Medical Policy Medical Policy
Policy Num: 03.001.008
Policy Name: Quantitative Electroencephalography as a Diagnostic Aid for Attention-Deficit/Hyperactivity Disorder, Cognitive Impairment, or Autism Spectrum Disorder
Policy ID: [03.001.008] [Ac / B / M- / P-] [3.01.03]
Last Review: November 06, 2024
Next Review: November 20, 2025
Related Policies:
02.01.067 - Neurofeedback
| Population Reference No. | Populations | Interventions | Comparators | Outcomes |
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| 2 | Individuals:
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| 3 | Individuals:
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Patients with attention-deficit/hyperactivity disorder (ADHD) may have alterations in their brain wave patterns that can be measured by quantitative electroencephalography (EEG). A commercially available system, the Neuropsychiatric EEG-based ADHD Assessment Aid, measures the resting theta/beta ratio of the electroencephalogram. This technology is being evaluated to aid in the diagnosis of ADHD in adolescents and children for whom there is a clinical suspicion of ADHD.
Quantitative EEG is also being evaluated to aid in the diagnosis of other disorders such as in individuals with cognitive impairment (eg, dementia) and autism spectrum disorder.
This evidence review does not address the use of quantitative EEG in epilepsy or emergent intraoperative settings.
For individuals suspected of having attention-deficit/hyperactivity disorder (ADHD) who received quantitative electroencephalography (EEG), the evidence includes a number of studies on brain wave patterns, particularly the theta/beta ratio. Relevant outcomes are symptoms, functional outcomes, and medication use. Numerous studies have evaluated brain wave patterns with standard EEG equipment, and a pivotal trial, submitted to the U.S. FDA, measured the theta/beta ratio with the Neuropsychiatric EEG-based ADHD Assessment Aid system. In the pivotal trial, both the specificity and positive predictive value of quantitative EEG were high. The reclassification analysis would suggest that a negative Neuropsychiatric EEG-based ADHD Assessment Aid might make ADHD less likely, although it is not clear from this study whether the consensus diagnosis was more accurate than the initial clinical diagnosis that included patient interview and parent rating scales. The larger body of evidence also raises questions about the utility of measuring the theta/beta ratio because it has not been a consistent finding across studies. Given the uncertainty of an increase in the theta/beta ratio in patients with ADHD, additional study is needed to determine whether a low theta/beta ratio can identify children and adolescents who are unlikely to have ADHD. Also, the effect of the test on patient outcomes would allow greater certainty regarding the usefulness of this test. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome.
For individuals suspected of having cognitive impairment (eg, dementia) who receive quantitative electroencephalography (EEG), the evidence includes an observational study. Relevant outcomes are symptoms and functional outcomes. One study found quantitative EEG poorly diagnosed Alzheimer's disease (AD). Another study evaluating quantitative EEG for diagnosing dementia and dementia with Lewy bodies (DLB) demonstrated a sensitivity of 80% and a specificity of 89% for diagnosing dementia, and a sensitivity of 60% and a specificity of 90% for diagnosing DLB. This study had a small sample size and was conducted at a single center. There is limited evidence on the brain wave patterns that associated with cognitive impairment. Therefore, additional study is needed to determine the brain wave patterns that can identify individuals with cognitive impairment. Also, the effect of the test on patient outcomes would allow greater certainty regarding the usefulness of this test. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome.
For individuals suspected of having autism spectrum disorder (ASD) who receive quantitative electroencephalography (EEG), the evidence includes a systematic review and meta-analysis. Relevant outcomes are symptoms and functional outcomes. One systematic review with meta-analyses showed that autistic individuals had reduced relative alpha power (g=-0.35) and increased gamma power (absolute: g=0.37, relative: g=1.06) compared to neurotypical individuals. This systematic review did not report on sensitivity or specificity. There is limited evidence on the brain wave patterns that associated with ASD. Therefore, additional study is needed to determine the brain wave patterns that can identify individuals with ASD. Also, the effect of the test on patient outcomes would allow greater certainty regarding the usefulness of this test. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome.
Not applicable
The objective of this evidence review is to determine whether the use of quantitative electroencephalography improves the net health outcome in individuals suspected of having attention-deficit/hyperactivity disorder, cognitive impairment, or autism spectrum disorder. This evidence review does not address the use of quantitative EEG in epilepsy or emergent intraoperative settings.
Quantitative electroencephalographic-based assessment of the theta/beta ratio is considered investigational as a diagnostic aid for attention-deficit/hyperactivity disorder.
Quantitative electroencephalographic-based assessment is considered investigational as a diagnostic aid for cognitive impairment.
Quantitative electroencephalographic-based assessment is considered investigational as a diagnostic aid for autism spectrum disorder.
This testing would likely be reported with existing electroencephalography CPT codes. The clinician would report the appropriate code for electroencephalography (eg, 95812-95813) and the code for digital analysis of electroencephalogram (95957) would be reported for the analysis.
Blue Card/National Account Issues
State or federal mandates (eg, Federal Employee Program) may dictate that certain U.S. Food and Drug Administration-approved devices, drugs, or biologics may not be considered investigational, and thus these devices may be assessed only by their medical necessity.
