“Gender Differences in Prescribing among 

Veterans Diagnosed with Posttraumatic 

Stress Disorder”

Nancy C. Bernardy, Ph.D., 

VA National Center for PTSD

 

 
Acknowledge

• My mentor and collaborator, Dr. Matthew J. Friedman, past 

Executive Director and now consultant, NCPTSD

• Our pharmacy colleagues in the Iowa City VA Medical Center, 

Drs. Brian Lund and Bruce Alexander, Ms. Aaron Jenkyn, my 

invaluable research assistant and Dr. Paula Schnurr who 

suggested that I explore the topic of gender differences in 

prescribing in PTSD

• Funding from the Department of Veterans Affairs Mental 

Health, the PT/BRI and the SUD QUERI programs

2 
Objectives

• Briefly review first line recommended 

treatments for PTSD, particularly guidance 

regarding benzodiazepines and our work 

examining prescribing practices in PTSD 

• Discuss gender-specific findings and 

possible explanations

• Share new work focused on polysedatives 

and implications for the way forward

3 
Poll Question #1

• What is your primary role in VA? 

– student, trainee, or fellow

– mental health clinician

– primary care clinician

– researcher 

– administrative, manager or policy-maker 

– other 
Pharmacotherapy for PTSD: Summary

Balance = Benefit - Harm

SR SUBSTANTIAL SOMEWHAT UNKNOWN NONE or HARM

A SSRIs, SNRIs

B Mirtazapine, TCAs, 

MAOIs (phenelzine), 

Prazosin (nightmares), 

Nefazodone (caution) 

C Prazosin (PTSD)

D Guanfacine, Topiramate, 

Valproate, Tiagabine

Benzodiazepines (harm) 

Risperidone (adjunct)

I Buspirone, Bupropion, 

Non-benzodiazepine 

Hypnotics, Lamotrigine, 

Gabapentin, Clonidine, 

Trazodone (adjunct),

Atypical antipsychotics (mono),

Atypical antipsychotics 

(besides Risperidone) (adjunct) 

Conventional antipsychotics, 

Propranolol 

5 

SR = Strength of recommendation

(Full Guideline, p. 149)

http://www.healthquality.va.gov/guidelines/MH/ptsd/
Problem with this Guidance

• Role of benzodiazepines in PTSD management remains 

contentious

• What small clinical trials have been done showed no 

benefit in alleviating or preventing PTSD symptoms 

• Evidence-based literature regarding the significant risks of 

chronic benzodiazepines is large and very, very clear and is 

growing rapidly

• Lack of evidence of efficacy plus clearly evidenced high 

risk profile support the PTSD Clinical Practice Guideline 

recommendation 

6 
Benzodiazepines in PTSD

– Commonly prescribed to manage insomnia and anxiety but there are now 

better treatment options – both medications and psychotherapy

– Two common comorbidities, mTBI and SUD, are contraindications to 

benzodiazepine use

– Some clinical evidence that benzodiazepines can reduce the effectiveness 

of evidence-based cognitive behavioral treatments (CBT) in real world 

patients 

– Tolerance, dependence, withdrawal symptoms and dramatic rebound are 

concerns but most adverse effect may be cognitive “fogginess”

• New evidence suggests increased risk of dementia (de Gage et al., 2012), 

increased detrimental effects on immune system (Huang et al., 2014), and 

significantly higher ratios for mortality associated with long term use of 

benzodiazepines prescribed for sleep (Weich et al., 2014)

7 
VA’s Commitment to Women’s Health 

Needs 

• Women are now the fastest growing cohort 

within the Veteran community

• Represent approximately 16% of 

OEF/OIF/OND

• Virtually no work conducted to examine the 

role of pharmacotherapy in management of 

PTSD in women Veterans

8 
Total number of Veterans in VHA with a 

diagnosis of PTSD, by year

9 

0

100000

200000

300000

400000

500000

600000

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Number

Total

Male

Female

485,917 

49,589

535,506
Percentage of Veterans in VHA with a 

diagnosis of PTSD, by year

10

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Percentage

Total

Male

Female

9.6%, 

9.4% 

13%
POLL Question 1

What method do you prefer for learning new clinical information?

