Evaluation of a Clinical Decision Support Tool to Guide Adoption of the American Heart Association Telemetry Monitoring Practice Standards

Abstract

Background

The objectives of this study were to (1) evaluate telemetry use pre‐ and postimplementation of clinical decision support tools to support American Heart Association practice standards for telemetry monitoring and (2) understand the factors that may contribute to variation of telemetry monitoring in practice.

Methods and Results

First, we captured overall variability in telemetry use pre‐ and postimplementation of the clinical decision support intervention. We then conducted semistructured interviews with telemetry‐ordering providers to identify key barriers and facilitators to adoption. During the study period, 399 physicians met criteria for inclusion and were divided into excessive and nonexcessive orderers. Distribution of telemetry use was bimodal. Among nonexcessive users, 24.4% of patient days were with telemetry compared with 51.6% among excessive users. On average, both excessive (6.1% reduction) and nonexcessive users (2.8% reduction) decreased telemetry use postimplementation, and these reductions were sustained over a 16‐month period. Sixteen interviews were conducted. Physicians believed that the tool was successful because it caused them to more closely consider if telemetry was indicated for each patient. Physicians also voiced frustration with interruptions to their workflow, and some noted that they commonly use telemetry outside of practice standards to monitor patients who were acutely but not critically ill.

Conclusions

Embedding telemetry practice standards into the electronic health record in the form of clinical decision support is effective at reducing excess telemetry use. Although the intervention was well received, there are persistent barriers, such as preexisting views on telemetry and existing workflow habits, that may inhibit higher adoption of standards.

Nonstandard Abbreviations and Acronyms

AHA

American Heart Association

CDS

clinical decision support

CFIR

Consolidated Framework for Implementation Research

Clinical Perspective.

What Is New?

• This study evaluated telemetry monitoring ordering behavior, both quantitatively and qualitatively, after implementing a clinical decision support tool in alignment with telemetry monitoring ordering practice standards.

What Are the Clinical Implications?

• A clinical decision support tool that promotes telemetry monitoring practice standards resulted in a sustained decrease in telemetry monitoring ordering.

• Interviewees commented that the tool helped them think more critically about telemetry monitoring ordering, yet other barriers persist, such as the belief that telemetry monitoring provides a higher level of care.

Continuous cardiac monitoring in the inpatient setting, otherwise known as cardiac telemetry monitoring, allows for the prompt diagnosis and recognition of cardiac arrhythmia in hospitalized patients. ¹ When used in patients who are at high risk for a cardiac‐related event, telemetry monitoring has been shown to provide rapid and life‐saving alerts for clinical deterioration. ² Despite its benefits, overuse of telemetry monitoring has been associated with multiple negative patient outcomes. Prior research has shown that event rates for patients on telemetry monitoring for indications such as low‐risk chest pain may be lower than 3%, ³ , ⁴ and as many as 80% to 99% of alarms in the inpatient setting may be false activations. ⁵ , ⁶ Therefore, many health care clinical staff and providers may become desensitized and experience alarm fatigue, ⁷ which has been shown to directly affect patient outcomes. ¹ , ⁸ , ⁹ Limiting the unnecessary use of cardiac telemetry monitoring may reduce the false alarm burden and improve alarm‐related patient safety. ⁵

Inappropriate use of telemetry monitoring also contributes to increased health care costs without adding benefits to patient care. Based on daily cost estimates for nursing staff and monitoring supplies, the additional cost of 1 day of monitoring is, at a minimum, $53, with an average cost of $82 per patient, per day. ¹⁰ A review of cardiac monitoring practices at a tertiary care hospital in 2018 demonstrated that approximately 24% of telemetry monitoring days were deemed appropriate per American Heart Association (AHA) practice standards, and there were no cardiac code calls that occurred on a day when telemetry monitoring was not indicated. ¹¹ In addition, telemetry monitoring can be a limited resource in many hospitals with standard medical‐surgical beds not having it readily available, which may cause patients who have telemetry monitoring ordered and require admission to board in the emergency department, leading to both overcrowding in the emergency department and opportunity cost in lost revenue for the hospital system. ³ , ¹²

The first scientific statement on inpatient continuous cardiac monitoring by the AHA was issued in 2004. It was established to reduce false alarms and overtreatment, provide guidance for use of telemetry monitoring to prevent or mitigate the impact of cardiac infarcts, and to monitor patients at risk for arrhythmias or changes in ECG intervals. ¹³ These practice standards were updated in 2017 to also address the importance of reducing alarm fatigue and providing recommended ECG monitoring practices by patient population and indication. ¹

Reducing overuse of telemetry monitoring by providing guideline concordant monitoring is key to improving patient and provider experience, quality of care, and also reducing unnecessary health care spending. Therefore, studying provider adoption of AHA telemetry monitoring practice standards and understanding variations in adoption is essential to consider when implementing standards into practice. ¹⁴ , ¹⁵ The objectives of this study were to (1) evaluate physician telemetry monitoring use pre‐ and postimplementation of electronic health record (EHR) clinical decision support (CDS) tools to support practice standards, and (2) understand the factors that may contribute to physician variation of telemetry monitoring use in practice.

