MISSION VIEJO, Calif., Oct. 10, 2016 (GLOBE NEWSWIRE) — MYnd Analytics, Inc. (OTCQB:CNSOD), which provides a unique set of reference data and analytic tools for clinicians to assist in determining the right therapeutic medication for individuals with mental health disorders, announces today the approval of its CMS application as an Independent Diagnostic Testing Facility (IDTF), providing EEG recording and Quantitative EEG services.

CMS approval will improve patient access to PEER by providing an approved location for EEG testing, facilitating reimbursement under Medicare and Medicaid plans. As the largest purchaser of health care, CMS forecasts that half of reimbursement will be value based by 2018, which the Company believes will favor tools and therapies that enable patients to be treated more quickly with medications suitable to the patient’s individual illness and disease.

“With the recent publication of our military results, and the 42 independent, confirming studies being reported in this month’s Biological Psychiatry, we now move our focus to commercialization and growth. CMS reimbursement is a significant step forward,” said George Carpenter, CEO of MYnd Analytics. “We have generated over 5,000 leads in California from individuals suffering from depression, anxiety and other behavioral disorders who are interested in using PEER technology, and believe removing the financial burden will enable many of them to receive treatment.”

PEER results are available same-day and provide objective, actionable data to support treating physicians. Its foundation is the largest clinical registry of longitudinal patient outcomes, collected from subscribing physicians and patients over more than a decade. In the most recent published randomized, controlled trial PEER technology showed a reduction in suicidality by over 75% when physicians followed PEER recommendations, 2.5 times greater adherence to PEER-recommended therapy, and three times higher medication efficacy than physicians treating as usual without the benefit of PEER.

A core attribute of the PEER registry approach is that it “learns,” using machine-learning algorithms to improve the accuracy of recommendations as outcomes are added to the database. In the last three years, an additional 1,500 patients were added to the PEER Registry, improving overall predictive accuracy from 86% to 91%.

“With the largest database of its kind, and continuous machine-learning, we are uniquely positioned to build the gold standard for personalizing treatment in mental health,” said Carpenter.

About MYnd Analytics, Inc.

MYnd Analytics, Inc. (www.myndanalytics.com) provides a unique set of reference data and analytic tools for clinicians and researchers in psychiatry. While treatment for mental disorders has doubled in the last 20 years, it is estimated that 17 million Americans have failed two or more medication therapies for their mental disorders. The Company’s Psychiatric EEG Evaluation Registry, or PEER Online®, is a registry and reporting platform that allows medical professionals to exchange treatment outcome data for patients referenced to objective neurophysiology data obtained through a standard electroencephalogram (EEG). Based on the Company’s original physician-developed database, there are now more than 38,000 outcomes for over 10,000 unique patients in the PEER registry. The goal of PEER Online is to provide objective, personalized data to assist physicians in the selection of appropriate medications. 

To read more about the benefits of this patented technology for patients, physicians and payers, please visit www.myndanalytics.com.

Safe Harbor Statement Under the Private Securities Litigation Reform Act of 1995

Except for the historical information contained herein, the matters discussed are forward-looking statements made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, as amended. These forward-looking statements involve risks and uncertainties as set forth in the Company’s filings with the Securities and Exchange Commission. These risks and uncertainties could cause actual results to differ materially from any forward-looking statements made herein.

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