Benefits are determined by the group contract, member benefit booklet, and/or individual subscriber certificate in effect at the time services were rendered. Benefit products or negotiated coverages may have all or some of the services discussed in this medical policy excluded from their coverage.
Attention-deficit/hyperactivity disorder (ADHD) is common in children, adolescents, and adults, and is defined by pervasive symptoms of inattention and/or hyperactivity-impulsivity, which lead to impairment in at least 2 domains of the work, school, or home environments. Stimulant medications reduce symptoms associated with ADHD, although there are concerns about the potential for overdiagnosis and overprescribing of medication.
Presently, ADHD is diagnosed clinically by assessing behavioral symptoms and impairment via interviews and standard questionnaires. Diagnosis can be challenging because the core symptoms are nonspecific. They may be present in other psychiatric disorders (eg, learning disabilities, conduct disorders, affective disorders) or result from environmental influences such as a lack of discipline. Also, ADHD is a heterogeneous disorder with multiple subtypes and frequently coexists with other psychiatric disorders.
There has been substantial research conducted over the last several decades on whether electroencephalography (EEG)-derived brain wave patterns in patients with ADHD differ from those without ADHD. EEG patterns are typically categorized into 4 frequency ranges: delta (<4 Hz), theta (4-7 Hz), alpha (8-12 Hz), and beta (13-25 Hz). The largest focus of research on brain wave patterns in ADHD has been on whether there are increased theta wave activity and an increased theta/beta ratio in ADHD patients.
The Neuropsychiatric EEG-based ADHD Assessment Aid (NEBA®) system is a specific quantitative EEG system that measures the resting theta/beta ratio of the electroencephalogram with an electrode located at the central midline position (referred to as position CZ in the international 10-20 EEG system). Quantitative EEG uses computer analysis with the mathematical transformation from the time domain into the frequency domain (fast-Fourier transform) to determine the total power at each frequency. The relative power of the waveform can then be calculated in relation to the total power of the 4 frequency ranges. The NEBA system uses proprietary cutoffs to generate an estimate of the likelihood of ADHD based on the resting theta/beta ratio.
It is proposed that the NEBA system can be used to confirm a clinical diagnosis or support further testing in children and adolescents with ADHD. The system is not intended to evaluate patients for whom the clinician’s diagnosis of ADHD is negative, and the system does not generate an interpretive report in this situation. It is also proposed that the clinician’s diagnostic impression plus the results generated by the NEBA system may reduce the potential for overdiagnosis of ADHD, and thereby reduce the risks of administering unnecessary pharmacologic therapy in the intended-use population. Also, as a result of research on EEG brain waves in ADHD, neurofeedback has been developed as a potential treatment for ADHD (see evidence review 2.01.28). This treatment employs principles of biofeedback using EEG brain wave activity and attempts to alter the brainwave patterns in beneficial ways.
Dementia is characterized by the decline in cognition in one or more cognitive domains, such as learning and memory, language, executive function, complex attention, perceptual-motor, and social cognition. Alzheimer Disease (AD) is the most common form of dementia in older adults. AD is a fatal neurodegenerative disease that causes progressive loss in memory, language, and thinking, with the eventual loss of ability to perform social and functional activities in daily life. Survival after a diagnosis of dementia due to AD generally ranges between 4 and 8 years; however, life expectancy can be influenced by other factors, such as comorbid medical conditions. It is estimated that 6.2 million Americans aged 65 and older are currently living with AD dementia, and the number is projected to reach over 12 million by 2050, with an approximate lifetime risk of developing AD dementia at age 65 of 21.1% for women and 11.6% for men.1, The lifetime risk for dementia due to AD is approximately 20% for women and 10% for men. Per the 2018 American Academy of Neurology practice guideline update on mild cognitive impairment (MCI), the prevalence of MCI was 6.7% for ages 60 to 64, 8.4% for ages 65 to 69, 10.1% for ages 70 to 74, 14.8% for ages 75 to 79, and 25.2% for ages 80 to 84.2, The cumulative dementia incidence was 14.9% in individuals with MCI >65 years of age followed for 2 years.
Data from the National Institute on Aging have shown that Black Americans are approximately 1.5 to 2 times more likely to develop AD and related dementias as compared to Whites.3, Additionally, Black participants in AD research studies were 35% less likely to be diagnosed with AD and related dementias and were found to have more risk factors for the disease as well as greater cognitive impairment and symptom severity than White participants. Findings from 2 national surveys conducted by the Alzheimer's Association also found that people of color face discrimination when seeking health care for AD and related dementias with the highest level of discrimination in dementia health care reported by Black Americans (50%) followed by Native (42%), Asian (34%), and Hispanic (33%) Americans.4, Non-Hispanic White Americans reported a discrimination rate of 9%.
Presently, dementia is diagnosed clinically through initial cognitive testing followed by a physical examination including neurological examination, and then subsequent laboratory testing and neuroimaging (eg, computed tomography (CT) or magnetic resonance imaging MRI). According to The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), criteria for major neurocognitive disorder (eg, dementia), include the following5,:
"Evidence of significant cognitive decline from a previous level of performance in one or more cognitive domains (complex attention, executive function, learning and memory, language, perceptual-motor, or social cognition) based on:
Concern of the individual, a knowledgeable informant, or the clinician that there has been a significant decline in cognitive function; and
A substantial impairment in cognitive performance, preferably documented by standardized neuropsychological testing or, in its absence, another quantified clinical assessment.