A. Webinar such as this

B. Written materials, study books or journal articles

C. Mobile Applications on Smart Phone or iPad-like device

D. Live Lecture Grand Rounds with case presentations

E. Face-to-face discussion such as that with a pharmaceutical company 

representative or staff member

11
Declining Benzodiazepine Use in 

Veterans with PTSD

12

Is Benzodiazepine Use Increasing or Decreasing? 

(Lund et al., 2012)
Prescribing Trends in Veterans with 

PTSD

Results – a Good News Story?

– Proportion receiving either SSRI and SNRI, top 2 

recommended pharmacotherapy treatments for 

PTSD increased from 49.7% in 1999 to 58.9% in 

2009 – this increase represents more than 46,000 

Veterans receiving these meds

– In addition to reduced BZ prescribing, overall 

frequency of antipsychotic use declined 6.1% from 

20% in 1999 to 13.9% in 2009

– Nonbenzodiazepine hypnotic prescribing tripled 

when zolpidem (Ambien) was added to formulary in 

2008. 

13
General Prescribing Trends in PTSD

14

0%

10%

20%

30%

40%

50%

60%

70%

99 00 01 02 03 04 05 06 07 08 09

Frequency of use

Fiscal Year

SSRI or SNRI Benzodiazepines

Atypical Antipsychotics Quetiapine, low dose

Zolpidem Prazosin

Frequency of Medication Use by Drug Class and Fiscal Year 

(Bernardy et al., 2012) 
Where the Medications were 

Prescribed

1. 70% of prescribing of SSRI/SNRIs to Veterans with PTSD (65.7%) 

was attributable to mental health care providers

2. 80% of prescribing of atypical antipsychotics to these Veterans 

(25.6%) was from mental health care providers

3. Benzodiazepines were prescribed for 37.0% of the sample and 

69% of the prescribing was again from mental health prescribers

4. Confirmed that Veterans with PTSD are frequently prescribed 

medications not supported by the guidelines and most of the 

prescriptions are written by mental health care providers

Abrams et al., 2013 15
Identify Predictors Associated with 

Benzodiazepine Prescribing

Patient Level Correlates of Benzodiazepine Use: Univariate Comparisons (FY09)

16

Patient Characteristic Benzodiazepine

Characteristic Frequency Frequency OR (95% CI)

Women 7.5% 38.3% 1.47 (1.43, 

1.50) 

Age ≥ 30 years 89.0% 31.6% Reference

Rural 26.9% 33.2% Reference

Service connection ≥ 

50% 

55.0% 35.5% 1.72 (1.70, 

1.75) 

Vietnam era 56.2% 32.3% Reference

≥ 3 year duration 54.7% 36.0% Reference

(Lund et al., 2013)
Gender Differences Background

• Women disproportionately receive prescriptions for 

psychotropic medications (1 in 4 American women 

compared to 15% of men)

• Particularly true of anti-anxiety drugs where approx. 11% 

of women (ages 45-64) received benzodiazepines in 2010 

compared to a rate half that seen in men (5.7%)

• Women suffer more frequently from psychiatric disorders 

than men

• Greater diagnostic frequency, gender differences in 

acceptance/receipt of mental health treatment, or 

gender-based inequity?