METHODS

Setting

M Health Fairview, a 10‐hospital academic health system in Minnesota, identified telemetry monitoring bed capacity as a bottleneck for patient flow, thus affecting patient experience, clinical safety, and cost efficiencies. In the system, there are 12 telemetry monitoring units, each with 25 beds. Three of the units are capable of being continuously monitored by a telemetry technician, and the remainder are transmitted to the nursing station of the medical unit where the bed is located. Typically, patients with cardiac conditions are placed on continuously monitored units.

AHA telemetry monitoring practice standards had not been fully embedded or adhered to within the system, leading to wide variation in what was considered appropriate telemetry monitoring use among hospitals, units, and providers. This was a prevalent issue because, on a monthly basis, the system was placing 2119 inpatient telemetry monitoring orders, resulting in 141 761 patient hours on telemetry monitoring.

Telemetry Monitoring Ordering and Duration Clinical Decision Support Development

CDS tools were embedded in the M Health Fairview EHR, Epic, to promote adherence to AHA telemetry monitoring practice standards for continuous cardiac monitoring (Figure 1), both for initiating telemetry monitoring and for the duration in which telemetry monitoring would be used. System stakeholders, including cardiology, cardiothoracic surgery, and internal medicine leadership, met to condense the AHA standards into a series of broad categories that comprised specific indications with recommended monitoring durations (Table 1). In addition, an open‐response option of “Other” was added that providers could write in an indication (common responses included sepsis, respiratory failure, vital abnormalities, etc). An interruptive alert was also developed (Figure 2) that would appear at the completion of the recommended telemetry monitoring duration. When it would appear, providers would be prompted to reorder cardiac monitoring, if necessary. The CDS was implemented on January 21, 2022, and data collection continued until May 21, 2023, and compared with a 1‐year historical baseline. The University of Minnesota Institutional Review Board determined that, as a quality improvement project, this study did not meet the definition of human subjects research and therefore did not require full review (Study #00014799). The quantitative data that support the findings of this study are available from the corresponding author upon reasonable request. To maintain the confidentiality of interviewees, qualitative data will not be made available.

Figure 1. Screenshot of telemetry clinical decision support tool that required listing of indication.

ACS indicates acute coronary syndrome; AHA, American Heart Association; AMI, acute myocardial infarction; ICU, intensive care unit; NSTEM, non‐ST‐segment–elevation myocardial infarction; and STEMI, ST‐segment–elevation myocardial infarction.

Table 1.

Categorization of Telemetry Monitoring Indications and Durations Used for the Clinical Decision Support Tool Based on the American Heart Association ECG Monitoring Practice Standards

Category	Indication	Duration (h)
Cardiac	Acute MI (non‐ST‐segment–elevation MI/ST‐segment–elevation MI)	48
	Acute decompensated heart failure	48
	Bradycardias	48
	Chest pain/acute coronary syndrome rule out	24
	Infective endocarditis—additional guidance recommending until clinically stable	48
	QTc prolonging medication	48
	Syncope—high cardiac risk	48
	Syncope—low cardiac risk	48
	Tachyarrhythmias, acute	48
Cardiac procedure	Open heart surgery	72
	Postelectrophysiology procedure	48
	Postimplantable cardioverter‐defibrillator or pacemaker placement	48
	Postpercutaneous coronary intervention/percutaneous cardiac intervention	24
	Angiogram	24
	Transcatheter structural interventions	24
Medical	Drug overdose	24
	Electrolyte imbalance—magnesium <1.3 mg/mL; Potassium ≤2.8 or >5.5 mg/mL	24
	Stroke, acute	48
Procedural area	Procedural area	24
ICU	ICU	N/A
Other	Other*	24
Missing/Nonspecified	Nonadherent to indication reporting	N/A

ICU indicates intensive care unit; and MI, myocardial infarction.

^*Common responses included sepsis, respiratory failure, vital abnormalities, etc.