The cognitive deficits interfere with independence in everyday activities (i.e., at a minimum, requiring assistance with complex instrumental activities of daily living such as paying bills or managing medications).
The cognitive deficits do not occur exclusively in the context of a delirium.
The cognitive deficits are not better explained by another mental disorder (e.g., major depressive disorder, schizophrenia)."
Autism spectrum disorder (ASD) is a biologically based neurodevelopmental disorder characterized by persistent deficits in social communication, social interaction and restricted, repetitive patterns of behavior, interests, and activities. ASD can range from mild social impairment to severely impaired functioning. As many as half of individuals with autism are non-verbal and have symptoms that may include debilitating intellectual disabilities, inability to change routines, and severe sensory reactions. The American Psychiatric Association’s DSM-5 provides standardized criteria to help diagnose ASD.5, Autism can co-occur with mental health diagnoses, including, but not limited to, depression, anxiety disorders (eg, social anxiety, obsessive-compulsive disorder), attention deficit hyperactivity disorder, Tourette syndrome/tic disorder, personality disorder, and/or psychosis.6,
Diagnosis of ASD in the United States (U.S.) generally occurs in 2 steps: developmental screening followed by comprehensive diagnostic evaluation if screened positive. The American Academy of Pediatrics (AAP) recommends general developmental screening at 9, 18, and 30 months of age and ASD-specific screening at 18 and 24 months of age.7,8, Diagnosis and intervention in the first few years of life can have a strong impact on functioning since it allows for treatment during a key window of developmental plasticity.9,10, However, early diagnosis in the US remains an unmet need even though studies have demonstrated a temporal trend of decreasing mean age at diagnosis over time.11,12,
In 2011, the generic device Neuropsychiatric Interpretive Electroencephalograph Assessment Aid was granted a de novo 510(k) classification by the U.S. Food and Drug Administration (FDA; class II, special controls, product code: NCG). According to the FDA documentation, a neuropsychiatric interpretive EEG assessment aid is a device prescribed by a physician that uses a patient’s electroencephalogram to provide an interpretation of the patient’s neuropsychiatric condition. In addition to the general controls, approval of these devices is subject to a number of special controls, including the following:
Clinical performance testing must demonstrate the accuracy, precision, and reproducibility of the EEG-based interpretation, including any specified equivocal ones (cutoffs).
Clinical performance testing must demonstrate the ability of the device to function as an assessment aid for the medical condition for which the device is indicated. Performance measures must demonstrate device performance characteristics per the intended use in the intended use environment. Performance measurements must include sensitivity, specificity, positive predictive value, and negative predictive value per the device intended use. Repeatability of measurement must be demonstrated using interclass correlation coefficients and illustrated by qualitative scatterplots.
The device design must include safeguards to prevent device use as a stand-alone diagnostic.
The labeling must bear all information required for the safe and effective use of the device.
In 2013, the Neuropsychiatric EEG-based Assessment Aid (NEBA ; NEBA Health previously Lexicor Medical Technology) for ADHD was granted a de novo 510(k) classification by the FDA (K112711). The device is indicated to measure the theta/beta ratio of the electroencephalogram at electrode CZ on patients 6 to 17 years of age, combined with a clinician’s evaluation, to aid in the diagnosis of ADHD. NEBA should only be used by a clinician as confirmatory support for a completed clinical evaluation or as support for the clinician’s decision to pursue further testing following clinical evaluation. The device is not intended as a stand-alone tool in the evaluation or diagnosis of ADHD. FDA product code: NCG
In 2017, the eVox System (Evoke Neuroscience, Inc.) was granted 510(k) classification and cleared for marketing by the FDA (K171781; FDA Product Codes: GWQ, GWJ). In 2020, the NeuralScan System was granted 510(k) classification and cleared for marketing by the FDA (K192753; FDA Product Codes: OLT, GWJ, GWQ). Both of these devices are indicated for: "the acquisition, display, and storage, of electrical activity of a patient’s brain including electroencephalograph (EEG) and event-related potentials (ERP) obtained by placing two or more electrodes on the head to aid in diagnosis." These indications are not condition- or disease-specific.
Puerto Rico Law 163 of August 13, 2024:Law for the protection, security, integration, well-being and comprehensive development of people with Autism Spectrum Disorders.
This evidence review was created in October 2013 and has been updated regularly with searches of the PubMed database. The most recent literature update was performed through August 28, 2024.
Evidence reviews assess whether a medical test is clinically useful. A useful test provides information to make a clinical management decision that improves the net health outcome. That is, the balance of benefits and harms is better when the test is used to manage the condition than when another test or no test is used to manage the condition.
The first step in assessing a medical test is to formulate the clinical context and purpose of the test. The test must be technically reliable, clinically valid, and clinically useful for that purpose. Evidence reviews assess the evidence on whether a test is clinically valid and clinically useful. Technical reliability is outside the scope of these reviews, and credible information on technical reliability is available from other sources.
