Ambulatory Electroencephalography

Number: 0425

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 ambulatory electroencephalography.

1. Medical Necessity

   Aetna considers ambulatory electroencephalography (EEG) with or without home video monitoring medically necessary for any of the following conditions, where the member has had a recent (within the past 12 months) neurologic examination and standard EEG studiesFootnote*:

   1. Classification of seizure type in members who have epilepsy (routine EEG is equivocal) – only ictal recordings can reliably be used to classify seizure type (or types) which is important in selecting appropriate anti-epileptic drug therapy; or
   2. Diagnosis of a seizure disorder (epilepsy) – members who have episodes suggestive of epilepsy when history, examination, and routine EEG do not resolve the diagnostic uncertainties (routine EEG should be negative with provocative measures); or
   3. Localization of the epileptogenic region of the brain during pre-surgical evaluation – to identify appropriate surgical candidates.

   Aetna considers the combined use of ambulatory EEG and home-video recording an equally acceptable medically necessary alternative to ambulatory EEG alone.

   Aetna considers ambulatory EEG experimental, investigational, or unproven for all other indications because of insufficient evidence in the peer-reviewed literature.

   Aetna considers implantable sub-scalp, continuous electroencephalography monitoring systems (e.g., Epios, Minder) experimental, investigational, or unproven for the management of epilepsy because of insufficient evidence in the peer-reviewed literature.

   Footnote1*Requirements for a standard EEG and neurological examination is waived for medically necessary continuous EEG performed in an intensive care unit (ICU). 

   Duration of Monitoring

   The goal of ambulatory EEG is usually achieved within 48 hours. Ambulatory EEG monitoring for longer than 7 days may be reviewed for medical necessity.

2. Related Policies

   • CPB 0221 - Quantitative EEG (Brain Mapping)
   • CPB 0289 - Grid Monitoring and Intraoperative Electroencephalography
   • CPB 0322 - Electroencephalographic (EEG) Video Monitoring

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Table:

CPT Codes / HCPCS Codes / ICD-10 Codes

Code	Code Description
CPT codes covered if selection criteria are met:
95700	Electroencephalogram (EEG) continuous recording, with video when performed, setup, patient education, and takedown when performed, administered in person by EEG technologist, minimum of 8 channels
95705	Electroencephalogram (EEG), without video, review of data, technical description by EEG technologist, 2-12 hours; unmonitored
95706	with intermittent monitoring and maintenance
95707	with continuous, real-time monitoring and maintenance
95708	Electroencephalogram (EEG), without video, review of data, technical description by EEG technologist, each increment of 12-26 hours; unmonitored
95709	with intermittent monitoring and maintenance
95710	with continuous, real-time monitoring and maintenance
95711	Electroencephalogram with video (VEEG), review of data, technical description by EEG technologist, 2-12 hours; unmonitored
95712	with intermittent monitoring and maintenance
95713	with continuous monitoring and maintenance
95714	Electroencephalogram with video (VEEG), review of data, technical description by EEG technologist, each increment of 12-26 hours; unmonitored
95715	with intermittent monitoring and maintenance
95716	with continuous, real-time monitoring and maintenance
95717	Electroencephalogram (EEG), continuous recording, physician or other qualified health care professional review of recorded events, analysis of spike and seizure detection, interpretation and report, 2-12 hours of EEG recording; without video
95718	with video (VEEG)
95719	Electroencephalogram (EEG), continuous recording, physician or other qualified health care professional review of recorded events, analysis of spike and seizure detection, each increment of greater than 12 hours, up to 26 hours of EEG recording, interpretation and report after each 24-hour period; without video
95720	with video (VEEG)
95721	Electroencephalogram (EEG), continuous recording, physician or other qualified health care professional review of recorded events, analysis of spike and seizure detection, interpretation, and summary report, complete study; greater than 36 hours, up to 60 hours of EEG recording, without video
95722	greater than 36 hours, up to 60 hours of EEG recording, with video (VEEG)
95723	greater than 60 hours, up to 84 hours of EEG recording, without video
95724	greater than 60 hours, up to 84 hours of EEG recording, with video
95725	greater than 84 hours of EEG recording, without video
95726	greater than 84 hours of EEG recording, with video (VEEG)
CPT codes not covered for indications listed in the CPB:
0956T	Partial craniectomy, channel creation, and tunneling of electrode for sub-scalp implantation of an electrode array, receiver, and telemetry unit for continuous bilateral electroencephalography monitoring system, including imaging guidance
0957T	Revision of sub-scalp implanted electrode array, receiver, and telemetry unit for electrode, when required, including imaging guidance
0958T	Removal of sub-scalp implanted electrode array, receiver, and telemetry unit for continuous bilateral electroencephalography monitoring system, including imaging guidance
0959T	Removal or replacement of magnet from coil assembly that is connected to continuous bilateral electroencephalography monitoring system, including imaging guidance
0960T	Replacement of sub-scalp implanted electrode array, receiver, and telemetry unit with tunneling of electrode for continuous bilateral electroencephalography monitoring system, including imaging guidance
ICD-10 codes covered if selection criteria are met:
G40.001 - G40.919	Epilepsy and recurrent seizures
P90	Convulsions of newborn
R25.0 - R25.9	Abnormal involuntary movements
R56.01	Complex febrile convulsions
R56.1	Post traumatic seizures
R56.9	Unspecified convulsions

