Medication Optimization Using Pharmacogenetic Testing and the Genomind Drug Interaction Guide (G-DIG) to Reduce Polypharmacy in a Mental Health Population
Conditions: Pharmacogenetic Testing
Sponsor: Seattle Institute for Biomedical and Clinical Research

Medication Optimization Using Pharmacogenetic Testing and the Genomind Drug 
Interaction Guide (G-DIG) to Reduce Polypharmacy in a Mental Health Population 
MIRB#:  01600 
Funding Agencies: 
Investigator Initiated Grant – Genomind Incorporated 
Seed Grant – VA Research & Development 
Amanda Wood, PhD 
Protocol Version 4;  March 21, 2018 
Human Subjects Protocol 
VA Puget Sound IRB 
VA Puget Sound IRB Approved 
09-05-2018

Protocol Version 4; March 21, 2018  
    VA Puget Sound IRB Protocol Template – Version: 12/2015 Page 2 of 21 
Abstract 
1. Objective(s) and Hypotheses:
Use of polypharmacy has significantly increased over the past two decades, which
has unproven clinical benefit and increased the risk of drug-drug interactions and
adverse side effects. Pharmacogenetic assays have the purported benefit of being
able to predict response(s) to specific medication based on genetic markers.  One
such assay is the Genecept® Assay produced by Genomind, which detects 63 allele
polymorphisms of 18 genes.  In addition, Genomind has developed the Genomind
Drug Interaction Guide (G-DIG), which examines drug-drug-gene interactions.  This
computerized decision tool for medication providers uses the genetic information from
the Genecept Assay to look at the current medications being utilized to determine if
there are specific drug-drug interactions that may be relevant given the individual’s
specific genetic test results.
The study will test the following hypotheses:
1) Use of pharmacogenetic testing and the G-DIG will reduce psychiatric
polypharmacy.
2) Use of pharmacogenetic testing and the G-DIG information provided to
providers will result in changes to the medication treatment plan based on the
new information.
3) Use of pharmacogenetic testing and the G-DIG will improve overall clinical
symptoms as measured by the CGI (secondary analyses).
4) Pharmacogenetic testing and the G-DIG will reduce healthcare costs
associated with medications (secondary analyses).
5) Pharmacogenetic testing will reduce clinical symptoms of anxiety and
depression and improve quality of life (secondary analyses).
2. Research Design:
This is a 12-week open-label, naturalistic study of the provision of pharmacogenetic
testing information to both providers and patients.  Veterans who have been
prescribed polypharmacy and are experiencing a sub-optimal effect will be eligible for
the study.  Medication providers who are participating in the study as sub-investigators
will refer their own patients for the study.  Participating subjects will sign informed
consent and a sample will be obtained in order to complete the pharmacogenomic
testing.  Providers will utilize the pharmacogenetic assay results along with the G-DIG
tool to design an optimized medication regime.  The overall global level of symptoms
and other patient symptoms measures will be administered at baseline, 6-weeks, and
12-weeks.
3. Methodology
Fifty Veterans within the VAPSHCS who are prescribed polypharmacy, as defined as
five or more medications, with at least two prescribed for a mental health diagnosis,
and have a sub-optimal treatment effect will be enrolled in this study.  The provider’s
medication plans will be compared before and after the pharmacogenetic assay
information is provided.  Number of medications will be reviewed to determine any
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Protocol Version 4; March 21, 2018  
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reduction in polypharmacy and healthcare costs.  The clinical global improvement 
scale (CGI) and patient assessments, including measures of depression, anxiety, 
PTSD, insomnia, pain, drug and alcohol use, quality of life, side effects, and 
medication adherence will be administered at baseline, 6-weeks, and 12-weeks. 
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List of Abbreviations 
AE  
Adverse Event  
CRF  
Case Report Form  
DSMB  
Data Safety Monitoring Board  
G-DIG
Genomind Drug Interaction Guide 
HIPAA
Health Insurance Portability & Accountability Act 
IRB
Institutional Review Board  
PHI
Protected Health Information  
PI
Principal Investigator  
PTSD
Post-Traumatic Stress Disorder  
R&D
Research & Development  
SAE
Serious Adverse Event  
Sub-I
Sub Investigator 
TBD
To Be Determined 
VAPSHCS 
VA Puget Sound Health Care System 
VA Puget Sound IRB Approved 
09-05-2018

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Contents 
Protocol Title: .................................................................................................................. 6 
1.0 
Study Personnel .................................................................................................... 6 
2.0 
Introduction ............................................................................................................ 6 
3.0 
Objectives .............................................................................................................. 8 
4.0 
Resources and Personnel ..................................................................................... 9 
5.0 
Study Procedures .................................................................................................. 9 
5.1 Study Design .......................................................................................................... 9 
5.2 Recruitment Methods ........................................................................................... 13 
5.3 Informed Consent Procedures ............................................................................. 14 
5.4 Inclusion/Exclusion Criteria .................................................................................. 14 
5.5 Study Evaluations ................................................................................................ 15 
5.6 Data Analysis ....................................................................................................... 15 
5.7 Withdrawal of Subjects......................................................................................... 16 
6.0 
Reporting ............................................................................................................. 16 
7.0 
Privacy and Confidentiality .................................................................................. 17 
8.0 
Communication Plan ........................................................................................... 17 
9.0 
Information Security and Data Storage/Movement .............................................. 17 
10.0    References…………………………………………………………… ……….……….18 
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Protocol Title:  Medication Optimization Using Pharmacogenetic Testing and the 
Genomind Drug Interaction Guide (G-DIG) to Reduce Polypharmacy 
in a Mental Health Population  
 