17
General Methodology

• Time period

– Fiscal years (FY) 1999 through 2009 

• Patients

– Veterans with ≥ 1 encounter coded for PTSD ICD-9 code 

(309.81) from inpatient discharges and outpatient 

encounters

• Medication use based on at least one outpatient 

prescription record of any days supply and 

included SSRIs, SNRIs, atypical antipsychotics, 

benzodiazepines, non-benzodiazepine hypnotics 

and prazosin 18
Demographic characteristics

Variable Mean, % in women Mean, % in men

Age 43.3 +/- 11.9* 54.7 +/- 14.5 

Urban residence 79.6%* 72.6% 

Post Vietnam era 86.4% 33.3% 

Service connection >50% 46.5% 55.6%* 

PTSD diagnosis duration*

 New diagnosis 26.2% 21.7% 

 1-2 years 25.2% 23.1% 

 3+ years 48.6% 55.2% 

19

*<0.0001
Comorbidity characteristics

Variable Mean, % in women Mean, % in men

Depressive disorder 65.6%* 47.3% 

Anxiety disorder, any 14.8%* 7.5% 

Panic disorder 8.2%* 3.5% 

GAD 6.2%* 3.8% 

OCD 1.8%* 0.7% 

Social phobia 0.4%* 0.3% 

Substance use disorder 17.8% 22.8%* 

Traumatic brain injury 3.4% 4.5%* 

20

*<0.0001
21

Gender Differences in Prescribing Trends

FY99 FY03 FY07 FY09

SSRI/SNRI

Women 56.4% 68.4% 66.1% 65.7%

Men 49.2% 58.0% 58.2% 58.3%

OR (95% CI) 1.34 (1.28, 1.39) 1.57 (1.51, 1.62) 1.40 (1.36, 1.44) 1.37 (1.34, 1.40)

Benzodiazepines

Women 33.4% 37.3% 39.1% 38.3%

Men 36.7% 33.4% 31.3% 29.8%

OR (95% CI) 0.86 (0.83, 0.90) 1.18 (1.14, 1.23) 1.41 (1.38, 1.45) 1.47 (1.43, 1.50)

Atypical antipsychotics

Women 14.6% 27.6% 26.6% 26.3%

Men 14.1% 25.1% 22.5% 21.3%

OR (95% CI) 1.05 (0.99, 1.11) 1.14 (1.10, 1.18) 1.25 (1.22, 1.29) 1.31 (1.28, 1.35)

Zolpidem

Women 3.8% 5.6% 6.1% 16.9%

Men 3.8% 4.3% 4.2% 12.4%

OR (95% CI) 1.02 (0.92, 1.13) 1.33 (1.24, 1.43) 1.48 (1.40, 1.56) 1.43 (1.39,1.48)

Prazosin

Women 0.2% 1.9% 5.0% 7.1%

Men 1.5% 2.6% 6.4% 9.3%

OR (95% CI) 0.14 (0.09, 0.21) 0.73 (0.64, 0.82) 0.76 (0.72, 0.80) 0.75 (0.72, 0.78)

(Bernardy et al., 2013) 
22
Independent Predictors of Gender 

Differences in Prescribing

• Demographic characteristics and psychiatric comorbidities 

were examined for SSRIs, benzodiazepines and atypical 

antipsychotics 

• Age had substantial impact on BZs and AAs – younger 

reproductive-age women had lower rates of receipt of both, 

increased with age for BZs 

• AAs showed an inverted U pattern where lower rates were 

seen in younger, increased in middle age and decreased in 

older for both men and women 

• An increased percentage of VA service-connected disability 

(>50%) contributed to an increase in prescribing of all 

medications for both men and women

23
Independent Predictors of 

Prescribing

• Psychiatric comorbidity has significant impact

• Likelihood of SSRI/SNRI use was 3-fold higher in patients with 

co-occurring depressive disorder

• BZ use was more common for all anxiety disorder 

comorbidities, particularly with panic disorder

• Elevated prescribing of AAs was observed in both men and 

women with co-occurring SUD

• TBI was associated with increased prescribing across all 

classes except for SSRI use in women

• Benzodiazepine use was actually higher for women with cooccurring SUD whereas the opposite was true for men

