Holter Monitors

Number: 0019

Table Of Contents

Policy
Applicable CPT / HCPCS / ICD-10 Codes
Background
References

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Policy

Scope of Policy

This Clinical Policy Bulletin addresses holter monitors. 

1. Medical Necessity

   Aetna considers Holter monitoring medically necessary for diagnostic evaluation of adult members with any of the following symptoms or conditions:

   1. Assessment of efficacy of medications for arrhythmia treatment; or
   2. Assessment of efficacy of surgical interventions for the treatment of arrhythmia; or
   3. Autonomic cardiac neuropathy associated with diabetes mellitus; or
   4. Idiopathic hypertrophic or dilated cardiomyopathy; or
   5. Evaluation of possible or documented long QT syndrome; or
   6. Assessment of the function of pacemakers or implantable cardioverter defibrillators; or
   7. Individuals with pain suggestive of variant (Prinzmetal's) angina; or
   8. Post myocardial infarction with left ventricular dysfunction; or
   9. Evaluation of symptoms related to cardiac arrhythmias (e.g., palpitations, syncope or near syncope, unexplained dizziness); or
   10. Asymptomatic congenital complete atrioventricular (AV) block in pediatric patients.

   Aetna considers Holter monitoring experimental and investigational for all other indications because its effectiveness for indications other than the ones listed above has not been established.

   Holter monitoring is generally considered medically necessary no more frequently than twice in a six month time period. Holter monitoring lasting more than 48 hours is generally considered not medically necessary.  The literature indicates that if more frequent monitoring is needed to evaluate arrhythmias, use of cardiac event recorders should be considered.  See CPB 0073 - Cardiac Event Monitors.

   Note: For Aetna's policy on home-based real-time cardiac surveillance systems (e.g., CardioNet Mobile Outpatient Cardiac Telemetry Service, Cardiac Telecom Telemetry @ Home Service), see CPB 0073 - Cardiac Event Monitors.

2. Experimental and Investigational

   Aetna considers the Empatica E4 Wristband experimental and investigational for ambulatory heart rate variability monitoring because its effectiveness has not been established.

3. Policy Limitations and Exclusions 

   Note: Digitalization and/or color display of results are considered incidental features of Holter monitoring.

   Note: Routine performance of Holter monitoring has no proven benefit for individuals who are undergoing sleep studies for suspected obstructive sleep apnea.

4. Related Policies

   • CPB 0073 - Cardiac Event Monitors

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Table:

CPT Codes / HCPCS Codes / ICD-10 Codes

Code	Code Description
CPT codes covered if selection criteria are met:
93224	External electrocardiographic monitoring up to 48 hours by continuous rhythm recording and storage; includes recording, scanning analysis with report, physician review and interpretation
93225	recording (includes connection, recording, and disconnection)
93226	scanning analysis with report
93227	physician review and interpretation
HCPCS codes not covered for indications listed in the CPB:
Empatica E4 wristband - no specific codes
ICD-10 codes covered if selection criteria are met:
E10.40 - E10.49 E10.610 E11.40 - E11.49 E11.610	Diabetes mellitus with neurological complications
F45.8	Other somatoform disorders
G45.0 - G45.1 G45.8 - G45.9	Transient cerebral ischemic attacks and related syndromes
G99.0	Autonomic neuropathy in diseases classified elsewhere
I20.0 - I20.1 I21.01 - I22.9 I24.0 - I24.9 I25.2	Ischemic heart diseases
I21.A1	Myocardial infarction type 2
I21.A9	Other myocardial infarction type
I42.0 - I42.2 I42.5 I42.8 - I42.9	Cardiomyopathy
I44.0 - I44.7	Atrioventricular and left bundle-branch block
I45.0 - I45.9	Other conduction disorders
I46.2 - I46.9	Cardiac arrest
I47.0 - I47.9	Paroxysmal tachycardia
I48.0 - I48.92	Atrial fibrillation and flutter
I49.01 - I49.9	Other cardiac arrhythmias
I67.841 - I67.848	Cerebral vasospasm and vasoconstriction
Q24.6	Congenital heart block [asymptomatic congenital complete atrioventricular (AV) block in pediatric patients]
R00.1	Bradycardia, unspecified
R00.2	Palpitations
R42	Dizziness and giddiness
R55	Syncope and collapse
Z95.0	Presence of cardiac pacemaker
Z95.810	Presence of automatic (implantable) cardiac defibrillator
ICD-10 codes not covered for indications listed in the CPB:
F51.01 - F51.9	Sleep disorders not due to a substance or known physiological condition [if undergoing sleep studies for suspected obstructive sleep apnea]
G47.00 - G47.39 G47.50 - G47.9	Sleep disorders [if undergoing sleep studies for suspected obstructive sleep apnea]
R06.00 - R06.09 R06.81 R06.83 - R06.89	Dyspnea and other abnormalities of breathing [if undergoing sleep studies for suspected obstructive sleep apnea]

