Abstract
Each year, ineffective medical management of patients with mental illness compromises the health and well-being of individuals, and also impacts communities and our society. A variety of interrelated factors have impeded the health system's ability to treat patients with behavior health conditions adequately. A key contributing factor is a lack of objective markers to help predict patient response to specific drugs that has led to patterns of “trial and error” prescribing. For many years, clinicians have sought objective data (eg, a laboratory or imaging test) to assist them in selecting appropriate treatments for individual patients. Electroencephalogram (EEG) findings coupled with medication outcomes data may provide a solution. “Crowdsourced” physician registries that reference clinical outcomes to individual patient physiology have been used successfully for cancers. These techniques are now being explored in the context of behavioral health care. The Psychiatric EEG Evaluation Registry (PEER) is one such approach. PEER is a clinical phenotypic database comprising more than 11,000 baseline EEGs and more than 39,000 outcomes of medication treatment for a variety of mental health diagnoses. Collective findings from 45 studies (3130 patients) provide compelling evidence for PEER as a relatively simple, inexpensive predictor of likely patient response to specific antidepressants and likely treatment-related side effects (including suicidal ideation).
Highlights
Despite unprecedented progress in understanding and treating physical illness, effective medical management of patients with mental health conditions remains among the most daunting and complex population health issues in the United States today
Psychiatric EEG Evaluation Registry (PEER) is a clinical phenotypic database comprising more than 11,000 baseline EEGs and more than 39,000 outcomes of medication treatment for a variety of mental health diagnoses
Subsequent findings from studies by Leuchter,[12] Arns,[13,14,15] Pizzagalli,[16] and others confirmed that patients within the same neuropsychiatric disorder might be characterized by their propensity to respond to certain medications and that these propensities could be revealed by QEEG
Summary
Despite unprecedented progress in understanding and treating physical illness, effective medical management of patients with mental health conditions remains among the most daunting and complex population health issues in the United States today. Subsequent findings from studies by Leuchter,[12] Arns,[13,14,15] Pizzagalli,[16] and others confirmed that patients within the same neuropsychiatric disorder might be characterized by their propensity to respond to certain medications (and not others) and that these propensities could be revealed by QEEG These findings were replicated in the recently reported EMBARC (Establishing Moderators and Bio-signatures of Antidepressant Response for Clinical Care) trial at 4 US sites in which more than 300 patients with MDD were evaluated through brain imaging and various DNA, blood, and other tests. With a rapidly growing evidence base (12 randomized controlled trials of QEEG neurometrics for predicting medication response and 88 observational cohort studies), PEER shows promise as a tool to assist physicians in selecting the treatment options that are most likely to be effective for each patient. Results of NNT analyses mirror results of claim-based budget impact models, which show a 4.7 to 1 net cost offset when tools such as PEER are applied to reduce trial and error treatment (Hornberger J; unpublished data; 2017)
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