Figure 2. Example of interruptive best practice alert that would display at the end of suggested telemetry duration.

AHA indicates American Heart Association; BPA, best practice alert; and MD, medical doctor.

Objective 1 Methods: Evaluate Physician Variation in Adoption of AHA Telemetry Monitoring Practice Standards

To capture physician variation in telemetry monitoring use, physicians most likely responsible for a patient on a given day were algorithmically determined. The physician identification algorithm used EHR metadata, including structured data from daily notes, work type defined by Current Procedural Terminology codes, physician specialty, and hospital and unit identification. The algorithm included tiered prioritization for each day: (1) the admission or discharge note author; (2) Current Procedural Terminology codes; and (3) author's progress note. Within each tier, subpriorities were included that prioritized intensive care unit (ICU) physicians while also excluding physician specialties that are not primary providers throughout the health system. Fifty randomly selected charts were validated before finding 96% sampling accuracy. This approach was more accurate than assigned provider, admission provider, and discharging provider.

To calculate excess telemetry monitoring days for each physician, we took a 2‐step process. First, for each physician patient‐day we determined if telemetry was ordered and not discontinued. Next, we determined if that telemetry day fell within or outside AHA guidelines as dictated by the CDS. We then summed total number of patient days for each physician, total number of telemetry days, and total number of excess telemetry days. This allowed stratification of physicians by proportion of total patient days telemetry monitoring was ordered, and proportion of days telemetry monitoring was used outside of standards. Excess telemetry monitoring rate is the proportion of days with excess telemetry monitoring divided by the total number of hospital days for each physician. Patients in the ICU under the care of the critical care team were excluded from analysis.

To be included in this study, a physician required at least 30 patient‐days (number of days they were identified as the primary inpatient physician) pre‐ and postintervention, 10 telemetry monitoring patients pre‐ and postintervention, and 7 new telemetry monitoring orders after the intervention had been implemented. Anesthesiology, emergency department, and critical care physicians were excluded, as they use a different ordering system for telemetry monitoring.

To ensure physicians were sampled across locations, hospitals were clustered into 3 sampling groups based on patient volume. For each group, median excess telemetry monitoring use was calculated. Physicians were then dichotomized into excess or nonexcess users based on whether their use was above or below the median. For physicians who worked at more than 1 hospital, the hospital for which they had the most patient‐days was assigned.

Statistical Analysis

To describe physician variation in telemetry monitoring ordering, we dichotomized the population into excess and nonexcess users. Continuous covariates were summarized by the sample mean and SD, and categorical covariates were summarized by counts and the sample proportion. Between group comparisons were made by chi‐square and Mann–Whitney U test where appropriate. Finally, to demonstrate durability of each population, we plotted the proportion of total and excess telemetry use following interventions against a 1‐year historical benchmark. We used the modified Wilson method to estimate the 95% CIs for each month. ¹⁶ , ¹⁷ Data processing of raw EHR data and statistical analysis was performed in STATA (v17.0 Statacorp) and Prism (v7, Graphpad) was used to visualize summary data.

Objective 2 Methods: Understand the Factors That May Contribute to Physician Variation Ordering Telemetry Monitoring

Conceptual Framework

It has been widely cited that it can take 17 to 20 years for evidence‐based practices to be successfully implemented into routine practice. ¹⁸ To address this, implementation science is a growing discipline that examines the methods and strategies necessary to promote the systematic uptake of interventions into practice. ¹⁹ A widely used framework within implementation science is the Consolidated Framework for Implementation Research (CFIR). ²⁰ The CFIR is a determinant framework that outlines factors that act as barriers and facilitators that influence implementation uptake and outcomes and was recently updated in 2022. ²¹ , ²² The framework is composed of 5 domains—innovation, outer setting, inner setting, individuals, and implementation process—with several constructs within each domain that may impact successful implementation (Table 2). ⁵ , ¹⁹ The innovation domain encompasses factors related to what is being implemented (in this case, the telemetry CDS), the outer setting are external factors (eg, policy, national quality measures) affecting implementation, the inner setting are factors associated with the setting in which the innovation is being implemented (eg, health system, hospital), individuals are the roles and characteristics of the people involved in implementing the innovation (eg, leadership, care team members), and implementation processes are the activities and strategies used to implement the innovation (eg, workflows, providing performance feedback). The updated CFIR served as the conceptual framework for developing qualitative interview questions (Data S1) and completing data analysis.

Table 2.