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Background

A Holter monitor is a self-contained ambulatory and recording device used to capture continuous electrocardiographic measurements over a period of 24 to 48 hours.  Holter monitors must be distinguished from ambulatory event monitors, which capture episodic electrocardiographic data over large periods of time, up to 1 month.

Electrodes are placed on the patient's chest and attached to a small recording monitor that the patient carries in a pocket or in a small pouch.  The monitor is battery operated.  A continuous electrocardiogram is recorded on a cassette tape, usually for a 24-hour period, while the patient keeps a diary of activities.  The recording is then analyzed, a report of the heart's activity is tabulated, and irregular heart activity is correlated with the patient's activity at the time.

Advanced Holter monitors have been developed that use digital electrocardiographic recordings, extended memory greater than 24 hours, pacemaker pulse detection and analysis, software for analysis of digital electrocardiographic recordings that are downloaded and stored on a computer, and capability of transmission of results over the internet (e.g., Raytel Medical Corporation, 2004; MIDMARK Diagnostics Group, 2004; Integrated Medical Devices, 2003).

Hegazy and Lotfy (2007) noted that Holter monitoring (HM) has been established as one of the most effective noninvasive clinical tools in the diagnosis, assessment and risk stratification of cardiac patients.  However, studies in the pediatric age group are limited.  These investigators at determined the value of HM in the diagnosis and management of children.  Holter records of 1,319 pediatric patients (54.1 % males and 45.9 % females) were reviewed.  Their average age was 6.7 +/- 4.1 years (5 days to 16 years).  Indications for which Holter monitoring was done were analyzed as well as all the abnormalities diagnosed and factors that may increase Holter yield.  Statistical Package of social science (SPSS) version 9,0 was used for analysis of data.  The most common indications were palpitations (19.8 %), syncope (17.8 %), cardiomyopathy (12.6 %), chest pain (10 %), evaluation of anti-arrhythmic therapy (6.8 %), post-operative assessment (2.6 %) and complete atrio-ventricular (AV) block (2.4 %).  A  total of 141 Holter recordings were found abnormal with a total diagnostic yield of 10.7 %.  The highest contribution to diagnosis was in post-operative assessment (32.4 %) and in cardiomyopathy (19.9 %) where the most common abnormalities were frequent supra-ventricular/ventricular premature beats, supra-ventricular tachycardia (SVT), ventricular tachycardia (VT) and AV block.  Diagnostic yield was low in  patients with palpitations (5.7 %) and syncope (0.4 %).  An abnormal electrocardiography (ECG) was significantly associated with a higher diagnostic yield (p = 0.0001).  None of the children with chest pain had abnormal Holter recordings.  the authors concluded that HM has an extremely valuable role in the assessment of high-risk patients (post-operative and cardiomyopathy).  However in children with palpitations, syncope and chest pain HM has a low-yield.  In this group of patients an abnormal ECG is more likely to be associated with abnormal Holter recordings. 