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Background

A 24-hour ambulatory electroencephalogram (AEEG) is used to record EEG tracings on a cassette or digital recorder on a continuous outpatient basis.  Electrodes for at least 3 recording channels are secured to the patient's head while a digital or cassette recorder is secured to the patient's waist or to a shoulder harness.  The EEG information is stored for later play back and analysis. A CMS National Coverage Determination (NCD) states that ambulatory EEG should always be preceded by a resting EEG.

The advantage of 24-hour AEEG is its ability to continuously record over a prolonged period both general and localized seizure activity during near-normal activity.  Recent advances in computer technology have improved available capabilities of AEEG monitors.  Lighter weight, smaller, and faster processors with larger digital storage capacity have overcome earlier limitations on EEG recording and analysis.  Commercially available AEEG has evolved during the last 2 decades from 3-channel analog devices to digital machines with reformable montages of up to 32 channels and computer-assisted spike and seizure detection programs.

Ambulatory EEG monitoring may facilitate the differential diagnosis between seizures and syncopal attacks, sleep apnea, cardiac arrhythmias or hysterical episodes.  The test may also allow the investigator to identify the epileptic nature of some episodic periods of disturbed consciousness, mild confusion, or peculiar behavior, where resting EEG is not conclusive.  It may be useful in documenting seizures that are precipitated by naturally occurring cyclic events or environmental stimuli, which are not reproducible in the hospital or clinic setting.  It may also allow an estimate of seizure frequency, which may at times help to evaluate the effectiveness of a drug and determine its appropriate dosage.

Ambulatory monitoring, however, is not necessary to evaluate most seizures, which are usually readily diagnosed by routine EEG studies and history.

Combined Use of Ambulatory EEG and Home-Video Recording

Lawley et al (2015) stated that EEG is an established diagnostic tool with important implications for the clinical management of patients with epilepsy or non-epileptic attack disorder. Different types of long-term EEG recording strategies have been developed over the last decades, including the widespread use of AEEG, which holds great potential in terms of both clinical usefulness and cost-effectiveness.  These investigators presented the results of a systematic review of the scientific literature on the use of AEEG in the diagnosis of epilepsy and non-epileptic attacks in adult patients.  Taken together, these findings confirmed that AEEG is an useful diagnostic tool in patients with equivocal findings on routine EEG studies and influenced management decisions in the majority of studies.  There is evidence that AEEG is also more likely to capture events than sleep-deprived EEG; however, there are currently insufficient data available to compare the diagnostic utility of modern AEEG technology with inpatient video-telemetry.  The authors concluded that further research on the combined use of AEEG and home-video recording is needed.

Implantable Sub-Scalp, Continuous EEG Monitoring Systems (e.g., Epios, Minder) for the Management of Epilepsy

Minder is a minimally invasive device for continuous monitoring of electrographic activity of the brain, providing patients and their doctors with detailed data on brain activity over an extended period (Epiminder, 2025). Patients can wear the device as they go about their normal daily activities.  Minder’s long-term monitoring of patients outside of a controlled clinical environment is expected to result in more effective treatment of underlying conditions, including determining the effectiveness of drug therapies and other potential interventions. Minder has also been designated as a Breakthrough Technology by the FDA, recognizing its potential to provide more effective diagnosis and management for individuals with epilepsy. In April 2025, the FDA has granted authorization for Minder under its De Novo pathway creating a new classification of device, allowing for marketing and sale of the device in the U.S. for patients with drug-resistant epilepsy.