Updated Consolidated Framework for Implementation Research ¹⁹

Domain	Innovation	Outer setting	Inner setting	Individuals	Implementation process
Constructs	Source Evidence‐base Relative advantage Adaptability Trialability Complexity Design Cost	Critical incidents Local attitudes Local conditions Partnerships and connections Policies and laws Financing External pressure*	Structural characteristics* Relational connections Communications Culture* Tension for change Compatibility Relative priority Incentive systems Mission alignment Available resources* Access to knowledge and information	Roles High‐level leader Midlevel leader Opinion leaders Implementation leads Implementation team members Other implementation support Innovation deliverers Innovation recipients Characteristics Need Capability Opportunity Motivation	Teaming Assessing needs* Assessing context Planning Tailoring strategies Engaging* Doing Reflecting and evaluating* Adapting

^*Additional subconstructs exist.

Interviewee Selection

To identify participants for qualitative interviews, it was important to select from physicians that had sufficient experience using the CDS tool so that they could adequately speak to any barriers and facilitators it presented. Therefore, the same inclusion criteria that were used to assess physician variation were also applied to identify potential interviewees (at least 30 patient‐days and 10 telemetry monitoring patients pre‐/postintervention as well as at least 7 new telemetry monitoring orders after the intervention had been implemented).

In addition, to understand if there were any differences between physicians who were using telemetry monitoring in excess, according to AHA practice standards, and those who were within monitoring duration standards, physicians from both groups were sought out to understand if there were any differences between the 2 groups in how they viewed telemetry monitoring along with the ordering CDS and monitoring duration alert. To identify these groups, using the dichotomized approach described previously, 10 physicians were randomly selected who were excessive and 10 who were nonexcessive users from each hospital group for a total of 60 physicians. This method of identifying primary inpatient physicians was determined to have 96% accuracy on manual review of 200 charts during its optimization. For this cohort, the 60 physicians were manually reviewed and 1 physician was eliminated. As a result, the list of potential interviewees was made up of 59 physicians.

Data Collection

The 59 identified physicians were sent an email requesting their participation in a phone interview to discuss their perceptions of the new telemetry monitoring ordering process. Through this approach, 16 agreed to participate in an interview (10 excess users and 6 nonexcess users). Although there were unequal numbers of physicians in the groups, the goal of qualitative research is to gather various opinions until saturation, the point in qualitative research where no new codes or information emerge, indicating that sufficient interviews have been completed. ²³ The number of participants that agreed to participate was felt to be enough to achieve saturation. Interviews were carried out by 4 members of the research team trained in qualitative interviewing. All interviews occurred via Zoom or phone and were recorded with permission and transcribed verbatim. Because this was deemed nonhuman subjects research, written consent was not necessary.

Data Analysis

All transcripts were uploaded and analyzed in the qualitative software, NVivo. A member of the research team read through transcripts as they became available and inductively coded the data by identifying recurring emergent concepts through initial coding. Initial coding is a coding method where qualitative data are segmented into discrete parts and then examined and compared for similarities and differences to develop code names and definitions. ²⁴ Codes were then mapped to the most appropriate CFIR domain to create an initial codebook. Another member of the research team reviewed 4 of the 16 transcripts along with the draft codebook. The 2 researchers met to discuss code names, any possible additional codes, and the deletion of any codes to finalize the codebook. The finalized codes were then applied to all transcripts. As an additional validity check, another member of the research team reviewed all the coding that was applied to the CFIR domain of “inner setting” to ensure codes were accurately defined and attributed.

RESULTS

Objective 1: Evaluate Physician Variation in Adoption of AHA Telemetry Monitoring Practice Standards

During the study period, 399 physicians met criteria for inclusion and were divided into excessive and nonexcessive users of telemetry monitoring (Table 3). This covered over 134 000 patient days preimplementation and 152 000 patient days postimplementation of the CDS. Distribution of telemetry monitoring is illustrated in Figure 3. Among nonexcessive users, 24.4% of patient days were with telemetry monitoring compared with 51.6% among excessive users. Although cardiologists were identified more commonly among excessive users, hospitalists were as well. Excessive users also had significantly higher total patient volume than nonexcessive users, which may be related to the fact that hospitalists are overrepresented in excessive users.

Table 3.

