Keywords
electronic health record - telemetry - appropriate telemetry use
Background and Significance
Background and Significance
Cardiac telemetry monitoring in accordance with evidence-based standards predicts
cardiac events,[1] but inappropriate overuse leads to alarm fatigue, patient discomfort, and unnecessary
resource utilization including unnecessary work-up potentially adversely impacting
patient safety and increasing costs of care.[2]
[3]
[4] The American Heart Association (AHA) has published guidelines on appropriate telemetry
use[1] and the Society of Hospital Medicine's Choosing Wisely initiative recommends against
using continuous telemetry monitoring outside the intensive care unit (ICU) without
a protocol that governs its continuation.[5] Many providers are unaware of these guidelines and recommendations and few receive
education about guideline-directed telemetry use. On acute care services, telemetry
is often ordered due to patients' deteriorating clinical status and less so to monitor
cardiac rhythm dysfunction.[6]
Several studies have tried different approaches to address these shortcomings including
provider education, routine feedback, provider incentives, and modifications to electronic
health record (EHR) telemetry orders. These studies have demonstrated that multifaceted
approaches do in fact lead to more appropriate telemetry utilization and duration
of use,[7]
[8]
[9]
[10] but may require more resources and time to complete. Other studies have shown that
changes to the EHR with reminders about discontinuing telemetry via pop-up dialog
boxes or automatic telemetry discontinuation after a set time period, without provider
education or incentives, were enough to encourage appropriate telemetry ordering and
increase timely telemetry discontinuation.[11]
[12]
[13] To date, no study has looked at other methods using the EHR to directly ask providers
to consider discontinuing telemetry when the guideline-recommended duration for a
specific indication has passed.
Objectives
We describe a quality-improvement project to help physicians appropriately order telemetry
and decrease unnecessary use by making modifications to the EHR. Specifically, we
describe three interventions to the EHR, all of which were low cost and required minimal
time to implement. We examine hours of telemetry use and percent telemetry orders
discontinued prior to discharge pre- and post-intervention to determine if the EHR
changes lead to improved telemetry utilization. Additionally, we look at differences
in hours of telemetry use and percent telemetry orders discontinued prior to discharge
between services with residents versus just hospitalists. We also examine how hours
of telemetry use and percent telemetry orders discontinued change over an extended
period of time (2 and 3 years post-intervention). Our goal was to harness the EHR
to actively support providers in ordering telemetry in accordance with evidence-based
guidelines and discontinuing telemetry when it is no longer medically necessary on
acute care services.
Methods
Study Design, Setting, and Population
The project was designed as a quality-improvement project at two academic medical
centers within the University of Washington Medicine Health System, Harborview Medical
Center (HMC), a 413-bed academic referral center and safety net hospital, and University
of Washington Medical Center (UWMC), a 570-bed academic referral center. Data were
extracted from the EHR for all hospital stays in which patients had telemetry monitored
for admissions from July 2015 to June 2019. ICU telemetry usage was excluded. For
patients who had telemetry ordered more than once during the same hospitalization,
only the first telemetry episode was evaluated. We limited this analysis to patients
cared for on acute care medicine services; some services were hospitalist only and
others were teaching services with residents. Attending physicians on the resident
medicine services included hospitalists and nonhospitalist internal medicine physicians.
HMC has three hospitalist-run services and five resident medicine teams. UWMC has
two hospitalist teams and four resident medicine teams. Patients are assigned to medicine
teams based on time of day and admitting capacity of the resident teams. Each site
has a distinct cardiology service.
Intervention
In July 2016, we implemented three changes to the EHR to support guideline-directed
telemetry ordering without provider training or staff coaching. The first was a new
telemetry order set that requires providers to use AHA-recommended indications for
telemetry and lists the evidence-based duration of telemetry for each condition ([Fig. 1]). The order set includes a list of conditions for which telemetry is frequently
ordered but not recommended per current standards to discourage inappropriate monitoring.