Weissler-Snir and colleagues (2016) stated that non-sustained ventricular tachycardia (NSVT), defined as greater than or equal to 3 consecutive ventricular beats at greater than or equal to 120 beats/min lasting less than 30 seconds, is an independent predictor of sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC).  Current guidelines recommend 24- to 48-hour Holter monitoring as part of SCD risk stratification.  These investigators evaluated the difference in diagnostic yield of 14-day Holter monitoring compared to 24 to 48 hours for the detection of NSVT and assessed the prevalence and characteristics of NSVT in patients with HC with prolonged monitoring.  They retrospectively analyzed the 14-day Holter monitors of 77 patients with HC from May 2014 to March 2016.  Number of episodes and maximal length and rate on each day were recorded; NSVT was detected in 75.3 % of patients during 14-day Holter monitoring.  The median number of runs was 2 (range of 0 to 26 runs).  The median number of beats of the longest run was 10.5 (range of 3 to 68 beats) with a mean maximum rate of 159.5 ± 20.8.4 beats/min (range of 102 to 203 beats/min).  First episodes of NSVT were detected throughout the 14 days, with only 22.5 % and 44.8 % of the episodes captured within the first 24 and 48 hours of monitoring, respectively.  The authors concluded that prolonged Holter monitoring revealed greater than or equal to 1 episode of NSVT in 75 % of patients with HC of which less than 50 % were detected within the first 48 hours.  Hence, they noted that prolonged Holter monitoring may be superior for SCD risk stratification in HC.  However, the high prevalence of NSVT in this population may limit its utility in evaluating the risk for SCD of the individual patient.

A health technology assessment by Health Quality Ontario (2017) noted that  ambulatory ECG monitors are often used to detect cardiac arrhythmia.  For patients with symptoms, an external cardiac loop recorder will often be recommended.  The improved recording capacity of newer Holter monitors and similar devices, collectively known as long-term continuous ambulatory ECG monitors, suggests that they will perform just as well as, or better than, external loop recorders.  This health technology assessment evaluated the effectiveness, cost-effectiveness, and budget impact of long-term continuous ECG monitors compared with external loop recorders in detecting symptoms of cardiac arrhythmia.  Based on systematic search for studies published up to January 15, 2016, the authors did not identify any studies directly comparing the clinical effectiveness of long-term continuous ECG monitors and external loop recorders.  Thus, they conducted an indirect comparison, using a 24-hour Holter monitor as a common comparator.  They used a meta-regression model to control for bias due to variation in device-wearing time and baseline syncope rate across studies.  The authors conducted a similar systematic search for cost-utility and cost-effectiveness studies comparing the 2 types of devices; none were found.  Finally, they used historical claims data (2006 to 2014) to estimate the future 5-year budget impact in Ontario, Canada, of continued public funding for both types of long-term ambulatory ECG monitors.  The clinical literature search yielded 7,815 non-duplicate citations, of which 12 cohort studies were eligible for indirect comparison; 7 studies examined the effectiveness of long-term continuous monitors and 5 examined external loop recorders.  Both types of devices were more effective than a 24-hour Holter monitor, and the authors found no substantial difference between them in their ability to detect symptoms (risk difference [RD] 0.01; 95 % confidence interval [CI]: -0.18, 0.20).  Using GRADE for network meta-analysis, the authors evaluated the quality of the evidence as low.  The budget impact analysis showed that use of the long-term continuous monitors had grown steadily in Ontario since they became publicly funded in 2006, particularly since 2011 when monitors that can record for 14 days or longer became funded, and the use of external cardiac loop recorders has correspondingly declined.  The analysis suggested that, with these trends, continued public funding of both types of long-term ambulatory ECG testing will result in additional costs ranging from $130,000 to $370,000 per year over the next 5 years.  The authors concluded that although both long-term continuous ambulatory ECG monitors and external cardiac loop recorders were more effective than a 24-hour Holter monitor in detecting symptoms of cardiac arrhythmia, they found no evidence to suggest that these 2 devices differ in effectiveness.  Assuming that the use of long-term continuous monitors will continue to increase in the next 5 years, the public health care system in Ontario can expect to see added costs of $130,000 to $370,000 per year.