1.0 
Study Personnel 
 
Principal Investigator: 
Amanda Wood, PhD  
VA Puget Sound Health Care System, Tacoma, WA 98493 
University of Washington; Dept. of Psychiatry & Behavioral Sciences 
amanda.wood@va.gov 
253-583-1652 
 
Sub-Investigators:  
Luz Starck, MD  
VA Puget Sound Health Care System, Tacoma, WA 98493 
luz.stark@va.gov 
253-583-3171 
 
Collaborators: 
David Krause, MD 
Genomind Inc. 
 
2.0 
Introduction 
 
Prevalence of Polypharmacy:  Use of polypharmacy has significantly increased 
over the past two decades. The National Ambulatory Medical Care Survey from 
1996-2006 found the number of psychotropic medications has significantly 
increased, with a 40.1% increase in the median number of medications 
prescribed (Mojtabai et al., 2010). This increase is even more significant for 
people over the age of 65, with the same survey finding that between 2004 and 
2013, polypharmacy in older adults increased 145% (from 1.50 million to 3.68 
million).  In developed countries, approximately 30% of individuals 65 and older 
are prescribed five or more medications (Qato et al., 2008).   
 
Polypharmacy is becoming more common in mental health populations.  
Individuals with bipolar disorder are at increased risk with approximately 1 in 5 
individuals with bipolar prescribed at least four medications (Goldberg et al., 
2009). Persons with schizophrenia have been shown to be prescribed 
antipsychotic polypharmacy in up to 50% of cases in some settings (Barnes & 
Paton, 2011).  Veterans with PTSD and traumatic brain injury have also been 
shown to be at increased risk for polypharmacy (Collett et al., 2016). 
 
Risks Associated with Inappropriate Polypharmacy:  These increases in 
polypharmacy increase the risk of drug-drug interactions, adverse side effects, 
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with unproven clinical benefit.  Higher levels of antipsychotic daily doses have 
been associated with decrements in information processing speed and verbal 
memory. (Rehse et al., 2016).  Higher doses of antipsychotics may in turn lead to 
additional adverse effects, some of which are commonly treated with 
anticholinergics, leading to additional adverse effects (Barnes & Paton, 2011; 
Minzenberg et al., 2004).  Reducing polypharmacy has been shown to have 
clinical improvements. In a population of individuals with schizophrenia, reducing 
antipsychotic polypharmacy led to improvements in cognition along with 
reductions in symptoms (Kawai et al., 2006).   
 
Older adults may be at particular risk for the dangers of polypharmacy.  
Physiological changes that occur with age alter the pharmacokinetic and 
pharmacodynamics responses to medications, with resulting increased risks for 
polypharmacy as one ages.  These adverse drug events can result in poor 
health, disability, cognitive impairment, hospitalization, increased risk of falls, and 
even death (Rehse et al., 2016; Zia et al., 2015). The number of prescribed 
medications is the single greatest predictor of inappropriate polypharmacy (Scott 
et al., 2015).   
 
Veterans with PTSD and depression with traumatic brain injury may also be a 
risk for polypharmacy. Veterans prescribed polypharmacy have been shown to 
be at increased risk for suicide related behaviors, demonstrating that this is a 
vulnerable population, which may particularly benefit from medication 
optimization (Collett et al., 2016).  
 
Barriers to Reducing Polypharmacy:  Given the risks associated with 
polypharmacy, one might assume that there would be considerable pressure to 
reduce the number of medications, however, prescribers are often reluctant to 
remove medications for fear of destabilizing the patient.  In order to reduce 
polypharmacy and the risks associated with it, several researchers have 
proposed methods by which the current medication regimen is examined and 
inappropriate medications removed (Lavan et al., 2016).  These methods, 
however, are based on medication criteria, logical assumptions, and trial and 
error to gain the optimal medication regimen for each individual patient.   
 
Optimizing Treatment Utilizing Pharmacogenetic Testing:  The use of 
pharmacogenetics in clinical practice is a burgeoning field, but one that needs 
more research in order to determine the clinical and cost effectiveness of the 
receiving the pharmacogenetic test results.  Pharmacogenetic assays have the 
purported benefit of being able to predict response(s) to specific medication 
based on genetic markers, thus, being able to identify medications that cannot be 
effectively processed and should be avoided, along with medications that may 
produce more optimal results.   
 