Characteristics of Telemetry Use Among Nonexcess and Excess Users

	No.	Nonexcess user	Excess user	P value
		199	200
Subspecialty	Hospitalist (n, %)	109 (54.8%)	132 (66%)	<0.001
	Cardiology	2 (1.0%)	35 (15.2%)	<0.001
	Surgery	31 (15.6%)	10 (4.3%)	<0.001
	Other	57 (28.6%)	23 (11.5%)	<0.001
Preintervention	Patient days, total (mean)	51 160 (257)	82 850 (413)	0.003
	Telemetry days, total (mean)	13 323 (66.9)	38 601 (193)	<0.001
	Telemetry rate, mean	24.40%	51.60%	<0.001
Postintervention	Patient days	59 491 (299)	93 394 (467)	0.001
	Telemetry days	13 052 (65.6)	37 714 (189)	<0.001
	Telemetry rate	21.50%	45.30%	<0.001
	Excess telemetry days	830 (4.2)	4302 (21.5)	<0.001
	Net change	−2.80%	−6.10%	<0.001

Figure 3. Distribution of telemetry monitoring.

 

On average, both excessive (6.1% reduction) and nonexcessive users (2.8% reduction) decreased telemetry monitoring use postimplementation, and these reductions were sustained over a 16‐month period (Figure 4). Telemetry monitoring use in excess of AHA standards continued to decrease after implementation among excess users (Figure 5) but not among nonexcessive users. Postimplementation, 10.1% of all telemetry monitoring use remained outside of AHA practice standards.

Figure 4. Telemetry monitoring use postimplementation among excess and nonexcess users.

 

Figure 5. Telemetry monitoring use in excess of AHA standards among excessive users and nonexcessive users following the intervention.

AHA indicates American Heart Association.

Objective 2: Understand the Factors That May Contribute to Physician Variation Ordering Telemetry Monitoring

Participants' attitudes and reflections toward the implementation of the telemetry monitoring ordering CDS and telemetry duration alert occurred across 3 different CFIR domains: innovation, inner setting, and individuals, and there were no major differences between excess and nonexcess usage groups. The following is a description of the salient codes that occurred within each domain. Full mapping of the codes to the CFIR is available in Table S1.

Innovation Domain

According to the CFIR, the innovation domain includes barriers and facilitators related to the program or initiative being implemented. Participants spoke specifically about the design of the ordering CDS and monitoring duration alert, as well as the advantages it brought to care delivery and resource use. Their perceptions are reflected in the following codes.

Telemetry Monitoring CDS

There were varying opinions about the indications that were offered in the telemetry monitoring order set—some thought there were too many options to choose from whereas others felt more could be added. However, it was commented that having the “other” box was helpful for indications that fall outside of the AHA standards, such as sepsis or alcohol withdrawal. Also, 2 interviewees said that having the list of indications to choose from provided a litmus test of whether telemetry monitoring was really necessary (ie, if the indication was not on the list, telemetry monitoring likely was not necessary), as 1 physician noted,

Let's say I want telemetry for a reason and I look at [the CDS] and it's not one of the standard reasons and I have to use that other tab, it makes me evaluate whether or not I really, really want to use it.—Physician 2 (Nonexcessive user)

Telemetry Monitoring Duration Alert

The general sentiment was that the monitoring duration alerts were appropriate and helpful. However, some expressed that monitoring durations should be increased for some conditions (eg, stroke) and that some indications should not have a duration at all (eg, acute myocardial infarction). For example, 1 physician said,

I do question the primary cardiac admission diagnoses having a limit on telemetry. That doesn't make a lot of sense to me, clinically.—Physician 10 (Excessive user)

For indications that require a longer monitoring duration, it was mentioned that the continued need to reorder telemetry monitoring was frustrating.

Gray Areas

Participants mentioned several gray areas where they felt the practice standards did not fit well. For example, it was brought up that patients may have multiple indications during their stay, which complicates selecting a single indication for telemetry monitoring. Also, within the system there are intermediate care units that have cardiac monitoring capabilities. It was mentioned that there was internal professional debate on how the telemetry monitoring initiative should be used for these patients. One interviewee expressed desire for more direction on ordering telemetry monitoring for this population:

If you look at an IMC [intermediate care] patient in intermediate care…I have a lot of providers I encounter who believe all those patients should be on tele and nurses too. Then there's those who don't. That's a huge controversial point. I think we, as a system, need to either educate not to use it there or offer a button on that cardiac monitoring order for IMC, just because I think we get a lot of wildly inappropriate, goofy ‘other’ indications typed in because of that particular class of patient. —Physician 13 (Excessive user)