24
25

Gender differences in prescribing among 

Veterans diagnosed with PTSD

SSRI/SNRI Benzodiazepines Atypical Antipsychotics

Model OR 

(95% CI) *

c statistic OR 

(95% CI)

c statistic OR 

(95% CI)

c statistic

Unadjusted 1.37 

(1.34, 1.40)

0.511 1.47 

(1.43, 1.50)

0.514 1.31 

(1.28, 1.35)

0.510 

Demographics 

only

1.34 

(1.31, 1.37)

0.567 1.63 

(1.60, 1.67)

0.608 1.08 

(1.05, 1.10)

0.605 

Comorbidity 

only

1.13 

(1.10, 1.15)

0.630 1.27 

(1.24, 1.30)

0.590 1.25 

(1.22, 1.28)

0.607 

Demographics 

and comorbidity

1.15 

(1.12, 1.18)

0.658 1.47 

(1.44, 1.51)

0.653 1.08 

(1.05, 1.11)

0.652 

* Odds-ratio and 95% confidence interval for the likelihood of receiving medication in women compared to men
Gender Differences in Prescribing 

SSRIs/SNRIs

• Women Veterans were more likely to receive 

psychotropic medications across all classes 

except prazosin which was more likely in men

• Substantial increases in SSRI/SNRIs reflect a 

positive shift to evidence-based care – 

additional 18,388 women receiving first-line 

recommended medications

• When adjusted for comorbidities, still higher 

frequencies of SSRIs/SNRIs in women 

26
Prescribing of Atypical 

Antipsychotics 

• Observed comparable guideline-concordance prescription 

patterns with atypical antipsychotics with similar gender 

frequencies until a shift occurred in 2003 that saw an 

increase for women that stayed elevated compared to 

men

• When adjusted for demographic characteristics, still 

elevations in frequency for women not accounted for by 

more severe service-connected disability

• May target insomnia symptoms in women as there is 

evidence of gender differences in arousal symptoms

• Atypical antipsychotics were recommended adjunctively 

to SSRIs in CPG before modified in 2012 but concerns 

about side effects should be considered

27
Prescribing of Benzodiazepines

• Significant exception

• Decreased prescribing in men, steady increases for 

women despite CPG recommendations of harm

• Not only did we observe increased rates of prescribing in 

women but in women with co-occurring SUD and TBI 

where contraindicated, elevations were seen

• Age appeared to also be a related factor: reduced 

prescribing in reproductive-age group encouraging but 

being older and having a greater service connection 

contributed to elevated prescribing

28
Possible Reasons for this 

Discrepancy (Disparity?)

• Women may exhibit higher rates of distress (King et al., 2013); 

Men report more nightmares, numbing and hypervigilence 

• Clinicians may also prescribe benzodiazepines for symptoms 

that are not an indication for their use such as headache, 

fatigue, chest pain and vertigo 

• Sleep symptom management is clearly playing a role 

– Extraordinary 10% increase in zolpidem use in women from 2007 to 

2009 confirms how much sleep difficulties are part of the clinical 

presentation of PTSD and this may not be a good substitute

– Not clear why prazosin use would be the exception and more widely 

used in men

29
Possible Reasons for this 

Discrepancy

• Gender-specific mechanisms have been suggested to underlie 

relationship between sleep impairment and development of 

PTSD (Kobayashi, 2013)

• Research suggests discrepant findings but overall, appears to 

suggest that males with PTSD report more PTSD-related sleep 

disturbances 

• In other words, PTSD may not be driving the discrepancy in 

women but it may be age and gender factors contributing to 

this – again, are women more willing to take medications for 

sleep?