One such assay in current use is the Genecept® Assay (Genomind, King of 
Prussia, Pennsylvania). The Assay detects 60 allele polymorphisms of 18 genes, 
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of which 12 code for pharmacodynamic proteins, e.g., receptors, transporters, 
enzymes, and ion channels. The remaining 6 genes code for pharmacokinetic 
variants, i.e., CYP450 alleles. Using a proprietary algorithm based on clinical 
data, the Assay suggests treatment options which might be more or less 
appropriate for the specific combination of genotype and indication.    A 
naturalistic study of the use of this assay found that 87% of patients 
demonstrated clinical improvement as measured by the Clinical Global 
Impression Scale (CGI).  Patients also showed decreases in depression, anxiety, 
and medical side effects, along with increases in their quality of life (Brennan et 
al., 2014).  A recent systematic review of pharmacogenetic testing for the 
treatment of depression found that overall there was clinical benefit associated 
with the pharmacogenetic testing, but results for cost effectiveness were mixed 
(Rosenblat et al., 2017). 
 
In addition to the Genecept® Assay, Genomind has developed the Genomind 
Drug Interaction Guide (G-DIG), which examines drug-drug-gene interactions.  
This computerized decision tool for medication providers, uses the genetic 
information from the Genecept® Assay to look at the current medications being 
utilized to determine if there are specific drug-drug interactions that may be 
relevant given the individuals specific genetic test results.  This tool allows 
providers to not only identify medications that are not recommended based on 
their individual genetics, but also drug-drug interactions that may become 
problematic.  Thus, this tool provides valuable information to providers in order to 
develop an optimized medication plan. 
 
In summary, polypharmacy is associated with risks of drug-drug interactions, 
adverse side effects, with unproven clinical benefit. Pharmacogenetic testing may 
be able to predict an individual’s response to medications based on their 
individual genetic results, which may be beneficial in reducing polypharmacy by 
eliminating medications that are not beneficial, leading to medication 
optimization. These pharmacogenetic assays are new to the market and have 
limited research data. The use of this assay to reduce polypharmacy has never 
been tested. 
 
 
3.0 
Objectives 
 
 
The use of polypharmacy in Veterans, especially for the treatment of PTSD and 
traumatic brain injury, has increased over the past two decades, exposing 
Veterans to risks for drug-drug interactions and adverse side effects.  Use of a 
pharmacogenetic tool that could give providers essential information needed to 
optimize Veteran’s medication regimen has the potential to improve Veteran 
health outcomes, reduce risks for adverse events, and reduce treatment utilization 
costs.  
 
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This project is designed to evaluate the effectiveness of pharmacogenetic testing 
in individuals who are prescribed psychiatric polypharmacy.  The study will test 
the following hypotheses: 
 
• Use of pharmacogenetic testing and the G-DIG will reduce psychiatric 
polypharmacy. 
 
• Use of pharmacogenetic testing and the G-DIG information provided to 
providers will result in changes to the medication treatment plan based on 
the new information. 
 
• Use of pharmacogenetic testing and the G-DIG will improve overall clinical 
symptoms as measured by the CGI (secondary analyses). 
 
• Pharmacogenetic testing and the G-DIG will reduce healthcare costs 
associated with medications (secondary analyses). 
 
• Pharmacogenetic testing will reduce clinical symptoms of anxiety and 
depression and improve quality of life (secondary analyses). 
 
4.0 
Resources and Personnel 
 
This research study will be conducted with the VAPSHCS, American Lake 
Division.  All procedures (consent, data collection, data analysis) take place at the 
VAPSHCS and all data will reside within the VAPSHCS system.   
 
Dr. Wood, as the PI, will have overall responsibility for the conduct of the study.  
Dr. Starck will assist in the development of the project, data analysis, and report 
writing.  Dr. Wood will be responsible for study coordination, data analysis and 
report writing. Dr. Starck will assist with project development, protocol writing, 
data analysis, and report writing. Laurie Maus will assist with the maintenance of 
regulatory documents and data management.  The Study Coordinator, Elaine 
Nevins, will be responsible for study coordination, subject consent and study 
assessments, data entry, and data analysis. Additional providers within the 
VAPSHCS may join this study and will refer their own patients to the study.  All 
providers involved in referring patients will be sub-investigators on the study. All 
individuals involved in the study will be trained to protect private health information 
(PHI). 
 
Genomind, Inc. will process the genetic sample and provide access to the 
pharmacogenetic test results from the Genecept® Assay within the G-DIG tool for 
providers. No PHI will be sent to Genomind, with subjects only identified with a 
study number. 
 
5.0 
Study Procedures 
 
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5.1 Study Design 
 
 
This is a 12-week open-label, naturalistic study of the provision of 
pharmacogenetic testing information to both providers and patients.  Veterans 
who have been prescribed polypharmacy and are experiencing a sub-optimal 
effect will be eligible for the study.  Medication providers who are participating 
in the study as sub-investigators will refer their own patients for the study.  
Eligible patients will be given the opportunity to participate in this study.  
Informed consent will be obtained by research staff who are not the potential 
participant’s provider to avoid any undue pressure to participate.   
 
If the potential participant signs consent, a cheek swab sample will be 
obtained in order to complete the pharmacogenomic testing.  The genetic 
information will be sent to Genomind for processing using only a unique study 
number.  No personal health information will be shared with the sponsor.   
Participants will be asked to complete a short battery of psychological 
measures, including measures of depression, anxiety, PTSD, insomnia, pain, 
drug and alcohol use, quality of life, side effects, and medication adherence 
(See Appendix A).   
 