Detection of Sleep-Disordered Breathing with Ambulatory Holter Monitoring

Grasso and co-workers (2018) noted that obstructive sleep apnea (OSA) syndrome is a common condition that can impact clinical outcomes among patients with cardiovascular disease.  Screening all subjects with heart disease via polysomnography (PSG) is costly and resource-limited.  In a prospective cohort study, these researchers compared a Holter monitor-based algorithm to detect OSA to in-laboratory attended PSG.  A standard 12-lead Holter monitor was attached to patients at the initiation of PSG.  Holter-derived respiratory disturbance index (HDRDI) was extracted from the respiratory myogram, based on detecting skeletal muscle "noise" detected on the baseline.  Apneic and hypopneic episodes were identified by comparing sudden changes in the myogram to abrupt increases in heart rate.  The HDRDI was compared with the PSG-derived apnea-hypopnea index (PDAHI).  A total of 30 patients underwent simultaneous Holter monitoring and over-night diagnostic PSG.  An ROC curve for peak HDRDI was 0.79 (95 % CI: 0.61 to 0.97) for OSA, with sensitivity of 94.4 % and specificity of 54.5 %.  A cut-off value of HDRDI of less than 10 appeared to identify those individuals without clinically significant sleep-disordered breathing.  The authors concluded that Holter-derived respiration detected OSA comparable to PSG.  Moreover, they stated that further study is needed to determine its utility for screening and diagnosing OSA in appropriately selected patients.

Assessment of Efficacy of Surgical Interventions for the Treatment of Arrhythmia

Davtyan and associates (2018) stated that while several studies have compared the radiofrequency current (RFC) and cryoablation for the treatment of patients with atrial fibrillation (AF), no study has monitored the long-term outcomes with the usage of implantable loop recorders (ILRs).  These investigators enrolled 89 consecutive patients with non-valvular paroxysmal AF (n = 44 for RFC and n = 45 for cryoballoon).  The primary efficacy end-point was the assessment of effectiveness for each group (RFC versus cryoballoon) when examining freedom from arrhythmia by monitoring with ECG, Holter, and ILR.  The primary safety end-point compared rates of adverse events (AEs) between both groups.  The secondary efficacy end-point examined the duration of the post-ablation blanking period from ILR retrieved data.  The mean age of the study population was 56.6 ± 10.2 years, and the follow-up duration was 12 months.  There were no differences in baseline patient characteristics between groups.  At 12 months, the absolute effectiveness (measured by ILR) was 65.9 % in the RFC group and 51.1 % in the cryoballoon group (odds ratio [OR] = 1.85; 95 % CI: 0.79 to 4.35; p = 0.157), and the clinical effectiveness (measured by ECG and Holter) was 81.8 % in the RFC group and 55.6 % in the cryoballoon group (OR = 3.6; 95 % CI: 1.37 to 9.46; p = 0.008).  There was no difference in safety between both groups.  Asymptomatic episodes were significantly more present in the RFC group as measured by ILRs (p < 0.010).  In the cryoballoon group, arrhythmia episodes were recorded equally irrespective of the follow-up method (i.e., ECG and Holter versus ILR (p > 0.010)).  The blanking period did not seem to be as important in cryoballoon as compared to RFC.  The authors concluded that RFC and cryoballoon ablation had similar absolute effectiveness at 12 months; ECG and Holter were effective when assessing the efficacy of the cryoballoon ablation; however, in the RFC group, ILR was necessary to accurately assess long-term efficacy. 

Risk Stratification of Sudden Death and Cardiovascular Outcomes in Individuals with Type 1 Myotonic Dystrophy

Cardiac conduction disturbances and tachyarrhythmias occur in type 1 myotonic dystrophy, and to a lesser extent in type 2 myotonic dystrophy. Guidelines from the American Heart Association recommend ambulatory ECG at the time of diagnosis, regardless of symptoms (Feingold, et al., 2017). Patients with a normal left ventricular ejection fraction should receive annual ambulatory ECG monitoring.