Suggestions for Improvement

Physicians brought up a number of frustrations or areas for improvement for the new telemetry monitoring order system. For example, the current alert on the duration of telemetry monitoring is set to trigger whenever the indication selected has reached the recommended duration. The alert fires during daytime hours (8:00–22:00) when a prescriber opens the chart; however, 1 interviewee suggested having the alert fire no more than once a day. Rather than having the indications grouped under categories in the order set, 1 physician suggested just having a list of indications because that is the first thing that comes to mind when ordering telemetry monitoring. Because it is not a time‐sensitive alert, to minimize alert fatigue, some participants suggested having a separate area in the chart where these types of alerts could be placed rather than it occurring as a pop‐up. Additionally, 1 physician suggested that the monitoring duration alert be included in the transfer order when a patient is transferred between floors:

A lot of times what happens, someone will be admitted to a higher level of care, like the ICU [intensive care unit], or our step‐down unit. Those have more capability to do cardiac telemetry. When someone is transferring floors, I think we would decrease overuse if there was something tied to that transfer floor order. Someone's going from the ICU to general medicine, maybe, the alert will fire at some point so the floor team will remember to discontinue cardiac telemetry. Potentially, when being transferred, if telemetry is no longer needed, that could be incorporated in that transfer order.—Physician 12 (Excessive user)

Lastly, a couple of interviewees mentioned that the alert was not intuitive, because rather than providing an option to discontinue telemetry monitoring within the alert, one has to close the alert and go to the orders to discontinue telemetry monitoring.

Benefits the Intervention Has Brought

Nearly all participants mentioned the benefits of this initiative compared with the previous standard of practice. Some noted that there has been a noticeable reduction in inappropriate telemetry monitoring use and that this improves quality of care and patient experience while reducing costs. It was also noted that the telemetry monitoring duration alert reminds providers of resource management and helps providers deliver practice standard‐concordant care.

I would say it does change how I manage patients, with respect to whether they need telemetry or not, so I am taking patients off telemetry that I might not normally have done. Just either it forces me to think, ‘Yeah, it's clinically unlikely they're going to have a dysrhythmia now at this point or what have you,’ or I simply just forget about it, because it's just another order buried within all of the other orders that are just sitting there.—Physician 10 (Excessive user)

Lastly, 1 physician added that the telemetry monitoring initiative helps them stay up to date with best practices while another interviewee brought up that the telemetry monitoring duration alert also provides a teaching moment for those working on residency teams.

Inner Setting Domain

The inner setting is composed of the components within the environment (eg, hospital, system) in which the innovation is implemented. Within this domain, interviewees discussed the challenges of existing system culture around telemetry monitoring, the need for change, and the impact of technological innovations, such as CDS of various types.

Breaking Old System Habits

A number of system norms were mentioned among interviewees that may inhibit appropriate telemetry monitoring use. For example, there were recent system mergers and 1 interviewee mentioned that providers that had been in a different system were still getting accustomed to the telemetry monitoring order sets used by M Health Fairview. In addition, with COVID‐19 and capacity limits, patients may sometimes be placed on a cardiac floor even though they may not have a cardiac issue. However, the norm is that everyone on the cardiac floor receives telemetry monitoring, so there are some patients on the cardiac floor that receive telemetry monitoring unnecessarily. Lastly, 1 physician discussed that previously there were not sufficient pulse oximeters, which led to care team members using telemetry monitoring instead.

Having pulse‐ox since COVID has really helped because a lot of times people used a ton of tele for COPD and pneumonia because we didn't have a pulse‐ox. —Physician 15 (Excessive user)

Now that pulse oximeters are in sufficient quantity, it has still been a difficult habit for team members to no longer use telemetry monitoring.

Existing Attitudes and Beliefs About Telemetry Monitoring

Several interviewees mentioned some of the existing care team beliefs that may contribute to telemetry monitoring overuse. Many physicians discussed how easy it is to forget telemetry monitoring is being used once the initial order is placed,

Once you order it, you stop thinking about it to some degree, just like a vital signs order, Q4‐hour vital signs. You have it there, and then you sort of stop thinking about it—Physician 10 (Excessive user)

In addition, 1 physician mentioned how orders are often not “cleaned up” when patients are transferred from 1 unit to another and the way orders are sorted in the EHR may contribute to not discontinuing telemetry monitoring sooner. It was also mentioned that telemetry monitoring can provide a safety net if you are unsure what is happening clinically, for example, and that it provides an additional monitoring point if something were to go wrong. One physician stated,

I do like it as a higher level of care. Meaning I want this patient looked at a little more often. I want an alarm to go off if something's going wrong. Kind of the same way I use continuous pulse ox, because I just want a closer eye on that patient. And if we have them hooked up to something that'll ding an alert when something's going wrong, that's really why I choose to put it on there.—Physician 1 (Excessive user)

Support for System‐Wide Adoption of AHA Practice Standards

When discussing having system‐wide adoption of AHA telemetry monitoring practice standards, some interviewees expressed support of this, whereas others were more apathetic. It was noted that having national practice standards integrated into the EHR would facilitate providing a consistent standard of care and that because it was a practice standard and not a policy, this would lead to better receptivity among physicians. It was also stressed that it be understood that there would be occasions when there are exceptions to the standards.