After the participant signs the consent form, they will enter a 2-week baseline 
period.  During theses 2 weeks, the pharmacogenetic test results will be 
available online for providers.  Prior to receiving the results, providers will draft 
an initial medication optimization plan without the benefit of the 
pharmacogenetic information.  The provider will also complete a Clinical 
Global Impression-Severity (CGI-S) rating of overall severity of symptoms for 
their client, and will document the participant’s primary and secondary (if any) 
diagnoses. 
 
When the results of the pharmacogenetic testing are ready, providers will 
review results using a secure web-based program and will utilize the G-DIG 
tool in order to determine the optimal medication regime for the patient, based 
on their individual genetic profile.  Genomind will provide training to all 
investigators prior to the study start regarding the interpretation of the 
pharmacological assay and the use of the G-DIG tool.  Genomind 
representatives will be available throughout the duration of the study for 
consultation regarding the interpretation and implementation of the testing 
results.  For each provider, consultation is mandatory for the first two subjects 
and then available as needed for further subjects.  If the patient is on a 
medication that is not currently listed in the G-DIG, the provider with inform the 
sponsor, and that medication will be added to the G-DIG tool.  All final 
decisions about changing dosage, adding medications, or removing 
medications will be determined by the provider.   
 
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The provider will design an optimized, individualized medication regimen for 
the participant and document this revised plan.  All clinical decisions regarding 
medical treatment and making any changes to medications will be made by 
the treating provider and their patient. Any medications that might be 
recommended by the testing results but are not provided by the VA’s 
pharmacy (not on formulary) will be noted.  Providers will then contact their 
patients by phone, mail, and/or schedule an in-clinic appointment for the 
subject (this can be scheduled at the initial consent appointment) to review the 
pharmacogenetic assay results and implement the medication optimization 
plan.  Any medication changes will be dispensed by the pharmacy either in 
person or can be sent to the participant by mail.  The provider will have 2 
weeks (±2 weeks) to review these results and contact the patient.   
 
After the 2-week baseline, future appointments between the provider and the 
participants will be conducted consistent with treatment as usual.  It is 
recommended that appointments around 6 and 12 weeks (within a three week 
buffer) be scheduled, but this is up to the discretion of the provider and the 
needs of the patient.  The provider will complete a CGI-Improvement (CGI-I) 
measure at appointments within the 6 and 12 week windows, as available.  
 
Study staff will contact the participant at 6 and 12 weeks by phone to conduct 
phone interviews to repeat the measures of depression, anxiety, PTSD, 
insomnia, pain, drug and alcohol use, quality of life, side effects, and 
adherence.  Study staff will also complete a CGI-I assessment.  Study staff 
collecting the participant ratings will be blind to any medication changes made 
until the end of the subject’s participation in the study.  After the 12 week 
assessment, study staff will review the medical record to determine changes in 
medications.  
 
During the consenting process, subjects will be presented with an additional 
consent in order to allow researchers to add the data into a research 
repository. Subjects can chose whether or not to participate. If they do, their 
data will be entered into the repository. If they do not, their data will be kept 
during the time of the study and maintained as per IRB rules and regulations. 
 
Risk/Benefit Ratio: This study naturalistic study presents only a limited risk to 
subjects and is associated with the possible benefits of reducing 
polypharmacy, improving symptoms, and reducing the risk of adverse events. 
Essentially, the only intervention in this study is the provision of additional data 
to the provider that may aid in choosing more appropriate medications.  
 
Potential risks of this study include participants becoming uncomfortable with 
questions asked on the survey, potential for breach of confidentiality, and the 
risk that if the assay provides poor advice, a medication chosen may not have 
the desired effect (of course this is always a risk when prescribing any 
medication and is not exclusive to this study). Since this is a naturalistic study, 
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side effects of medication treatment are an expected part of treatment as usual 
and will be handled by their provider as part of their regular clinical care.   
 
Vulnerable Populations:  This is a naturalistic study, so we are interested in 
opening it up to a representative sample of Veterans in order to evaluate the 
potential benefit of receiving the pharmacogenetic test results.  Since all 
subjects would already have been prescribed polypharmacy, providing their 
medication providers with information about how their body processes 
medications may be helpful to reducing the number of medications and 
potentially improving symptoms and reducing side effects.  This study does not 
recommend the prescribing on any medication.  All decisions regarding 
medication prescriptions will be made by the provider and the participant.  
Thus, vulnerable populations are at no greater risk for participating in the 
study, and participation may actually reduce risks of polypharmacy and the 
potential for adverse effects.  In order to conduct this naturalistic study is it 
essential to enroll persons with mental health diagnoses. However, those 
patients who in the clinical judgment of their provider have impaired decision 
making capacity that may affect their ability to provide informed consent will 
not be enrolled into the study. In addition, those who have a guardian for 
health care decisions will not be enrolled in the study.  Another vulnerable 
population is pregnant women.  Requiring a pregnancy test to exclude women 
who are pregnant would represent an invasion of privacy since this study does 
not represent any known increase risk to an unborn fetus. However, as per 
IRB request, if a woman self-identifies as being pregnant, she will be excluded 
from the study. 
 