Gamet and colleagues (2019) noted that prognosis of patient with type 1 myotonic dystrophy (DM1) is very poor.  Annual 24-hour Holter ECG monitoring is recommended but its relevance is debated.  In a retrospective study, these researchers examined if Holter ECG parameters could predict global death in DM1 patients and evaluated whether they could predict cardiovascular events and sudden cardiac death, comparing DM1 patients and healthy controls, and assessed their evolution in DM1 over a 5-year period.  This trial included genetically confirmed DM1.  Primary end-point was global death; secondary end-points were labeled "sudden cardiac death", which was a composite of sudden cardiac death, aborted sudden cardiac death, implantable cardioverter defibrillator therapy, sustained ventricular tachycardia, atrio-ventricular (AV) block grade 3, pause greater than 3 seconds; and "cardiovascular events", which was a composite of all-cause mortality, pacemaker or cardioverter defibrillator implantation, sustained ventricular tachycardia, supra-ventricular tachycardia, hospitalization for acute cardiac cause and heart failure.  A total of 47 patients (22 women, 40 ± 13 years old) were included; 3 (7 %) DM1 patients died, 9 (19 %) experienced "sudden cardiac death" end-point, and 21 (45 %) experienced "cardiovascular event" end-point during mean follow-up of 95 ± 22 months.  None of Holter ECG parameters was discriminant to predict death or secondary end-points.  Compared to healthy controls, DM1 patients had higher standard deviation of all normal-to-normal RR intervals (SDNN) and low-frequency/high-frequency (LF/HF) ratio.  Finally, heart rate variability parameters remained stable over a mean interval of 61 ± 15 months excepting pNN50, which decreased significantly.  The authors concluded that these findings suggested that annually-repeated Holter ECG in DM1 was not useful for stratifying risk of sudden death and cardiovascular outcomes.

Empatica E4 Wristband for Ambulatory Heart Rate Variability Monitoring

Menghini et al (2019) noted that wearable sensors are promising instruments for conducting both laboratory and ambulatory research in psychophysiology; however, researchers should be aware of their measurement error and the conditions in which accuracy is achieved.  These investigators examined the accuracy of a wearable sensor designed for research purposes, the E4 wristband, in measuring heart rate (HR), heart rate variability (HRV), and skin conductance (SC) over 5 laboratory conditions widely used in stress reactivity research (seated rest, paced breathing, orthostatic, Stroop, speech task) and 2 ecological conditions (slow walking, keyboard typing).  A total of 40 healthy participants concurrently wore the wristband and 2 gold standard measurement systems (i.e., electrocardiography and finger SC sensor).  The wristband accuracy was determined by examining the signal quality and the correlations with the Bland-Altman plots against gold standard-derived measurements.  Moreover, exploratory analyses were carried out to evaluate predictors of measurement error.  Mean HR measures showed the best accuracy over all conditions.  HRV measures showed satisfactory accuracy in seated rest, paced breathing, and recovery conditions but not in dynamic conditions, including speaking.  Accuracy was diminished by wrist movements, cognitive and emotional stress, non-stationarity, and larger wrist circumferences.  The authors concluded that wrist SC measures showed neither correlation nor visual resemblance with finger SC signal, suggesting that the 2 sites may reflect different phenomena.  These researchers stated that future studies are needed to evaluate the responsivity of wrist SC to emotional and cognitive stress.