Promotion of greater diversity and inclusion in clinical research of historically marginalized groups (e.g., People of Color [African-American, Asian, Black, Latino and Native American]; LGBTQIA (Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, Asexual); Women; and People with Disabilities [Physical and Invisible]) allows policy populations to be more reflective of and findings more applicable to our diverse members. While we also strive to use inclusive language related to these groups in our policies, use of gender-specific nouns (e.g., women, men, sisters, etc.) will continue when reflective of language used in publications describing study populations.
Attention-deficit/hyperactivity disorder (ADHD) is common in children, adolescents, and adults, and is defined by pervasive symptoms of inattention and/or hyperactivity-impulsivity, which lead to impairment in at least 2 domains of the work, school, or home environments. Stimulant medications reduce symptoms associated with ADHD, although there are concerns about the potential for overdiagnosis and overprescribing of medication.
The purpose of quantitative electroencephalography (EEG) in patients who are suspected of having ADHD is to inform a decision whether to initiate specific therapy.
The following PICO was used to select literature to inform this review.
The relevant population of interest is individuals with suspected ADHD.
The test being considered is quantitative EEG, using the Neuropsychiatric EEG-based ADHD Assessment Aid (NEBA) system, as part of a clinical evaluation. Devices that provide neurofeedback are also able to assess the theta/beta ratio with quantitative analysis.
The following practice is currently being used to diagnose ADHD: clinical evaluation alone.
The general outcomes of interest are patient symptoms, functional outcomes, and medication use.
For the evaluation of the clinical validity of the tests, studies that meet the following eligibility criteria were considered:
Reported on the accuracy of the marketed version of the technology (including any algorithms used to calculate scores)
Included a suitable reference standard
Patient/sample clinical characteristics were described
Patient/sample selection criteria were described
Included a validation cohort separate from development cohort.
A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).
A number of studies have measured theta activity or the theta/beta ratio in children and adolescents with ADHD compared with nonaffected controls. The most commonly reported alteration in EEG is an increase in the theta/beta ratio. However, some studies have reported that other patterns (eg, increased beta wave activity) are found in some patients, and several recent studies have found no significant difference in theta activity in a clinical versus nonclinical population. Quantitative reports of EEG used in the adult ADHD population have found no consistent evidence of atypical theta/beta ratios as a marker of ADHD. .13,
A TEC Assessment (2014) evaluated the evidence related to the use of quantitative EEG with the NEBA system in the diagnosis of ADHD.14, This evidence was submitted to the U.S. Food and Drug Administration (FDA) in 2013 and subsequently published by Snyder et al (2015).15,16, The evidence on the accuracy of NEBA in the diagnosis of ADHD is described next. The evidence also included a discussion of the technical performance of NEBA for the diagnosis of ADHD and test-retest reliability of the NEBA theta/beta ratio for EEG data from 198 patients who had recordings on 2 different days. Evidence of the technical performance is beyond the scope of this evidence review. No studies were identified that assessed whether the reclassification of patients suspected of having ADHD, as reported to the FDA, improved health outcomes.
Data submitted to the FDA regarding the diagnostic accuracy of the NEBA system were from the multicenter study of 275 children and adolescents (aged 6-18 years, described above) who presented with attention and/or behavioral concerns to 1 of 13 clinics in the U.S.15,16, An additional 89 children and adolescents were recruited but did not complete the study, and, of these, 67 had incomplete EEG recordings.16, Diagnostic evaluation for ADHD and other disorders was conducted with a clinical interview and rating scales that included behavior rating scales, IQ and achievement testing, and scales of severity and dysfunction. A consensus best-estimate diagnosis was determined by a multidisciplinary clinical team composed of a clinical psychologist, a neurodevelopmental pediatrician, and a child/adolescent psychiatrist. The clinical team had access to deidentified patient files; however, they did not interview patients or have access to the parent rating scales, features considered critical for a criterion standard diagnosis of ADHD. A separate group of investigators who were unaware of the clinical diagnosis collected the EEG data (NEBA system). When compared with the consensus diagnosis, NEBA had a sensitivity of 89%, a specificity of 87%, a positive predictive value of 81%, and negative predictive value of 93% for adolescents (aged 12-17 years). For children (ages 6-11 years), NEBA had a sensitivity of 79%, a specificity of 97%, a positive predictive value of 96%, and negative predictive value of 82%. The investigators calculated that the addition of NEBA to the clinician’s ADHD evaluation would have increased the clinician’s diagnostic accuracy from 61% to 88%. This calculation is based on the 275 patients who completed the protocol, rather than the intention-to-treat population. The results of this FDA-regulated study suggested that quantitative EEG might be used to decrease the overdiagnosis of ADHD by identifying patients who may not have the disorder. Strengths of this study included its multicenter design and the reclassification analysis of data obtained from a blinded analysis. Limitations were lack of patient interview by the consensus team and lack of intention-to-treat analysis.