Fig. 1 Electronic health record telemetry order set requiring providers to choose an indication
for telemetry with guideline-recommended duration of telemetry monitoring.
The second change involved creating an automatic paging system set up through the
EHR to actively notify the primary providers caring for patients on telemetry when
the order duration has exceeded the guideline-recommended duration. The page recommends
discontinuation of telemetry unless there is a new indication. Pages are sent during
daytime work hours and are bundled in the morning to coincide with usual rounding
times. We chose direct paging of providers from the EHR as this system is updated
by providers themselves identifying their role in real time. This ensures that the
patient's “primary contact” who is paged is accurately identified in the context of
multiple handoffs in a complex teaching environment.
The third change involved telemetry technicians moving from a paper-based record (printing
telemetry strips filed in the paper chart) to documenting their findings in the EHR
at one of the two sites. With implementation of the EHR, telemetry readings were the
only clinical data that remained on paper except for patient registration materials,
creating a gap in the EHR documentation. This shift in practice was intended to support
communication between telemetry technicians, providers, and nurses and to increase
provider awareness of telemetry findings. The algorithm that technicians used to notify
the nurse or provider of any significant changes in rhythm did not change.
Data Collection and Analysis
Data were electronically abstracted from the EHR for both hospitals for 1 year pre-intervention
(July 2015–June 2016) and 1 year post-intervention (July 2016–June 2017).We reviewed
two additional years of data to examine sustainability. Data including telemetry order
initiation and discontinuation date and time were initially collected as part of a
quality improvement project for patients admitted to medicine acute care services
for whom telemetry was ordered. All identifiers except month and year of order were
destroyed. Data were examined in aggregate and separately for the hospitalist-only
and resident services. We also obtained the average annual patient volume and length
of stay on medicine services for each hospital to control for environmental trends.
At the site at which telemetry technicians transcribed documentation directly into
the EHR, we surveyed them about their experience with the new workflow.
The percentage of orders actively discontinued and the average number of hours on
telemetry were computed for each month and compared over time for each hospital and
by service. We used t-tests to compare annual proportions (percent active order discontinuation) and means
(hours on telemetry) for years 1, 2, and 3 against year 0. We used Stata 16 for statistically
analyses and Excel to create the run charts.
Results
Overall, this set of EHR interventions led to increased active discontinuation of
telemetry monitoring on acute care medicine services with a 15% increase at HMC (63.4–78.7%,
p < 0.001) and 13% increase at UWMC (64.1–77.4%, p < 0.001; [Table 1]). At both sites, we saw a slightly greater increase in active discontinuation among
resident teams compared with hospitalist teams (16.1 vs. 13.1% [HMC]; 13.5 vs. 11.8%
[UWMC]) and only the resident improvements were statistically significant. At HMC,
residents were more likely to actively discontinue telemetry orders prior to intervention
than hospitalists; this was reversed at UWMC.
Table 1
Percentage of telemetry orders actively discontinued prior to discharge preintervention
and 1 to 3 years postintervention by site and by service
|
Telemetry discontinued
|
Baseline Pre: 2015–2016
|
Year 1 post: 2016–2017
|
Year 2 post: 2017–2018
|
Year 3 post: 2018–2019
|
|
% (n)
|
% (n)
|
% change from baseline
|
% (n)
|
% change from baseline
|
% (n)
|
% change from baseline
|
|
Site 1: all services
|
63.4 (985)
|
78.7 (850)
|
15.3[a]
|
79.7 (883)
|
16.3[a]
|
79.8 (952)
|
16.4[a]
|
|
Resident services
|
64.2 (801)
|
80.3 (669)
|
16.1[a]
|
78.7 (666)
|
14.5[a]
|
76.4 (750)
|
12.2[a]
|
|
Hospitalist services
|
59.8 (184)
|
72.9 (181)
|
13.1[a]
|
83.8 (167)
|
24.0[a]
|
78.2 (202)
|
18.4[a]
|
|
Site 2: all services
|
64.1 (518)
|
77.4 (455)
|
13.3[a]
|
73.7 (475)
|
9.6[a]
|
75.8 (532)
|
11.7[a]
|
|
Resident services
|
63.0 (408)
|
76.5 (340)
|
13.5[a]
|
75.8 (356)
|
12.8[a]
|
76.0 (384)
|
13.0[a]
|
|
Hospitalist services
|
68.2 (110)
|
80.0 (115)
|
11.8[a]
|
67.2 (119)
|
-1.0
|
75.0 (148)
|
6.8
|
a
p ≤ 0.01.