30
Limitations

• Use of administrative data allows us to 

examine these trends but not to fully 

determine justification for use

• Were able to capture important 

comorbidities but not insomnia symptoms 

associated with PTSD

• Other co-occurring disorders may be 

relevant that were not captured

• Nor can we confirm the timing (current 

active or history) or severity of the co-

31
Conclusions

• Important to explore reasons for increased prescribing of 

benzodiazepines for women with PTSD

• Complexity of patients may cause clinicians to respond to 

treatment failures by indiscriminately trying different, 

non-recommended medications

• Important to look at gender differences in response to 

cognitive-behavioral therapy for insomnia (CBT-I)

• Provider education is sorely needed for this reproductiveaged cohort to inform clinicians about gender differences 

in side effects, dosing and sex differences in 

pharmacokinetics of psychotropic medications to ensure 

quality PTSD care for our Veteran women

32
POLL Question 3

Provider Prescribing Report Cards Used as 

Audit and Feedback in PTSD Care

Do you think these tools would be:

A. Helpful for showing providers they are outliers in their prescribing

B. Not used because the data is too difficult to acquire in our healthcare 

practice

C. A bad idea, as they just cause providers to get upset when they see 

someone is looking at their prescribing.

33
Polysedative Prescribing

• PTSD treatment is often complicated by cooccurring conditions including pain, insomnia, 

brain injury and other MH disorders

• Pharmacologic approaches to these conditions 

can produce an accumulation of sedating 

medications with potential for safety concerns

34
Background

• Unfortunately the evidence base concerning coordinated 

treatment recommendations for these co-occurring 

conditions is limited.

– Seal (2012) noted among OEF/OIF Veterans with chronic pain, the 

presence of PTSD was associated with increased likelihood of opioid 

prescribing, as well as high risk behaviors and adverse outcomes.

– This study also showed that those with PTSD were more likely to receive 

2 or more opioids concurrently, as well as sedative hypnotics and opioids 

concurrently. 

– A small cross-sectional study found that 47% of Veterans with PTSD 

taking benzodiazepines were concurrently prescribed opioids (Hawkins, 

2012). 

– Recent work by Dr. Park and others in the VA noted considerable regional 

variability of overlap of benzodiazepines and opioid agonist therapies 

(2014) 

35
Demographic Subgroups

 Benzodiazepines Opioids

Demographic Characteristic Prevalence Incidence Prevalence Incidence

Sex 

Men (n=332,957) 33.8% 4.5% 34.7% 5.8%

Women (n=26,034) 44.4% 6.5% 38.1% 6.2%

Age group 

Adults, <65 yrs (n=283,757) 35.5% 4.8% 36.7% 5.9%

Older adults (n=75,234) 31.2% 3.9% 28.2% 5.8%

Residence 

Urban (n=251,380) 33.6% 4.6% 33.6% 5.7%

Rural (n=102,494) 36.2% 4.7% 38.6% 6.2%

Race/ethnicity 

White (n=231,699) 38.4% 4.7% 36.8% 5.9%

Black (n=62,498) 21.9% 4.5% 32.1% 6.0%

Hispanic (n=23,289) 36.6% 4.7% 30.3% 5.6%

Asian (n=5,707) 31.9% 4.9% 31.2% 6.2%

Native American (n=3,690) 33.0% 4.3% 44.0% 6.9%

Unknown (n=32,108) 31.1% 3.9% 30.0% 5.4%

36
Period Prevalence of any 

Concurrent Polysedative Use

Number of concurrent 

sedative classes

2004, N=165,391

n (%)

2011, N=358,992

n (%)

None 41 837 (25.3%) 91 709 (25.6%)

1 66 988 (40.5%) 136 067 (37.9%)

2 40 440 (24.5%) 87 842 (24.5%)

3 13 607 (8.2%) 34 620 (9.6%)

4 2 422 (1.5%) 7 997 (2.2%)

5 97 (0.1%) 757 (0.2%)

≥ 1 123 554 (74.7%) 267 283 (74.4%)

≥ 2 56 566 (34.2%) 131 216 (36.6%)

≥ 3 16 126 (9.8%) 43 374 (12.1%)