Interruptive Alerts for Telemetry Monitoring Duration and Impact on Workflows

Four physicians discussed how the introduction of behavioral nudges through the EHR, such as the telemetry monitoring duration alert, affects their behavior and workflow. Overall, they felt these tools were disruptive to workflow, as 1 physician stated:

When people come up with new ideas to improve the EHR, they add these notifications and over time, it just disrupts your day more and more and more. So I can log in and I'll get some notification about guardianship or get a notification about medications that haven't been reconciled. And then I click on orders and I want to put in a quick order, but then I get one or two notifications about orders that are out of date or that need to be restarted. So it just keeps adding up, and I'm having trouble just… I just think it's too much bother really to go through all of them, because sometimes you just want to get one thing done and then they're pulling you in different directions.—Physician 14 (Non‐excessive user)

Another physician commented that if they cannot figure out an alert within a few seconds, they will click whatever they can to make it disappear. On the other hand, despite being disruptive, another interviewee described alerts as being necessary to reevaluate clinical needs.

Individuals Domain

This domain consists of the characteristics of the individuals involved in the implementation and the effect this can have on the success of the intervention.

Provider Adoption and Variation of Telemetry Monitoring Initiative

Nine participants talked about the various approaches they have seen to using the ordering CDS and monitoring duration alert, along with their own approach. For example, 1 interviewee said,

I will say there is still a wide range in what I see it being used for. And sometimes, again, where I'm currently at we have tele doctors that are covering our overnights. Sometimes they will order it inappropriately and do it intentionally just because they don't want to deal with it. They'll say it is for a tachyarrhythmia even though the patient has no evidence of that or concern for it. Different things like that. They just want telemetry and don't really care how they get it.—Physician 2 (Nonexcessive user)

Other physicians discussed not engaging with the alerts and clicking past it because sometimes it appears when they are starting a shift and accomplishing other tasks. It was also mentioned that variation in use may be due to stylistic or personal preferences. In addition, it was brought up that providers feel that an ordering CDS or monitoring duration alert decreases autonomy, which leads to dissatisfaction. To address this, 1 physician suggested eliminating the telemetry monitoring duration alert for cardiac patients to limit provider dissatisfaction with the alert.

DISCUSSION

The purpose of this study was 2‐fold; first, we wanted to understand physician variation after the introduction of an ordering CDS and monitoring duration alert to align with AHA telemetry monitoring practice standards. Second, we wanted to understand factors that may contribute to physician adoption of AHA telemetry monitoring standards by interviewing excess and nonexcess telemetry monitoring users. Our results found that there was clear variation in ordering telemetry monitoring beyond the recommended duration outlined in the AHA practice standards, but that excess use decreased following the intervention and continued to decrease among excess users. In addition, both excess and nonexcess users of telemetry monitoring held similar opinions toward telemetry monitoring and the ordering CDS and monitoring duration alert. The qualitative data illustrated that the initiative was well received, in general, among both groups, yet both excess users and nonexcess users provided suggestions for improvements and discussed system‐ and provider‐level barriers that may inhibit better adherence.

Other studies in the field have tested different strategies for reducing excess telemetry monitoring use with varying degrees of success. For example, interventions relying on huddles, educational approaches, and weekly feedback have not been shown to be effective. ²⁵ , ²⁶ On the other hand, 1 study showed that when providers were required to include an indication when ordering telemetry monitoring, this produced a noticeable decrease in excess telemetry monitoring use. ²⁵ Similarly, a study that also implemented a ordering CDS and monitoring duration alert demonstrated a roughly 20% decrease in telemetry monitoring hours per patient encounter. ²⁷ This study adds to the literature because it describes physician behavior, as well as highlights and describes some of the contextual factors for why some implementation strategies may be more effective than others. For example, the qualitative portion of this study demonstrated that when a physician is required to provide an indication for telemetry monitoring, this causes them to reflect and consider if telemetry monitoring is really warranted, thereby decreasing potentially unnecessary telemetry monitoring use. At the same time, it was noted that alerts are disruptive to workflow, which may limit engagement among providers.