Snyder et al (2008) also reported on the accuracy of the theta/beta ratio for the diagnosis of ADHD in an industry-sponsored, investigator-blinded, multicenter study.17, Patients (N=159) aged 6 to 18 who had presented to 1 of 4 psychiatric and pediatric clinics with suspected attention and behavioral symptoms were evaluated in a standardized semi-structured manner according to Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) criteria by a clinical team trained on the study instruments. Rating scales were distributed to parents and teachers and held in sealed envelopes until the blind was broken. An EEG was collected separately by investigators, who were blinded to the clinical diagnosis, using a 19-electrode cap according to the 10-20 system with eyes open and eyes shut. A threshold of 1.5 standard deviations of the theta/beta ratio from normative database values (according to age) at electrode CZ was used to determine ADHD versus non-ADHD. With a prevalence of ADHD of 61% based on clinical diagnosis, the theta/beta ratio had a sensitivity of 87%, a specificity of 94%, a positive predictive value of 95%, and negative predictive value of 82%. The rating scales provided a sensitivity of 38% to 79% and specificity of 13% to 61%. Results from this study were used to set a new theta/beta threshold for an analysis of data from the FDA-regulated study of the NEBA device.15,16,
Other studies have reported lower accuracy of quantitative EEG in the diagnosis of ADHD. van Dijk et al (2020) assessed whether different signal processing methods affected the ability to distinguish patients with ADHD from controls.18, Five different signal processing algorithms were applied to EEG screening data from 2 multi-center clinical studies: the International Collaborative ADHD Neurofeedback multisite clinical trial and the International Study to Predict Optimized Treatment in ADHD. The 2 studies included 608 children with ADHD and 158 children without ADHD. van Dijk et al found significant differences in the the theta/beta ratio calculated with the 5 algorithms, but none of the methods were able to distinguish between children with and without ADHD. A limitation of this study is that methods used by NEBA were not specifically assessed.
Section Summary: Clinically Valid
Patients who have ADHD may have altered brain wave patterns on quantitative EEG compared with patients without ADHD. While an increased theta/beta ratio is the most common alteration reported, not all studies have found this association. No studies have reported on the sensitivity and specificity of the NEBA system when added to clinical diagnosis. In the pivotal study, diagnostic accuracy was estimated to increase from 61% to 88% when added to clinical diagnosis. However, there are limitations to the pivotal study, and a recent study of various EEG processing methods in a large dataset found no diagnostic value of the theta/beta ratio for children with ADHD, raising questions about the utility of quantitative EEG in the diagnosis of ADHD.
A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.
Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.
A proposed benefit of the NEBA system is a reduction in the overdiagnosis of ADHD, thereby lessening the risks of unnecessary pharmacologic therapy in children and adolescents. There were no published studies that directly reported on clinical outcomes, such as measures of disease activity and/or medication use.
Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.
The pivotal FDA study reported on the reclassification of diagnosis following NEBA; this may be considered an indirect measure that may impact outcomes.
The evidence related to whether quantitative EEG improves the clinical diagnosis of patients with suspected ADHD consists of the material submitted to the FDA as part of the NEBA’s approval process and subsequently published by Snyder et al (2015), as previously described.15,16, The study included reclassification tables to demonstrate whether NEBA provides additional information beyond the clinician’s initial diagnosis, which is summarized in Table 1. Use of NEBA was consistent with the categorization of patients diagnosed with ADHD by both the initial clinical diagnosis and the consensus diagnosis. For example, 95 (73%) of 130 children and adolescents who were considered to have ADHD by the consensus diagnosis were classified as ADHD by both the clinician alone and NEBA. Reclassification was observed when using NEBA for patients diagnosed by clinician alone as ADHD and consensus as non-ADHD. For example, 145 children and adolescents had a non-ADHD diagnosis by the consensus. Of the 145, 93 had received an initial clinical diagnosis of ADHD but 85 (91%) were negative by NEBA.
| Consensus Diagnosisa | Initial Clinical Diagnosis | Total | |||
| ADHD | + | - | |||
| NEBA interpretationb | + | 95 (81.9) | 11 (78.6) | 106 | |
| - | 21 (18.1) | 3 (21.4) | 24 | ||
| Total | 116 | 14 | 130 | ||
| Not ADHD | + | - | |||
| NEBA interpretationb | + | 8 (8.6) | 1 (1.9) | 9 | |
| - | 85 (91.4) | 51 (98.1) | 136 | ||
| Total | 93 | 52 | 145 | ||
ADHD: attention-deficit hyperactivity disorder; FDA: U.S. Food and Drug Administration; NEBA: Neuropsychiatric EEG-Based Assessment Aid.a The consensus diagnosis is assumed to be the reference standard (ie, correct). Two categories are included in the ADHD consensus diagnosis: diagnosed with ADHD or referred for more testing for the condition. Similarly, the “not ADHD” diagnosis included those diagnosed as not having ADHD or as needing more testing for other conditions.b The NEBA interpretation is a composite of both the initial clinical diagnosis and the NEBA results, like a dichotomized posttest probability. The performance measures are presumably calculated assuming that a negative NEBA result can override a positive initial clinical diagnosis, but in the FDA summary, it was stated that a negative diagnosis can only result from a negative initial clinical diagnosis (ie, the NEBA interpretation cannot override it).