In the year after implementing our EHR intervention, we also observed decreased numbers
of telemetry orders across medicine services at each site (985 to 850 at HMC; 518
to 455 at UWMC) although the number of patients admitted to medicine services increased
([Table 1]). The decrease in number of medicine acute care telemetry orders reflects fewer
telemetry orders among resident teams. Numbers of telemetry orders were similar among
hospitalists in the 2 years. There was also a statistically significant decrease in
mean duration of telemetry at both sites (62 to 47 hours, p < 0.001 at HMC; 73.3 to 59.8 hours, p < 0.001 at UWMC) despite essentially unchanged hospital length of stay on medicine
services ([Table 2]). Decreases in telemetry duration were only statistically significant among resident
teams.
Table 2
Mean hours of telemetry use preintervention and 1 to 3 years postintervention, by
site and by service
|
Telemetry hours
|
Baseline Pre: 2015–2016
|
Year 1 post: 2016–2017
|
Year 2 post: 2017–2018
|
Year 3 post: 2018–2019
|
|
Mean (SD) [95% CI]
|
Mean (SD) [95% CI]
|
Mean change from baseline
|
Mean (SD) [95% CI]
|
Mean change from baseline
|
Mean (SD) [95% CI]
|
Mean change from baseline
|
|
Site 1: all services
|
62.0 (81.9) [56.8–67.1]
|
47.0 (51.5) [43.6–50.5]
|
14.9[a]
|
46.8 (46.2) [43.7–50.0]
|
15.1[a]
|
53.9 (59.0) [50.2–57.7]
|
8.0[b]
|
|
Resident services
|
65.1 (87.9) [59.0–71.2]
|
49.0 (55.0) [44.8–53.2]
|
16.1[a]
|
47.9 (48.6) [44.2–51.6]
|
17.2[a]
|
56.5 (61.2) [52.1–60.9]
|
8.6[b]
|
|
Hospitalist services
|
48.4 (45.0) [41.8–54.9]
|
39.9 (34.5) [34.8–44.9]
|
8.5[b]
|
42.4 (35.1) [37.1–47.8]
|
6.0
|
44.4 (48.9) [37.6–51.1]
|
4.0
|
|
Site 2: all services
|
73.3 (88.7) [65.6–81.0]
|
59.8 (68.0) [53.5–66.1]
|
13.5[a]
|
58.3 (68.0) [52.2–64.5]
|
15.0[a]
|
60.4 (64.7) [54.9–65.9]
|
12.9[a]
|
|
Resident services
|
75.2 (89.0) [66.5–83.8]
|
59.1 (69.3) [51.7–66.5]
|
16.1[a]
|
58.2 (64.6) [51.5–64.9]
|
16.9[a]
|
61.7 (63.9) [55.3–68.1]
|
13.4[b]
|
|
Hospitalist services
|
66.4 (87.7) [49.8–83.0]
|
62.0 (64.4) [50.1–73.9]
|
4.4
|
58.6 (77.7) [44.5–72.7]
|
7.8
|
57.3 (66.6) [46.4–68.1]
|
9.2
|
Abbreviations: CI, confidence interval; SD, standard deviation.
a
p ≤ 0.01.
b
p ≤ 0.05.