 
Study Map: 
 
Procedure 
Initial 
Consent 
Appointment 
Baseline 
Period 
of 2 
weeks 
Week 
6 
Week 
12 
Consent 
X 
  
  
  
Pharmacogenetic testing 
X 
  
  
  
Provider documents initial 
medication plan 
X 
  
  
  
Provider reviews 
pharmacogenetic testing and 
uses G-DIG tool 
  
X 
 
  
Provider develops optimized 
medication plan 
  
X 
  
  
Provider contact patient & 
contacts pharmacy to make 
medication changes as needed 
  
X 
  
  
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Patient measures 
X 
  
X 
X 
     CGI 
X 
  
X 
X 
     Demographics 
X 
  
  
  
     PHQ-9 
X 
  
X 
X 
     GAD-7 
X 
  
X 
X 
     PCL-5 
X 
  
X 
X 
     VR-12 
X 
  
X 
X 
     PEG 
X 
  
X 
X 
     PSEQ 
X 
  
X 
X 
     ISI 
X 
  
X 
X 
     Drug & Alcohol Screening 
X 
  
X 
X 
     Side Effects  
X 
  
X 
X 
     Medication Adherence 
X 
  
X 
X 
 
Pharmacogenetic Sample:  Genomind will provide the Genecept Assay® Test 
Kits for this study.  The kits contain all of the specimen collection and shipping 
materials (e.g. buccal swab, FedEx shipping materials and prepaid shipping 
label).  The biological sample will be collected by cheek swab.  The de-
identified sample will be sent FedEX.  The sample will only be identified with a 
unique assay ID number, that is separate from the study ID number.  All 
samples will be processed by Genomind and the results will be added into the 
G-DIG tool, which can be accessed by the provider through the Genomind 
Clinician Portal, a secure website maintained by Genomind.  Because the 
assay results may provide important information that would be relevant and 
pertinent to more than just the psychiatric medication provider, subjects will be 
given the opportunity to sign a separate release of information to allow 
researchers to share the Genecept assay results with the subject’s other 
medical providers who may benefit from the assay information. Providers may 
also provide the subject with a paper copy of the test results if clinically 
appropriate. The assay will be identified by the unique assay ID number, which 
will be separate from the study ID number. The biological sample itself will be 
destroyed within 90 days by Genomind. Documentation of destruction of the 
biological sample will be provided by Genomind at the end of the study.   
 
 
5.2 Recruitment Methods 
 
Mental health patients within the VA Puget Sound Health Care System who 
have been prescribed polypharmacy will be eligible for this study. All 
providers participating in the study will be sub-investigators on this trial and 
will refer their own patients.  Informed consent will be obtained by study 
staff other than the patient’s own provider to reduce any undue pressure on 
the patient to participate. Patients will be fifty Veterans treated for a mental 
health diagnosis by an enrolled provider, who are prescribed polypharmacy 
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as defined as five or more active medications, with at least two for the 
treatment of a mental health disorder.   
 
Subjects will be identified and recruited by their medication provider who is 
participating in this study as a sub-investigator.  Study staff may assist 
study providers in identifying potential subjects by pre-screening upcoming 
appointments.  When a potential subject has been identified, the study 
provider will introduce the study to the subject at their next clinical visit and 
ask if they would be interested in getting more information about the study, 
providing them with an informational flier.  If the subject is interested, a 
study staff member would speak to the potential subject in a private area, 
review the consent form, and provide an opportunity for the subject to sign 
consent to participate in the study.  
 
The subject will be paid by check the amount of $20 per study visit, for a 
total of $60 if they complete all the visits.  It is expected that the measures 
will take less than an hour to complete, so this payment seems appropriate 
for the amount of time requested of the participant.  Checks will be mailed 
from the VA R&D to the subject’s home. 
 
 
5.3 Informed Consent Procedures 
 
If a potential subject expresses interest in learning more about the study, a 
study staff member will speak to the potential subject in a private area and 
review the consent form.  The potential subject will be encouraged to ask 
questions regarding the study.  At the end of the discussion, potential 
subject will be given the opportunity to sign consent  in order to participate 
in the study or to decline participation.  Potential subjects may also take the 
consent form home and think about whether or not they wish to participate, 
however, this may mean that the provider will delay changing their 
medications until they decide whether or not to participate.  In order to 
minimize any undue pressure or appearance of coercion, a subject’s 
provider will not be the one obtaining informed consent and the consenting 
process will occur in a location separate from the provider. 
 
All individuals obtaining informed consent will be trained to protect PHI and 
will be trained by the PI to obtain and document informed consent. 
Subjects with a legally authorized representative who are not competent to 
sign consent will not be allowed into the study. 
 
During the consenting process, potential participants will also be given the 
opportunity to consent to have their data entered into the mental health 
repository (MIRB#: 00696) and stored indefinitely. This will be handled with 
a separate consent. Participants do not have to sign this additional consent 
to participate. 
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5.4 Inclusion/Exclusion Criteria 
 
 
Inclusion Criteria 
1. Currently receiving outpatient treatment for a mental health 
diagnosis within the VA Puget Sound Health Care System from a 
provider who is a sub-investigator on this study. 
 
2. Currently experiencing a sub-optimal medication response as 
assessed by either continued symptoms or medication side 
effects, which in the opinion of their treating provider would 
indicate a change in medications would be warranted. 
 
