Banerjee R, Naessens J, Seferian E, Gajic O, Moriarty J, Johnson M,
et al. Economic implications of nighttime attending intensivist
coverage in a medical intensive care unit. Crit Care Med 2011;39(6):
1257-62.
[10] Sapirstein A, Lone N, Latif A, Fackler J, Pronovost P. Tele ICU:
Paradox or panacea? Best Pract Res Clin Anaesthesiol. 2009;23(1):
115-26.
[11] Chu-Weininger MYL, Wueste L, Lucke JF, Weavind L, Mazabob J,
Thomas EJ. The impact of a tele-ICU on provider attitudes about
teamwork and safety climate. Qual Saf Health Care 2010;19(6).
[12] Rosenfeld BA, Dorman T, Breslow MJ, Pronovost P, Jenckes M,
Zhang N, et al. Intensive care unit telemedicine: Alternate paradigm for
providing continuous intensivist care. Crit Care Med. 2000;28(12):
3925-31.
[13] Breslow MJ, Rosenfeld BA, Doerfler M, Burke G, Yates G, Stone DJ,
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(1):31-38.
[14] Zawada ETJ, Herr P, Larson D, Fromm R, Kapaska D, Erickson D.
Impact of an intensive care unit telemedicine program on a rural health
care system. Postgrad Med. 2009;121(3):160-170.
[15] Thomas EJ, Lucke JF, Wueste L, Weavind L, Patel B. Association of
telemedicine for remote monitoring of intensive care patients with
mortality, complications, and length of stay. JAMA 2009;302(24):2671-8.
[16] Morrison JL, Cai Q, Davis N, Yan Y, Berbaum M, Ries M, et al.
Clinical and economic outcomes of the electronic intensive care
unit: Results from two community hospitals. Crit Care Med. 2010;
38(1):2-8.
[17] 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):648-53.
[18] Eliminating CLABSI: A national patient safety imperative. AHRQ
Publication No.: 11-0037-EF. Rockville, MD: Agency for Healthcare
Research and Quality; 2011.
[19] Kahn JM. The use and misuse of ICU telemedici ne. JAMA
2011;305(21):2227-8.
[20] Pronovost PJ, Nolan T, Zeger S, Miller M, Rubin H. How can
clinicians measure safety and quality in acute care? Lancet
2004;363(9414):1061-7.
[21] Minvielle E, Dervaux B, Retbi A, Aegerter P, Boumendil A,
Jars-Guincestre MC, et al. Culture, organization, and management in
intensive care: construction and validation of a multidimensional
questionnaire. J Crit Care 2005;20(2):126-38.
[22] Pronovost PJ, Weast B, Holzmueller CG, Rosenstein BJ, Kidwell RP,
Haller KB, et al. Evaluation of the culture of safety: survey of
clinicians and managers in an academic medical center. Qual Saf
Health Care 2003;12(6):405-10.
[23] Pronovost PJ, Berenholtz SM, Goeschel C, Thom I, Watson SR,
Holzmueller CG, et al. Improving patient safety in intensive care units
in Michigan. J Crit Care 2008;23(2):207-21.
426.e16 M.C. Romig et al.
Page 8
  • Source
    [Show abstract] [Hide abstract] ABSTRACT: Introduction Telemedicine extends intensivists' reach to critically ill patients cared for by other physicians. Our objective was to evaluate the impact of telemedicine on patients' outcomes. Methods We searched electronic databases through April 2012, bibliographies of included trials, and indexes and conference proceedings in two journals (2001 to 2012). We selected controlled trials or observational studies of critically ill adults or children, examining the effects of telemedicine on mortality. Two authors independently selected studies and extracted data on outcomes (mortality and length of stay in the intensive care unit (ICU) and hospital) and methodologic quality. We used random-effects meta-analytic models unadjusted for case mix or cluster effects and quantified between-study heterogeneity by using I2 (the percentage of total variability across studies attributable to heterogeneity rather than to chance). Results Of 865 citations, 11 observational studies met selection criteria. Overall quality was moderate (mean score on Newcastle-Ottawa scale, 5.1/9; range, 3 to 9). Meta-analyses showed that telemedicine, compared with standard care, is associated with lower ICU mortality (risk ratio (RR) 0.79; 95% confidence interval (CI), 0.65 to 0.96; nine studies, n = 23,526; I2 = 70%) and hospital mortality (RR, 0.83; 95% CI, 0.73 to 0.94; nine studies, n = 47,943; I2 = 72%). Interventions with continuous patient-data monitoring, with or without alerts, reduced ICU mortality (RR, 0.78; 95% CI, 0.64 to 0.95; six studies, n = 21,384; I2 = 74%) versus those with remote intensivist consultation only (RR, 0.64; 95% CI, 0.20 to 2.07; three studies, n = 2,142; I2 = 71%), but effects were statistically similar (interaction P = 0.74). Effects were also similar in higher (RR, 0.83; 95% CI, 0.68 to 1.02) versus lower (RR, 0.69; 95% CI, 0.40 to 1.19; interaction, P = 0.53) quality studies. Reductions in ICU and hospital length of stay were statistically significant (weighted mean difference (telemedicine-control), -0.62 days; 95% CI, -1.21 to -0.04 days and -1.26 days; 95% CI, -2.49 to -0.03 days, respectively; I2 > 90% for both). Conclusions Telemedicine was associated with lower ICU and hospital mortality among critically ill patients, although effects varied among studies and may be overestimated in nonrandomized designs. The optimal telemedicine technology configuration and dose tailored to ICU organization and case mix remain unclear.