In years 2 and 3 postintervention, the percentage of telemetry orders actively discontinued
prior to discharge continued to be higher than preintervention levels overall (pre:
63.4%, 1 year post: 78.7%, 2 years post: 79.7%, 3 years post: 79.8%) and for hospitalist
and resident services at HMC ([Table 1]). At UWMC, the percentage of active order discontinuation remained higher than baseline
in years 2 and 3 after intervention overall (pre: 64.1%, 1 year post: 77.4%, 2 years
post 73.7%, 3 years post 75.8%) and among resident teams; the percent increase was
highest in the first year after intervention. Among hospitalists, there was greater
variability in years 2 and 3 after intervention. An improved lower average duration
of telemetry episodes was sustained in years 2 and 3 compared with preintervention
baselines at both sites on all teams ([Table 2]).
At both sites, rates of active discontinuation of telemetry orders and decreased telemetry
duration trended toward improvement, although there was significant month-to-month
variation in practice ([Fig. 2]).
Fig. 2 Telemetry ordering practices by month for all medicine services by hospital (site
1 = HMC, site 2 = UWMC). (A) A greater percentage of telemetry orders was discontinued before hospital discharge
after the EHR intervention but there was significant month-to-month variation at both
hospitals. (B) Trend of average hours of telemetry use shows a decrease in average hours of use
over time at both hospitals with significant month-to-month variation. EHR, electronic
health record; HMC, Harborview Medical Center; UWMC, University of Washington Medical
Center.
At HMC where telemetry technicians documented telemetry findings directly in the EHR,
10 surveys were completed. Overall, technicians were very satisfied with this initiative.
In total, 89% agreed/strongly agreed that the initiatives improved interdisciplinary
team communication and 88% agreed that increased teamwork improved their job satisfaction.
One technician stated, “I feel like telemetry technicians are communicating with doctors
and nurses to improve patient care.”
Discussion
Harnessing the EHR to support guideline-directed telemetry ordering improved telemetry
utilization on acute care medicine services at two academic referral hospitals in
our health system with fewer telemetry orders despite increased medicine admissions,
increased active discontinuation of telemetry orders prior to discharge, and decreased
average duration of telemetry. Impact was greatest on resident services although hospitalist
ordering practices also showed some improvements. Improvements were sustained over
time.
One strength of this intervention was employing the EHR to assist in clinical decision-making
in real time. Formal education on guideline-directed telemetry use is often absent
or lacking in residency programs and medical schools. Harnessing capabilities built
into the EHR to support guideline-directed ordering and actively discontinuation of
telemetry not only provides a persistent effect without the need for specific training,
but also does so at minimal cost.
Of the three arms of our intervention, the direct page to the patient's primary physician
recommending discontinuation of telemetry unless a new indication existed was felt
to be the most impactful. In a cluster-randomized clinical trial, Najafi and colleagues
demonstrated that a targeted EHR alert or “pop-up” dialog box as a single-component
intervention significantly reduced telemetry monitoring duration by 8.7 hours per
hospitalization on an academic general medicine service.[12] These findings were similar to improvements seen in our study on the hospitalist
services; however, we saw greater improvements with average decrease per hospitalization
of 16 to 17 hours on medicine resident services that were sustained in year 2 after
intervention. Year 3 performance continued to show an improvement over baseline. Our
study is unique in that we used a text page to engage the primary contact provider
and not a pop-up alert. Text pages are a routine method of active inpatient communication.
In complex academic medical centers with medicine patients bedded in multiple units,
the direct page is an active message that supports clinical decision-making in real
time and that reaches providers regardless of where they are in the hospital. Studies
have shown that pop-up alerts also lead to alert fatigue and may be dismissed given
their overuse.[14] Other studies have shown that multicomponent interventions including education,
process change, routine feedback, and financial incentives decrease telemetry utilization.[7] As in the Najafi et al study, our intervention was not significantly resource-intensive
and only involved modifications to the EHR. Directly engaging the primary provider
for the patient to consider discontinuation of telemetry orders also supported active-provider
decision-making for patients whose telemetry order exceeded the standard duration
for a specific indication. Studies have shown that automatic discontinuation of telemetry
also decreases telemetry utilization.[10]
[11] However, this approach requires nurses to contact physicians if discontinuation
is believed to be unsafe according to an algorithm. In our intervention, the provider
can proactively make this decision which in turn supports clinical decision-making
as well as resident learning in our academic centers. This intervention may be particularly
effective at academic centers as we noted a greater impact on resident teaching services.