Stirling et al (2021) stated that accurate identification of seizure activity, both clinical and sub-clinical, has important implications in the management of epilepsy.  Accurate recognition of seizure activity is essential for diagnostic, management and forecasting purposes; however, patient-reported seizures have been demonstrated to be unreliable.  Earlier studies have reported that accurate capture of electrographic seizures and forecasting is possible with an implantable intra-cranial device, but less invasive EEG recording systems would be optimal.  These researchers presented preliminary findings of seizure detection and forecasting with a minimally invasive sub-scalp device that continuously records EEG.  A total of 5 patients with refractory epilepsy who experienced at least 2 clinically identifiable seizures monthly were implanted with sub-scalp devices (Minder), providing 2 channels of data from both hemispheres of the brain.  Data were continuously captured via a behind-the-ear system, which also powered the device, and transferred wirelessly to a mobile phone, from where it is accessible remotely via cloud storage.  EEG recordings from the sub-scalp device were compared to data recorded from a conventional system during a 1-week ambulatory video-EEG monitoring session.  Suspect epileptiform activity (EA) was detected using machine learning (ML) algorithms and reviewed by trained neurophysiologists.  Seizure forecasting was revealed retrospectively by using cycles in EA and previous seizure times.  The procedures and devices were well-tolerated and no significant complications were reported.  Seizures were accurately identified on the sub-scalp system, as visually confirmed by periods of concurrent conventional scalp EEG recordings.  The data acquired also allowed seizure forecasting to be successfully undertaken.  The area under the receiver operating characteristic curve (AUC score) achieved (0.88), which was comparable to the best score in recent, state-of-the-art forecasting work using intra-cranial EEG.  The authors concluded that the findings of this study showed the feasibility of using a continuous sub-scalp EEG device to record data of sufficient resolution to capture relevant events, detect the events algorithmically, and use the events in a seizure forecasting algorithm.  These data were extremely valuable for the assessment of epilepsy, and could be linked to systems to improve safety and independence, potentially changing fundamentally the approach to the management of the condition.

The authors stated that there are limitations with sub-scalp EEG systems.  First, despite the limited invasiveness of subcutaneous electrodes, this surgical procedure may not be acceptable to all individuals with epilepsy.  Hence, patient seizure diaries will remain a useful tool in clinical settings, and non-invasive forecasting systems based on mobile and wearable devices are desired by the epilepsy community.  Wearable sensors and non-invasive features may be useful to forecast seizure likelihood, and self-reported events and biomarkers derived from wearables also revealed cycles that are co-modulated with seizure likelihood.  However, the correlation between self-reported events and electrographic events is patient-specific.  In cases where the accuracy is less than perfect, it is unlikely that forecasts using self-reported events will perform as well as forecasts using chronic EEG.  Despite advances in wearable technology for seizure detection, there remain significant false positives and many seizure types are missed.  It is likely that chronic sub-scalp EEG recordings will prove to be a critical “ground-truth” to develop wearable seizure detection and forecasting.  Second, validating electrographic seizures also remains a significant challenge, even with the aid of an algorithm detecting suspect events.  A short 24-hour segment of continuous EEG alone can take hours for a trained neurophysiologist to review, which is not viable for large-scale use of sub-scalp devices; thus, optimizing seizure detection algorithms will be critical.  The time taken for clinical review placed several limitations on the validation of the signal quality and the algorithms used in this preliminary study.  Qualitatively, EEG signals between scalp and sub-scalp were found to be similar.  In addition, the algorithm presented in this work highlighted strong cycles in detected activity, which are similar to cycles of epileptiform activity observed in previous studies.  However, a more comprehensive assessment of signal equivalence and algorithm performance is needed and will be addressed in future studies.  Third, the retrospective forecasting case study was only presented in 1 subject.  These researchers acknowledged that a larger cohort study is needed to show the generalizability of these forecasting results.  Fourth, it should be noted that the highly clustered nature of the electrographic seizures in Subject 1 may have aided the algorithm in achieving a high AUC score.  On the other hand, clusters tend to result in short cycles; however, the long 18-day and 29-day event cycles were the strongest predictors in this algorithm, and these were present irrespective of clusters.  To understand this further, further investigations should examine the forecasting performance on lead seizures only.

Haneef et al (2022) noted that sub-scalp EEG (ssEEG) is emerging as a promising technology in ultra-long-term EEG recordings.  Given the diversity of devices available in this nascent field, uncertainty persists regarding its use in epilepsy evaluation.  These researchers examined the many proposed applications of ssEEG devices including seizure quantification, seizure characterization, seizure lateralization, seizure localization, seizure alarms, seizure forecasting, biomarker discovery, sleep medicine, as well as responsive stimulation.  The different ssEEG devices in development have individual design philosophies with unique strengths and limitations.  There are devices offering primarily unilateral recordings (24/7 EEG, SubQ, Neuroview, Soenia, UltimateEEG), bilateral recordings (Minder, Epios), and even those with responsive stimulation capability (EASEE).  The authors synthesized the current knowledge of these ssEEG systems, and reviewed the ssEEG devices; used case scenarios; challenges; and suggested a road-map for ideal ssEEG designs.

Hirsch et al (2023) stated that treatment decisions in epilepsy critically depend on information on the course of the disease, its severity, as well as options for specific local interventions.  These investigators reported on the case of a patient with pharmaco-resistant, non-lesional temporal lobe epilepsy with evidence for predominant right temporal epileptogenesis.  While seizure frequency had been grossly under-estimated for many years, ultralong-term monitoring with a subcutaneous EEG device showed actual seizure frequency (66 over 11 months versus 4 patient-documented seizures), providing objective data on treatment effectiveness and additional supportive lateralizing information that played a decisive role for the choice of surgical treatment, which had been rejected by the patient before this information.