Patients who have ADHD may have altered brain wave patterns on quantitative EEG compared with patients without ADHD. While an increased theta/beta ratio is the most common alteration reported, not all studies have found this association. No studies have reported on the sensitivity and specificity of the NEBA system when added to clinical diagnosis. In the pivotal study, diagnostic accuracy was estimated to increase from 61% to 88% when added to clinical diagnosis. However, there are limitations to the pivotal study, and a recent study of various EEG processing methods in a large dataset found no diagnostic value of the theta/beta ratio for children with ADHD, raising questions about the utility of quantitative EEG in the diagnosis of ADHD. Reclassification results from the pivotal trial suggest that NEBA may support an alternative diagnosis in patients initially suspected of having ADHD but not confirmed by consensus diagnosis. No studies were identified that addressed whether clinical outcomes were improved for patients with suspected ADHD who were reclassified by NEBA.
For individuals suspected of having ADHD who received QEEG, the evidence includes a number of studies on brain wave patterns, particularly the theta/beta ratio. The relevant outcomes are symptoms, functional outcomes, and medication use. Numerous studies have evaluated brain wave patterns with standard EEG equipment, and a pivotal trial, submitted to the FDA, measured the theta/beta ratio with the NEBA system. In the pivotal trial, both the specificity and positive predictive value of QEEG were high. The reclassification analysis would suggest that a negative NEBA might indicate that ADHD is less likely, although it is not clear from this study whether the consensus diagnosis was more accurate than the initial clinical diagnosis that included patient interview and parent rating scales. The larger body of evidence also raises questions about the utility of measuring the theta/beta ratio because it has not been a consistent finding across studies. Given the uncertainty of an increase in the theta/beta ratio in patients with ADHD, additional study is needed to determine whether a low theta/beta ratio can identify children and adolescents who are unlikely to have ADHD. Also, the effect of the test on patient outcomes would allow greater certainty regarding the usefulness of this test. The evidence is insufficient to determine the effects of the technology on health outcomes.
| [ ] MedicallyNecessary | [X] Investigational |
Population Reference No. 2
The purpose of quantitative electroencephalography (EEG) in individuals who are suspected of having is to inform a decision whether to initiate specific therapy.
The following PICO was used to select literature to inform this review.
The relevant population of interest is individuals with suspected cognitive impairment.
The test being considered is quantitative EEG as part of a clinical evaluation. Devices that provide neurofeedback are also able to assess the theta/beta ratio with quantitative analysis.
The following practice is currently being used to diagnose cognitive impairment: clinical evaluation and neuroimaging (eg, computed tomography (CT) or magnetic resonance imaging MRI).
The general outcomes of interest are patient symptoms, functional outcomes, and medication use.
For the evaluation of the clinical validity of the tests, studies that meet the following eligibility criteria were considered:
Reported on the accuracy of the marketed version of the technology (including any algorithms used to calculate scores);
Included a suitable reference standard;
Patient/sample clinical characteristics were described;
Patient/sample selection criteria were described;
Included a validation cohort separate from development cohort.
A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).
There is limited evidence for the use of quantitative EEG in the diagnosis of cognitive impairment such as dementia. Iannaccone et al (2023) evaluated the effectiveness of quantitative EEG for diagnosing dementia and dementia with Lewy bodies (DLB).19, Patients with suspected initial state of dementia or cognitive impairment (n=32) and controls (n=16) were recruited for the study. Participants underwent clinical assessment by 2 blinded neurologists, EEG recording, and a 6-month follow-up clinical assessment. The use of quantitative EEG demonstrated a sensitivity of 80% and a specificity of 89% for diagnosing dementia, and a sensitivity of 60% and a specificity of 90% for diagnosing DLB. This study had limitations including its retrospective, single-center design. More evidence is needed to determine whether quantitative EEG can be used as a diagnostic tool for cognitive impairment.
Ommundsen et al (2011) conducted a study evaluating the use of quantitative EEG in diagnosing Alzheimer's disease (AD).20, They compared quantitative EEG results with clinical diagnoses (N=104). Quantitative EEG yielded a positive test in 22 of 30 patients with a clinical diagnosis of AD and a negative test in 34 of 74 patients without AD. The authors concluded that quantitative EEG was poor at diagnosing AD due to the frequency of false-positive results.
Individuals with cognitive impairment such as dementia may have altered brain wave patterns on quantitative EEG compared to individuals without cognitive impairment. However, there is limited evidence of the validity of quantitative EEG used to diagnose cognitive impairment. One study found quantitative EEG poorly diagnosed AD. Another study evaluating quantitative EEG for diagnosing dementia and DLB demonstrated a sensitivity of 80% and a specificity of 89% for diagnosing dementia, and a sensitivity of 60% and a specificity of 90% for diagnosing DLB. This study was retrospective and conducted at a single center.
A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.
Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.
Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.
Individuals with cognitive impairment such as dementia may have altered brain wave patterns on quantitative EEG compared to individuals without cognitive impairment. However, since there is limited evidence of the validity of quantitative EEG used to diagnose cognitive impairment, inferences cannot be made about clinical utility. One study found quantitative EEG poorly diagnosed AD. Another study evaluating quantitative EEG for diagnosing dementia and DLB demonstrated a sensitivity of 80% and a specificity of 89% for diagnosing dementia, and a sensitivity of 60% and a specificity of 90% for diagnosing DLB. This study was retrospective and conducted at a single center. No studies have demonstrated that quantitative EEG improves diagnostic accuracy in individuals with cognitive impairment.