At both hospitals, the resident services had a statistically significant increase
in the amount of telemetry orders discontinued prior to discharge and average duration
of telemetry. This may reflect a lower level of baseline knowledge of guideline-directed
telemetry use among residents and increased reliance on order-set recommendations
and suggestions sent by active page.
We hypothesized that technician entry of telemetry findings directly into the notes
section of the EHR notes would have a significant impact and we observed higher rates
and greater improvements in active discontinuation of telemetry orders prior to discharge
at the site that employed this intervention compared with the site that did not. This
may represent a greater awareness of patients who remained on telemetry as the findings
were in the patients' charts with other clinical information. We did not, however,
see significantly greater decreases in duration of telemetry episodes. Nonetheless,
telemetry technicians were satisfied with the changes and reporting improved intra-team
communication and job experience.
Overall, there were improved practices in years 2 and 3 at both sites relative to
pre-intervention baseline, suggesting that a structural improvement such as an EHR
intervention can have a sustained effect.
Limitations
It is possible that providers, particularly residents, ordered telemetry less often
because they had improved knowledge of when telemetry should be ordered based on the
order-set indications or because they felt the telemetry order set was cumbersome.
Our analysis showed that there was significant month-to-month variation in practice
suggesting that additional unmeasured factors, such as telemetry indication, differences
in patient population, or monthly census variation that we could not account for,
may have contributed to changed practice patterns. Nonetheless our interventions were
implemented in a real-world setting and the total telemetry usage on acute care medicine
was lower. Since we included only initial telemetry orders, our data are biased against
those situations in which telemetry was restarted. We were not able to capture any
adverse impacts of earlier discontinuation of telemetry monitoring although there
were no incident reports filed at either site related to earlier telemetry discontinuation
and no code blues. We did not collect readmission information for medicine patients
whose telemetry orders were included in this review; however, overall medicine service
readmission rates did not increase over this time period.
Conclusion
Our study showed that a low-cost, multipart, EHR-based intervention including a text
page directly to the responsible provider with no additional education decreased telemetry
usage and that the intervention had more effect on resident services. As many institutions
adopt EHRs, such EHR interventions may support effective use of telemetry in acute
care medicine.
Clinical Relevance Statement
Clinical Relevance Statement
Changing provider behavior is difficult. The EHR system can be harnessed to actively
assist physicians in choosing guideline-directed medical interventions and limiting
unnecessary use. Additionally, innovations using the EHR are often cheaper and less
time-consuming than other interventions.
Multiple Choice Questions
Multiple Choice Questions
-
Disadvantages of cardiac telemetry monitoring include:
-
Prolonged hospitalization.
-
Increased risk of infection.
-
Alarm fatigue.
-
Can only be performed at academic medical centers.
Correct Answer: The correct answer is c. Disadvantages of cardiac telemetry include alarm fatigue,
unnecessary medical costs, and patient discomfort. In and of itself, telemetry is
not known to prolong hospitalization or cause infections, and it is used in both community
and academic medical centers.
-
Which of the following changes were made to the University of Washington EHR to help
providers limit unnecessary telemetry use?
-
Pop-up reminder generated by the EHR to consider discontinuing telemetry if no longer
medically necessary.
-
An automatic page through the EHR to discontinue telemetry if no longer medically
necessary.
-
Automatic discontinuation of the telemetry order by the EHR when telemetry use has
exceeded guideline-recommended use.
-
Required daily attestation in the EHR by the provider stating the necessity of telemetry
use.
Correct Answer: The correct answer is b, as described in the Methods section. Choices a, c, and d
were not implemented.