3. Currently prescribed polypharmacy, as defined as five or more 
medications, with at least two being for a mental health 
diagnosis. Also allowable would be one medication for a mental 
health diagnosis and another medication for side effects related 
to a medication prescribed for the mental health diagnosis. 
 
4. Between the ages of 18 and 75. 
 
 
Exclusion Criteria 
1.  Any mental or physical health diagnosis, which in the opinion of 
their treating prescriber would prevent them from being compliant 
on a medication regimen or being able to complete the study 
measures. 
 
2. Current/active diagnosis of severe alcohol or drug use disorder. 
 
3. Serious medical or mental health symptoms requiring immediate 
stabilization and/or hospitalization. 
 
4. Impaired decision making capacity that in the clinical judgement 
of their provider would affect their ability to provide informed 
consent. 
 
5. Self-identification as being currently pregnant. 
 
5.5 Study Evaluations 
 
Measures:   
The primary measure to determine clinical effectiveness is the Clinical 
Global Improvement Scale. This scale will be completed both by the 
provider and the study coordinator (or study personnel collecting the 
assessment measures).  
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The number of medications and treatment utilization will be collected by 
chart review of the subject’s medical record at baseline and at 12 weeks to 
determine any change in the number and type of medications prescribed.  
 
Any differences between the initial medication plan developed by the 
provider prior to receiving the pharmacogenetic assay results, the 
medication optimization plan developed by the provider after the use of the 
G-DIG tool, and actual clinical practice will be noted.  The number and cost 
of medication changes will also be evaluated.   
 
Participant assessments administered at baseline, 6 and 12 weeks will 
include measures from the Behavioral Health Lab (BHL; Oslin et al., 2006). 
These measures will include a demographic questionnaire, GAD-7 
(Anxiety), PHQ-9 (Depression), PCL-5 (PTSD), Insomnia Severity Index, 
Chronic Pain, Screening for Alcohol and Drug use, RAND Health Survey, 
and Side Effects and Adherence (See Appendix A).  The results of the BHL 
assessments will be placed into the subject’s medical record. Participants 
will also be asked about smoking. 
 
5.6 Data Analysis 
 
Analysis Plan and Power Calculations:  The primary and secondary 
hypotheses will be calculated using within group t-tests using the Statistical 
Package for the Social Sciences (SPSS).  A statistical power analysis was 
performed for sample size estimation.  The effect size was estimated to be 
medium (0.50) using Cohen's (1988) criteria. With an alpha = .05 and 
power = 0.80, the projected sample size needed with this effect size is 
approximately N = 34 to conduct a single sample t-test. Thus, our proposed 
sample size of N = 50 should be more than adequate to analyze the main 
hypothesis for this study and should also allow for expected attrition and 
the analysis of our secondary hypotheses.     
 
Interpretation:  Interpretation of these hypotheses should demonstrate 
whether the Genecept® Assay and the G-DIG tool are beneficial to Veteran 
prescribed polypharmacy in order to reduce polypharmacy and improve 
clinical symptoms.  The primary limitation to this study is that there is no 
control group, so attribution of any change to the pharmacogenetic assay 
should be done with reservations.  If this study shows promising results, 
future studies should include a randomized control group.  Another 
limitation is sample size.  Though with our estimated effect size, we should 
have power to detect significance, larger sample sizes are preferred to 
increase generalizability to a larger population. 
 
 
5.7 Withdrawal of Subjects 
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Participants can choose at any time to cease their participation in the study 
by informing the study PI of their intention to do so.  Any information 
collected up to that point will remain in the database. 
 
6.0 
Reporting 
Since this is a naturalistic study, potential side effects to medications are an 
adverse event that is expected as part of treatment as usual.  The study will 
collect information on side effects in the study measures.  All concerns 
regarding side effects will be referred back to their treating provider for follow-
up.  In the case that the participant reveals an emergent mental or physical 
health issue, such as suicidal ideation, the participant will be treated as per 
clinical guidelines within the VA, and their immediate needs addressed as one 
would for any other clinical patient.  Their provider will be contacted for 
intervention and follow-up as needed. 
 
In the case of a Serious Adverse Event, these will be reported to the IRB as per 
current regulations.  Genomind partners may also be informed.  Definition of a 
Serious Adverse Event will follow IRB regulations and includes life-threatening 
situations, death, hospitalization, persistent or significant disability or incapacity, 
or a congenital anomaly or birth defect. 
 
All study records will be kept with a code, not the participant's identifying 
information to reduce the chance of an unintended breach in confidentiality.  
This study includes the genetic sample sent to Genomind to conduct the genetic 
testing. This sample will be sent only with a study code, not the participant’s 
name.  The sample will be used only for the purposes of the study and will be 
destroyed within 60 days by Genomind. 
 
7.0 
Privacy and Confidentiality 
 
All study records will be kept with a code, not the participant's identifying 
information to reduce the chance of an unintended breach in confidentiality. The 
data will be stored securely, and individuals not associated with the study will not 
have access to data. Identifying information, such as consent forms, will be kept 
separately from study data.  
 