For individuals suspected of having cognitive impairment (eg, dementia) who receive quantitative electroencephalography (EEG), the evidence includes an observational study. Relevant outcomes are symptoms and functional outcomes. One study found quantitative EEG poorly diagnosed Alzheimer's disease (AD). Another study evaluating quantitative EEG for diagnosing dementia and dementia with Lewy bodies (DLB) demonstrated a sensitivity of 80% and a specificity of 89% for diagnosing dementia, and a sensitivity of 60% and a specificity of 90% for diagnosing DLB. This study had a small sample size and was conducted at a single center. There is limited evidence on the brain wave patterns that associated with cognitive impairment. Therefore, additional study is needed to determine the brain wave patterns that can identify individuals with cognitive impairment. Also, the effect of the test on patient outcomes would allow greater certainty regarding the usefulness of this test. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome.
| [ ] MedicallyNecessary | [X] Investigational |
The purpose of quantitative electroencephalography (EEG) in individuals who are suspected of having is to inform a decision whether to initiate specific therapy.
The following PICO was used to select literature to inform this review.
The relevant population of interest is individuals with suspected autism spectrum disorder (ASD).
The test being considered is quantitative EEG as part of a clinical evaluation. Devices that provide neurofeedback are also able to assess the theta/beta ratio with quantitative analysis.
The following practice is currently being used to diagnose ASD: developmental screening followed by comprehensive diagnostic evaluation if screened positive.
The general outcomes of interest are patient symptoms, functional outcomes, and medication use.
For the evaluation of the clinical validity of the tests, studies that meet the following eligibility criteria were considered:
Reported on the accuracy of the marketed version of the technology (including any algorithms used to calculate scores);
Included a suitable reference standard;
Patient/sample clinical characteristics were described;
Patient/sample selection criteria were described;
Included a validation cohort separate from development cohort.
A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).
There is limited evidence for the use of quantitative EEG in the diagnosis of ASD. Neo et al (2023) conducted 10 meta-analyses, including 41 studies, to examine differences in resting-state EEG power across various frequency bands (delta, theta, alpha, beta, and gamma) in autistic individuals (n=1246) compared to neurotypical individuals (n=1455).21, The results showed that autistic individuals had reduced relative alpha power (g=-0.35) and increased gamma power (absolute: g=0.37, relative: g=1.06) compared to neurotypical individuals. There were no significant differences in delta, theta, absolute alpha, and beta power between the 2 groups. The study also found substantial heterogeneity in effect sizes across all frequency bands. Moderator analyses indicated that factors such as age, biological sex, IQ, referencing scheme, epoch duration, and use of gold-standard autism diagnostic instruments did not influence the effect sizes. However, the type of resting-state paradigm (eyes-closed vs. eyes-open) and recording duration did moderate some effect sizes. These findings suggest that resting-state alpha and gamma power could be potential biomarkers for autism. This systematic review did not report on sensitivity or specificity.
Individuals with ASD may have altered brain wave patterns on quantitative EEG compared to individuals without ASD. However, there is limited evidence of the validity of quantitative EEG diagnosing ASD. One systematic review with meta-analyses showed that autistic individuals had reduced relative alpha power (g=-0.35) and increased gamma power (absolute: g=0.37, relative: g=1.06) compared to neurotypical individuals. This systematic review did not report on sensitivity or specificity.
A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.
Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.
Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.
Individuals with ASD may have altered brain wave patterns on quantitative EEG compared to individuals without ASD. However, since there is limited evidence of the validity of quantitative EEG diagnosing ASD, inferences cannot be made about clinical utility. One systematic review with meta-analyses showed that autistic individuals had reduced relative alpha power (g=-0.35) and increased gamma power (absolute: g=0.37, relative: g=1.06) compared to neurotypical individuals. This systematic review did not report on sensitivity or specificity. No studies have demonstrated that quantitative EEG improves diagnostic accuracy in individuals with ASD.
For individuals suspected of having autism spectrum disorder (ASD) who receive quantitative electroencephalography (EEG), the evidence includes a systematic review and meta-analysis. Relevant outcomes are symptoms and functional outcomes. One systematic review with meta-analyses showed that autistic individuals had reduced relative alpha power (g=-0.35) and increased gamma power (absolute: g=0.37, relative: g=1.06) compared to neurotypical individuals. This systematic review did not report on sensitivity or specificity. There is limited evidence on the brain wave patterns that associated with ASD. Therefore, additional study is needed to determine the brain wave patterns that can identify individuals with ASD. Also, the effect of the test on patient outcomes would allow greater certainty regarding the usefulness of this test. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome.
| [ ] MedicallyNecessary | [X] Investigational |
The purpose of the following information is to provide reference material. Inclusion does not imply endorsement or alignment with the evidence review conclusions.
Guidelines or position statements will be considered for inclusion in ‘Supplemental Information' if they were issued by, or jointly by, a US professional society, an international society with US representation, or National Institute for Health and Care Excellence (NICE). Priority will be given to guidelines that are informed by a systematic review, include strength of evidence ratings, and include a description of management of conflict of interest.