    Full-text · Article · Jul 2012 · Critical care (London, England)
  • Source
    [Show abstract] [Hide abstract] ABSTRACT: Aging population is set to increase in the near future, and will need specialized care when admitted to ICUs. The elderly are beset with chronic conditions, such as cardiovascular, COPD, diabetes, renal complications and depression. Specialist opinions can now be made available through telemedicine facilities. Tele-ICU is a specialized hub consisting of highly skilled staff trained in critical care able to deliver timely, quality care service to patients admitted to ICUs in remote areas using highly advanced information technology services. These specialists in the tele-ICU hub are able to analyze and gather data arriving at timely interventional management decisions and provide this vital feedback to the nursing staff and doctors manning remote ICU locations where specialized intensivist may not be available. Known clinical benefits of such a system include better patient outcomes, reduced medical errors, mortality and reduced hospital length of stay. The main disadvantage in implementation could be the upfront high cost involved, for which low-cost models are being explored. In the face of delivering such remote care, it is up to the local health policy to make legislative changes to include associated legal and ethical issues. Considering the burgeoning aging population, tele-ICU could become the way forward in delivering geriatric critical care.
    Preview · Article · May 2014 · Aging - Clinical and Experimental Research
  • [Show abstract] [Hide abstract] ABSTRACT: Background: Increasing intensivist shortages and demand coupled with the escalating cost of care have created enthusiasm for intensive care unit (ICU)-based telemedicine ("tele-ICU"). This systematic literature review compares the Centralized Monitoring and Virtual Consultant tele-ICU Models. Materials and methods: With an experienced medical reference librarian, we identified all language publications addressing the employment and efficacy of the centralized monitoring and virtual consultant tele-ICU systems through PubMed, CINAHL, and Web of Science. We performed quantitative and qualitative reviews of documents regarding financial sustainability, clinical outcomes, and ICU staff workflow and acceptance. Results: Of 1,468 documents identified, 1,371 documents were excluded, with the remaining 91 documents addressing clinical outcomes (46 documents [enhanced guideline compliance, 5; mortality and length of stay, 28; and feasibility, 13]), financial sustainability (9 documents), and ICU staff workflow and acceptance (36 documents). Quantitative review showed that studies evaluating the Centralized Monitoring Model were twice as frequent, with a mean of 4,891 patients in an average of six ICUs; Virtual Consultant Model studies enrolled a mean of 372 patients in an average of one ICU. Ninety-two percent of feasibility studies evaluated the Virtual Consultant Model, of which 50% were in the last 3 years. Qualitative review largely confirmed findings in previous studies of centralized monitoring systems. Both the Centralized Monitoring and Virtual Consultant Models showed clinical practice adherence improvement. Although definitive evaluation was not possible given lack of data, the Virtual Consultant Model generally indicated lean absolute cost profile in contrast to centralized monitoring systems. Conclusions: Compared with the Virtual Consultant tele-ICU Model, studies addressing the Centralized Monitoring Model of tele-ICU care were greater in quantity and sample size, with qualitative conclusions of clinical outcomes, staff satisfaction and workload, and financial sustainability largely consistent with past systematic reviews. Attention should be focused on performing more high-quality studies to allow for equitable comparisons between both models.
    No preview · Article · Sep 2014 · Telemedicine and e-Health
Show more