The latest AHA telemetry monitoring practice standards list “implementation of practice standards” as a priority area for further research. Although measures, such as cardiac outcomes, length of stay, mortality, etc, demonstrate the effectiveness of an intervention, other areas, such as provider adoption, help to shed light on the effectiveness of the implementation. ¹⁴ Using formative evaluation and an implementation science framework, this study illustrated that some physicians continue to believe that having telemetry monitoring offers a higher level of care. There were also current and former institutional workflows in place that have become habitual and, therefore, difficult to break even with an ordering CDS and monitoring duration alert. Understanding these barriers are key to guiding further quality improvement efforts to reduce excess telemetry monitoring use. For example, education efforts targeted at excessive users and incorporating implementation champions may serve as useful additional implementation strategies to further reduce excess telemetry monitoring use.

One often cited theme in the interviews was a desire to have closer monitoring of patients who physicians were concerned may be at increased risk of clinical deterioration, particularly in “gray areas” of practice, such as patients whose condition is high acuity but not critical. This includes patients in intermediate care or with indications such as “respiratory distress” and “sepsis,” which were commonly entered as “other” in the CDS tool. However, previous studies have demonstrated that decreasing the unnecessary use of telemetry monitoring has not been associated with adverse patient outcomes. ²⁸ It is unclear whether full telemetry monitoring improves responsiveness to instability and is an important future direction for this work. Alternatives to telemetry monitoring include the development of protocols for single lead ECG achieved by wearable devices or continuous heart rate monitoring as a safer and more cost‐effective approach to high‐intensity monitoring among patients at risk for hemodynamic decompensation.

Limitations

There are several limitations to this study that should be considered. First, because providers were not required to include an indication at the time of telemetry monitoring ordering before this project, we cannot compare adherence to AHA practice standards before versus after the introduction of the ordering CDS and duration alert. This is due to a very high degree of missingness of telemetry indication, making excess telemetry calculations unreliable before the intervention. We were additionally unable to separate remote versus monitored telemetry use for their appropriateness. Additionally, telemetry decision‐making relies on patient characteristics as well as provider perceptions. A comprehensive analysis of the effectiveness of the CDS requires an assessment of patient characteristics, which falls outside the scope of this study but is an important additional direction. Second, although other clinicians (eg, nurse practitioners, physician associates) order telemetry, our data capture only the attending on record for the day. Third, this study was cross‐sectional; therefore, it is possible that as physicians became more familiar and comfortable with using the ordering CDS and associated duration alert, their telemetry monitoring ordering practices may have shifted, as well as their perceptions. Fourth, sustainment is an important implementation outcome that should be tracked to determine if more appropriate telemetry monitoring order is maintained or if providers revert to previous ordering patterns. Fifth, 3 out of 5 CFIR domains presented in the interviews with physicians. Themes related to the other domains (outer setting and process) may have occurred if we had interviewed others from the health system, such as leadership or those involved in designing the intervention. Lastly, not all qualitative codes are mutually exclusive. For example, the “suggestions for improvement” code has some overlap with physicians' perceptions of the CDS, as well as the duration alert.

CONCLUSIONS

Telemetry monitoring is a limited and costly resource and, therefore, strategies need to be put in place to limit unnecessary use. This study algorithmically evaluated variation in telemetry monitoring use pre‐ and postimplementation of an EHR‐based CDS intervention to align practice with AHA practice standards. In addition, we examined any potential differences in perceptions of the intervention between those that continued to order telemetry monitoring in excess of AHA telemetry monitoring practice standards and those who did not. Using a mixed‐methods approach, we demonstrated that the intervention reduced telemetry monitoring use across both excessive and nonexcessive users of telemetry monitoring in a sustained manner, but excess telemetry monitoring use persisted. The qualitative component uncovered that, even when stratified by excess or nonexcess use of telemetry monitoring, clinician attitudes toward telemetry monitoring appeared to be similar. Physicians from both groups saw the intervention as beneficial but struggled to apply the standards in “gray areas” and felt that alerts were disruptive to workflow leading to variation in acceptance. This study demonstrates that EHR‐based tools are an effective method for reducing excessive telemetry monitoring use, but that additional implementation strategies may be necessary to overcome continued individual‐ and system‐level barriers. For hospital systems implementing these EHR‐based tools to reduce excessive cardiac telemetry monitoring use, algorithmically stratifying physicians by their adoption of these tools may help identify where barriers to implementation exist and how to best overcome them.

Sources of Funding

This research was supported by the University of Minnesota Center for Learning Health System Sciences, which is a collaboration between the Medical School and School of Public Health. The content is solely the responsibility of the authors.

Disclosures

None.

Supporting information

Data S1

Table S1