Pacia (2023) noted that sub-scalp Implantable Telemetric EEG (SITE) devices are under development for the treatment of epilepsy; however, beyond epilepsy, continuous EEG analysis could revolutionize the management of patients suffering from all types of brain disorders.  These investigators reviewed decades of foundational EEG research, collected from short-term routine EEG studies of common neurological and behavioral disorders, that may guide future SITE management and research.  Established quantitative EEG methods, like spectral EEG power density calculation combined with state-of-the-art ML techniques applied to SITE data, can identify new EEG biomarkers of neurological disease.  From distinguishing syncopal events from seizures to predicting the risk of dementia, SITE-derived EEG biomarkers can provide clinicians with real-time information regarding diagnosis, treatment response, and disease progression.  The author concluded that few devices were available for the continuous monitoring of brain physiology.  SITE devices under development for seizure detection may not only improve epilepsy management but could extend the understanding of EEG biomarkers that characterize all other brain disorders.  Analysis of continuous EEG with advanced techniques such as ML has the potential to improve neurological diagnosis and management, advance therapeutic monitoring, and usher in a new era of personalized neurological care.

In a pilot study, Rubboli et al (2024) examined the clinical utility, safety, and tolerability of ultra long-term monitoring with a novel subcutaneous EEG device (sqEEG) in patients with epilepsy.  A total of 5 patients with drug-resistant focal epilepsy were implanted (1 patient bilaterally) with sqEEG.  In phase-I, these investigators examined sqEEG sensitivity for seizure recording by recording seizures simultaneously with scalp EEG in the epilepsy monitoring unit (EMU).  sqEEG was scored either visually (v-sqEEG) or by means of a semi-automatic algorithm (EpiSight; E-sqEEG).  In phase-II, subjects were monitored as outpatients for 3 to 6 months.  sqEEG data were analyzed monthly, examining concordance of data obtained by v-sqEEG, E-sqEEG, and patients' diaries.  v-sqEEG data were used to guide treatment adjustments; and sqEEG-related side effects were assessed throughout the study.  In phase-I, v-sqEEG detected all seizures recorded in the EMU in all patients, whereas E-sqEEG was as effective in 3 patients.  In the other 2 subjects, E-sqEEG detected only a proportion or none of the seizures, respectively.  Sensitivity of E-sqEEG depended on the ictal EEG features.  In phase-II, a 100 % concordance between E-sqEEG and v-sqEEG in seizure detection was observed for the same 3 patients as in phase-I.  In the other 2 subjects (1 implanted bilaterally), effectiveness of E-sqEEG in detecting seizure as compared to v-sqEEG ranged from 0 % to 83 %.  v-sqEEG showed that all patients reported in their diaries fewer seizures than they actually suffered.  In 4 of 5 patients, v-sqEEG showed that the treatment adjustments had been ineffective or associated with a seizure increment.  The only side effect was an infection at the implantation site in 1 patient.  The authors concluded that the sqEEG system could collect reliable information on seizure activity; thereby, providing clinically relevant information.  Sensitivity of EpiSight in detecting seizures varied across patients, depending on the ictal EEG features. sqEEG ultra long-term monitoring was feasible and well-tolerated; and it has the potential to provide clinically relevant information for clinical follow-ups and for treatment management.

The authors stated that this study had several drawbacks.  First, length of the sqEEG monitoring.  Second, the limited number of patients (n = 5) and the heterogeneity of their seizure types as shown by the EMU recordings might reduce the possibility to generalize these findings to other patients with the same seizures or different seizure types.  Third, most of patients manually filled in their diaries, and often the timing of seizure occurrence was imprecise or even lacking (the patient was unaware of the seizures, or a long post-ictal phase might have impeded annotating the correct timing of the seizure), rendering the comparison between timing of seizure occurrence in the diary and in sqEEG difficult.

An UpToDate review on “Video and ambulatory EEG monitoring in the diagnosis of seizures and epilepsy” (Moeller et al, 2025) states that “[M]ethods for ultra-long-term ambulatory EEG monitoring are being developed, mostly involving electrodes implanted between the scalp and the skull (subscalp) via simple outpatient surgical procedures.  Some of these have been approved in Europe, and at least one is being considered for US FDA approval.  These devices can be used to capture infrequent spells, for discovering long-term patterns such as circadian and longer (multiday) cycles, and for seizure forecasting”.

Furthermore, an UpToDate review on “Electroencephalography (EEG) in the diagnosis of seizures and epilepsy” (Haider et al, 2025) does not mention implantable/sub-scalp EEG monitor as a management tool.

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References