In 2016, the American Academy of Neurology released a technology report on quantitative electroencephalography for ADHD.22, The main conclusion of the report was that it remains “unknown whether a combination of standard clinical examination and EEG [electroencephalography] theta/beta power ratio increases diagnostic certainty of ADHD compared with clinical examination alone.”
in 2017, the American Academy of Neurology released a consensus report on the diagnosis and management of dementia with Lewy bodies (DLB).23, Quantitative EEG was listed as a supportive biomarker, defined as "biomarkers consistent with DLB that help the diagnostic evaluation, but without clear diagnostic specificity." They acknowledged building evidence for quantitative EEG, showing prominent posterior slow-wave EEG activity with periodic fluctuations in the pre-alpha/theta range, as a biomarker for DLB.
The 2019 American Academy of Pediatrics' practice guidelines on the diagnosis, evaluation, and treatment of attention-deficit/hyperactivity disorder (ADHD) was based on a systematic review from the Agency for Healthcare Research and Quality.24, The guidelines indicated that to make a diagnosis of ADHD, the primary care clinician should determine that Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, Text Revision, criteria have been met (including documentation of impairment in more than 1 major setting), and information should be obtained primarily from reports from parents or guardians, teachers, and other school and mental health clinicians involved in the child’s care. The primary care clinician should also rule out any alternative cause (quality of evidence B/strong recommendation). Assessment by quantitative electroencephalography was not mentioned in these guidelines.
In 2020, the American Academy of Pediatrics published a clinical report on the identification, evaluation, and management of children with ASD.8, The guidelines state: "EEG is not recommended as a routine baseline evaluation in the absence of clinical concern about seizures, atypical regression, or other neurologic symptoms on history or examination that would suggest an EEG is indicated."
In 2019, the American College of Radiology's Appropriateness Criteria for dementia did not include quantitative EEG in their list of imaging.25,
U.S. Preventive Services Task Force Recommendations
Not applicable.
There is no national coverage determination. In the absence of a national coverage determination, coverage decisions are left to the discretion of local Medicare carriers.
Some currently ongoing and unpublished trials that might influence this review are listed in Table 2.
| NCT No. | Trial Name | Planned Enrollment | Completion Date |
| Ongoing | |||
| NCT05635318 | Quantitative EEG Neurofeedback as an Add-on Therapy For Attention-deficit/Hyperactivity Disorder (ADHD) | 102 | Jan 2024 (not yet recruiting) |
| NCT05406778a | SPARK Neuro Quantitative Resting State EEG Protocol for Assessing Cognitive Impairment and AD Status 'REMIND' Study | 800 | Nov 2025 (recruiting) |
| Unpublished | |||
| NCT03644043a | Quantitative EEG for Assessment of Mild Cognitive Impairment Associated With Preclinical Alzheimer's Disease - Evidence for Amyloid Indication Study | 2000 | Nov 2020 (unknown status) |
NCT: national clinical trial.a Denotes industry-sponsored or cosponsored trial.
| Codes | Number | Description |
|---|---|---|
| CPT | 95812-95819 | Electroencephalogram (EEG) monitoring code range |
| 95957 | Digital analysis of electroencephalogram (EEG) (eg, for epileptic spike analysis) | |
| ICD-10-CM | Investigational for relevant diagnoses | |
| G31.84 | Mild cognitive impairment of uncertain or unknown etiology | |
| F70-F79 | Intellectual Disabilities code range | |
| F84.0 | Autistic disorder | |
| F84.9 | Pervasive developmental disorder, unspecified (atypical autism) | |
| F90.0-F90.9 | Attention-deficit hyperactivity disorders, code range | |
| ICD-10-PCS | ICD-10-PCS codes are only used for inpatient services. | |
| 4A00X2Z, 4A00X4Z | Measurement, central nervous system external, codes for conductivity and electrical activity | |
| 4A10X2Z, 4A10X4Z | Monitoring, central nervous system external, codes for conductivity and electrical activity | |
| Type of service | Medicine | |
| Place of service | Outpatient/Inpatient |
As per correct coding guidelines.
| Date | Action | Description |
|---|---|---|
| 11/06/2024 | Annual review | Policy updated with literature review through August 28, 2024; references added. Title changed to include newly added indications. Indications added for the use of quantitative EEG as a diagnostic aid for cognitive impairment and autism spectrum disorder with investigational policy statements.(PICO 2 & 3 were added) .Puerto Rico Law 163 of August 13, 2024:Law for the protection, security, integration, well-being and comprehensive development of people with Autism Spectrum Disorders were added in Regulatory Status Section .Existing policy statement unchanged. |
| 11/07/2023 | Annual review | Policy updated with literature review through August 29, 2023; no references added. Policy statement unchanged. A paragraph for promotion of greater diversity and inclusion in clinical research of historically marginalized groups was added in Rationale section. |
| 11/08/2022 | Annual review | Policy updated with literature review through August 22, 2022; no references added. Policy statement unchanged. |
| 11/17/2021 | Annual review | Policy updated with literature review through September 3, 2021; reference added. Policy statement unchanged. |
| 11/17/2020 | Annual review | Policy updated with literature review through August 31, 2020; references added. Policy statement unchanged. |
| 11/03/2019 | New policy | New policy created with literature review through August 5, 2019 ; considered investigational |