This study includes genetic samples sent to Genomind to conduct the genetic 
testing. This sample will be sent only with a study code, not the participant’s 
name.  The sample will be used only for the purposes of the study and will be 
destroyed within 60 days by Genomind.  De-identified data in the form of the 
pharmacogenetic test results will be available to providers on a secure website 
maintained by Genomind.  The test results will be kept indefinitely. 
 
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8.0 
Communication Plan 
 
Currently, the VA Puget Sound Health Care System is the only site conducting 
this study.  Genomind will be notified of any serious adverse events, however no 
PHI will be shared. 
 
 
9.0      Information Security and Data Storage/Movement 
 
Hard copies of CRFs will be maintained in research offices at the American Lake 
Division of the VA Puget Sound Health Care System. Electronic data will be kept 
with the VAPSHCS computer system and will be restricted to allow access to only 
research personnel.  The genetic sample sent to Genomind will be sent FedEx 
and will be de-identified. 
 
After this study is closed, research data will be entered into the Mental Health 
Research Repository maintained by Dr. Wood for participants who have signed 
that additional consent.  Anyone who has not signed the additional repository 
consent will not have their data entered into the repository, and the data will be 
kept as per R&D guidelines.  Additionally, there are no plans to destroy the de-
identified data from the Genecept Assay; the testing data will be stored 
indefinitely. 
 
 
 
 
10.0 References 
 
Barnes TRE & Paton C. (2011). Antipsychotic polypharmacy in schizophrenia. 
CNS drugs, 25(6), 383-399.  
 
Bastien CH, Vallieres A, Morin CM. (2001). Validation of the Insomnia Severity 
Index as an outcome measure for insomnia research. Sleep Med, 2, 297–307. 
 
Brennan FX, Gardner KR, Lombard DO, Perlis RY, Fava M, Harris HW, Scott R. 
(2015). A naturalistic study of the effectiveness of pharmacogenetic testing to 
guide treatment in psychiatric patients with mood and anxiety disorders. Prim 
Care Companion CNS Disord, 17(2), doi:  10.4088/PCC.14m01717. 
 
Collett GA, Song K, Jaramillo CA, Potter JS, Finley EP, Pugh MJ. (2016). 
Prevalence of central nervous system polypharmacy and associations with 
overdose and suicide-related behaviors in Iraq and Afghanistan war Veterans in 
VA care 2010-2011. Drugs–Real World Outcome, 3, 45-52. 
 
Goldberg JF, Brooks JO, Kurita K, Hoblyn JC, Ghaemi SN, Perlis RH, Miklowitz 
DJ, Ketter TA, Sachs GS, Thase ME. (2009). Depressive illness burden 
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associated with complex polypharmacy in patients with bipolar disorder: findings 
from the STEP-BD. Journal of Clinical Psychiatry, 70(2), 155-62. 
 
Guy W, editor. ECDEU Assessment Manual for Psychopharmacology. 1976. 
Rockville, MD, U.S. Department of Health, Education, and Welfare. 
 
Kawai N, Yamakawa Y, Baba A, Nemoto K, Tachikawa H, Hori T, Asada T, 
Iidaka T. (2006). High-dose of multiple antipsychotics and cognitive function in 
schizophrenia: the effect of dose-reduction. Prog Neuropsychopharmacol Biol 
Psychiatry, 30(6), 1009-14. 
 
Kazis LE, Miller DR, Clark JA, et al. (2004). Improving the response choices on 
the veterans Sf‐36 health survey role functioning scales: results from the 
veterans health study. J Ambul Care Manage, 27(3), 263–80. 
 
Krebs EE, Lorenz KA, Bair MJ, Damush TM, Wu J, Sutherland JM, Asch SM, 
Kroenke K. (2009). Development and initial validation of the PEG, a three-item 
scale assessing pain intensity and interference. J Gen Intern Med, 24(6), 733-8. 
 
Lavan AH, Gallagher PF, O'Mahony D. (2016). Methods to reduce prescribing 
errors in elderly patients with multimorbidity.  Clin Interv Aging, 11, 857-66.  
 
Minzenberg MJ, Poole JH, Benton C, Vinogradov S. (2004). Association of 
anticholinergic load with impairment of complex attention and memory in 
schizophrenia. Am J Psychiatry, 161(1), 116-24. 
 
Mojtabai R & Olfson M. (2010). National trends in psychotropic medication 
polypharmacy in office-based psychiatry. Arch Gen Psychiatry, 67(1), 26-36. 
 
Nicholas MK, McGuire BE, Asghari A. (2015).  A 2-item short form of the Pain 
Self-efficacy Questionnaire: development and psychometric evaluation of PSEQ-
2.  Journal of Pain, 16(2), 153-63. 
 
Oslin, D. W., Ross, J., Sayers, S., Murphy, J., Kane, V., & Katz, I. R. (2006). 
Screening, assessment, and management of depression in VA primary care 
clinics. The Behavioral Health Laboratory. Journal of General Internal Medicine, 
21(1), 46-50. 
 
Qato DM, Alexander GC, Conti RM, Johnson M, Schumm P, Lindau ST. (2008). 
Use of prescription and over-the-counter medications and dietary supplements 
among older adults in the United States. JAMA, 300(24), 2867-2878. 
 