The authors stated that this study had several drawbacks.  First, the sample size was not established via a power analysis but by qualitatively comparing sample sizes and CIs reported in previous studies.  Second, only measurement accuracy and not precision (which is a necessary condition for accuracy) was assessed; thus, future studies examining the E4 reliability via test‐retest designs are needed.  Third, the cut-off values for limits of agreement (LOA) acceptance were based on arbitrary criteria depending on ECG measures, as used in previous studies.  These researchers were unaware of published reference values for HR, HRV, or SC measurement error, and alternative approaches might be used depending on the field of application.  Fourth, the accuracy of reactivity values (i.e., changes from baseline) was not assessed.  Reactivity values were expected to be unaffected by systematic bias in the measured signals, leading to better accuracy.  However, as this trial focused on the absolute agreement between the 2 methods, this protocol did not include baseline phases, and the order of conditions was neither randomized nor counterbalanced.  Fifth, since these investigators focused on short‐term intervals, these findings may not be generalizable to long‐lasting recordings.

Schuurmans et al (2020) stated that wearable monitoring devices are an innovative way to measure HR and HRV, however, there is still debate regarding the validity of these wearables.  These investigators attempted to validate the accuracy and predictive value of the Empatica E4 wristband against the VU University Ambulatory Monitoring System (VU-AMS) in a clinical population of traumatized adolescents in residential care.  A sample of 345 recordings of both the Empatica E4 wristband and the VU-AMS was derived from a feasibility study that included 15 participants.  They wore both devices during 2 experimental testing and 12 intervention sessions.  These researchers used correlations, cross-correlations, Mann-Whitney tests, difference factors, Bland-Altman plots, and Limits of Agreement to examine differences in outcomes between devices.  Significant correlations were found between Empatica E4 and VU-AMS recordings for HR, standard deviation of the normal-to- normal interval (SDNN), root mean squared differences of successive difference of intervals (RMSSD), and high frequency (HF) recordings.  There was a significant difference between the devices for all parameters but HR, although effect sizes were small for SDNN, low frequency (LF), and HF.  For all parameters but RMSSD, testing outcomes of the 2 devices led to the same conclusions regarding significance.  The authors concluded that the Empatica E4 wristband provided a new opportunity to measure HRV in an unobtrusive way.  Results of this study indicated the potential of the Empatica E4 as a practical and valid tool for research on HR and HRV under non-movement conditions.  Moreover, these researchers stated that while more research needs to be conducted, this study could be considered as a 1st step to support the use of HRV recordings provided by wearables.

Van Voorhees et al (2022) noted that HRV is a useful index of psychological and physiological stress.  Although several wristband devices have purported to measure HRV, none has demonstrated reliability when compared with the criterion-standard Holter monitor.  These researchers examined the reliability of HRV readings from the Empatica E4 wristband compared with a Holter monitor over a 24-hour period of simultaneous monitoring.  Agreement between the monitors was evaluated by examining correlations and intra-class correlations (ICCs) for fixed sets in 13 individuals in a treatment trial for post-traumatic stress disorder (4 women; mean [standard deviation] age of 51.92 [6.17] years).  Agreement was calculated at 1-s and 5-min intervals for inter-beat intervals (IBIs) and for 5-min intervals of the root mean square of successive differences between normal heartbeats (RMSSD) and standard deviation of all normal R-R intervals (SDNN).  Agreement across the entire 24-hour observation period was also measured.  Frequency-domain measures of HRV could not be calculated because of too much missing data from the E4.  Although high inter-device correlations and ICCs were observed between the E4 and Holter monitors for IBIs at 1-s (median r = 0.88; median ICC = 0.87) and 5-min (median r = 0.94; median ICC = 0.94) intervals, reliabilities for 5-min RMSSD (median r = -0.09; median ICC = -0.05) and 5-min SDNN (median r = 0.48; median ICC = 0.47) were poor.  Agreement between the devices on 24-hour measures of HRV was satisfactory (IBI: r = 0.97, ICC = 0.97; RMSSD: r = 0.77, IBI = 0.76; SDNN: r = 0.92, IBI = 0.89).  The authors concluded that the findings of this study suggested that the low reliability of Empatica E4 as compared with the Holter monitor did not justify its use in ambulatory research for the measurement of HRV over time periods of 5 mins or less.

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References