Rehse M, Bartolovic M, Baum K, Richter D, Weisbrod M, Roesch-Ely D. (2016). 
Influence of Antipsychotic and Anticholinergic Loads on Cognitive Functions in 
Patients with Schizophrenia. Schizophr Res Treatment. Epub Apr 10.2016. doi: 
10.1155/2016/8213165. 
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Rosenblat JD, Lee Y, McIntyre RS. (2017). Does Pharmacogenomic Testing 
Improve Clinical Outcomes for Major Depressive Disorder? A Systematic Review 
of Clinical Trials and Cost-Effectiveness Studies. J Clin Psychiatry. Epub ahead 
of print. doi: 10.4088/JCP.15r10583. 
 
 
Scott IA, Hilmer SN, Reeve E, Potter K, Le Couteur D, Rigby D, Gnjidic D, Del 
Mar CB, Roughead EE, Jansen J, Martin JH. (2015). Reducing inappropriate 
polypharmacy: the process of deprescribing. JAMA Intern Med, 175(5), 827-34. 
 
Selim A, Rogers W, Fleishman J, et al. (2009). Updated U.S. Population 
standard for the veterans rand 12-item health survey (Vr-12). Qual Life Res, 
18(1), 43–52. 
 
Zia A, Kamaruzzaman SB, Tan MP. (2015). Polypharmacy and falls in older 
people: Balancing evidence-based medicine against falls risk. Postgrad Med, 
127(3), 330-7. 
 
 
11.0    Appendix A:  Measures 
 
Clinical Global Impression (CGI): The CGI (Guy, 1976) is a widely used measure 
of overall psychiatric function and improvement.  It is a clinician-rated two-item 
measure, consisting of a 7-point scale to measure clinical global impression of 
psychiatric illness and clinical global improvement. The first item will be rated at 
baseline, and both items will be scored for all subsequent assessments. 
 
Patient Health Questionnaire – 9 (PHQ-9):  The PHQ-9 (Kroenke et al., 2001) is 
self-report, nine-item screening tool for depression.  The tool rates the frequency 
of depressive symptoms based on DSM-5 criteria for major depression. The PHQ-
9 has been shown to have a sensitivity of 88% and specificity of 88% for Major 
Depression, with a Cronbach alpha of .89 (Kroenke et al., 2001). 
 
Generalized Anxiety Disorder Assessment (GAD-7): The GAD-7 (Spitzer et al., 
2006) is a 7-item self-report measure of general anxiety. It has been shown to 
have a 89% sensitivity and a 82% specificity for identifying general anxiety 
disorder, based on DSM-5. 
 
PTSD Checklist for DSM-5 (PCL-5):  The PCL-5 (Blevins et al., 2015) is a 20-item 
self-report measure of PTSD symptoms based on DSM-5 criteria. It also 
measures the severity of symptoms on a Likert scale.  
 
Veteran RAND 12-Item Health Survey (VR-12): The VR-12 (Kazis et al., 2004; 
Selim et al., 2009) is a 12-item instrument primarily used to measure health 
related quality of life and disease burden. The instrument summarizes both 
physical health and mental health influences on overall quality of life.  The VR-12 
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was derived from the Veterans RAND 36 Item Health Survey and has been used 
extensively with a Veteran population. 
 
Chronic Pain (PEG):  The PEG is a three-item scale of pain, derived from the Brief 
Pain Inventory, and includes items of pain intensity (P), interference with 
enjoyment of life (E), and interference with general activity (G). Overall, reliability 
of the PEG was good (0.73 and 0.89 in two samples).  Construct validity for the 
PEG was also good for pain-specific measures (Krebs et al., 2009). 
 
2-Item Pain Self-Efficacy Questionnaire (PSEQ):  The PSEQ is a 2-item 
questionnaire of pain, derived from the 10-item PSEQ.  The 2-item scale has 
shown good validity and internal consistency, and had good convergent validity 
(Nicholas et al., 2015).  
 
Insomnia Severity Index (ISI) – The ISI (Bastien et al., 2001) is a brief screening 
of insomnia and is designed to be used as a research outcome measure.  The 
scale in based on the DSM-IV criteria for insomnia and measures the individual’s 
difficult with falling asleep, staying asleep, or waking early in the past two week.  
Additional questions ask about sleep satisfaction and the impact of their sleep 
problems on their quality of life. 
 
Drug and Alcohol Screening:  These brief screening tools for drug and alcohol use 
include questions regarding the use of alcohol in the past year and the use of 
drugs of abuse in their lifetime and then how often they used any drug mentioned 
in the past three months.  This measure is included as part of the BHL (Oslin et 
al., 2006). 
 
Demographic Questionnaire:  A standard measure of demographic will obtain 
information regarding age, gender, race/ethnicity, level of education, current 
housing, current employment, and military service.  This questionnaire also 
queries about smoking.  These questions will be asked only once at baseline This 
measure is included as part of the BHL (Oslin et al., 2006). 
 
Side Effects and Medication Adherence: participants will be queried on their 
actual adherence to the medications prescribed, actual dose taken, and doses 
skipped, will be queried.  They will also be asked about common side effects and 
be given an opportunity to report any other side effect that they are experiencing. 
This measure is included as part of the BHL (Oslin et al., 2006). 
VA Puget Sound IRB Approved 
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