37
Trends in Sedative Use

Figure. Period prevalence and incidence in sedative prescribing

38
Frequency of Concurrent Polysedative Use 

Stratified by Demographic Subgroup

 2004 2011

Demographic Characteristic 2 or more 3 or more 2 or more 3 or more

Sex 

Men 33.6% 9.4% 35.5% 11.4%

Women 46.7% 15.7% 49.7% 20.8%

Age group 

Adults, <65 yrs 37.2% 11.1% 39.6% 13.6%

Older adults, >= 65 yrs 20.4% 3.6% 25.2% 6.3%

Residence 

Urban 33.4% 9.5% 35.7% 11.6%

Rural 35.9% 10.4% 38.3% 13.1%

Race 

Native American 39.4% 12.4% 41.0% 14.3%

White 37.2% 11.2% 39.0% 13.4%

Hispanic 34.6% 8.5% 36.2% 11.7%

Asian 29.7% 7.5% 32.5% 10.7%

Black 29.6% 7.4% 31.5% 9.2%

Unknown 25.5% 6.2% 29.5% 8.6%

All patients 34.2% 9.8% 36.6% 12.1%

39
Period Prevalence of any Concurrent Use of 

Polysedative Combinations in 2011

 Observed Prevalence (Expected Prevalence*)

 Hypnotics Atypical 

antipsychotics

Opioids

 

Skeletal muscle 

relaxants 

Benzodiazepines 5.2% (5.3%) 9.5% (8.1%) 15.9% (12.1%) 7.1% (6.8%)

Hypnotics 3.3% (3.6%) 6.1% (5.3%) 3.0% (3.0%)

Atypical 

antipsychotics

 8.9% (8.1%) 4.7% (4.6%)

Opioids 10.8% (6.9%)

40
The Impact of Musculoskeletal Pain

• Women are more likely to have musculoskeletal

disorders – 4.6% vs. 4.1%

• For women and men Veterans who use VA, the prevalence 

of painful musculoskeletal conditions including back, joint 

and musculoskeletal problems increases every year after 

deployment... 

• But, it increases more for women than men, so by 7 years 

post-deployment: 

– 20% of women and 17% of men have back problems

• 12% of women and 10% of men have musculoskeletal conditions

• 19% of women and 17% of men have joint problems

Previous talk by Sally Haskell and Laurie Zephyrin 41
Pain burden among Veterans 

entering PTSD treatment

N, severe pain %, severe pain N, non-severe 

pain

%, non-severe 

pain

Men 4642 39.15% 7215 60.85% 

Women 662 42.46% 897 57.54% 

42

Unpublished data, Hoff et al., 2014
Conclusions

• There is a significant pain burden associated with PTSD that 

may make treatment engagement more difficult

• We need to know more about concurrent pain management 

with PTSD treatment and guidance for PTSD and other mental 

health clinicians as to how best to address pain in treatment

• It is possible that an improvement in PTSD symptoms with 

treatment may increase perceptions and recognition of pain

• Area where there is a great need for more research – 

particularly in our women Veterans

43
What have we learned?

– Location of provider matters; Mental Health is 

doing the bulk of prescribing of benzodiazepines 

and atypical antipsychotics; Primary Care is 

bearing the burden of dealing with pain – 

Coordination of care is critically important

– Prescribing variability and patterns for women may 

reflect a difficult, complex patient mix or a failure to 

effectively disseminate the CPG recommendations

– Women and comorbidities present a dilemma

– Attempts to address PTSD-related sleep problems

– Opportunities for educational products and training 

44
Future Steps

• OMHO Psychopharmacology initiative and 

use of the academic detailing model are 

encouraging to improve practices

• Development of shared decision making 

tools that inform Veterans and their family 

members about the risks of some 

medications and safer options

• Determine if it is feasible to use a CBT 

protocol to taper Veterans from some of 

these medications, broader dissemination 

f CBT f i i CBT f i CBT f 

45
Encouraging New Research

• Recent research has suggested that interventions to taper patients 

from benzodiazepines can be effective 

– A Spanish group found two structured interventions in primary 

care led to significant reductions in long-term benzodiazepine use 

in patients without severe comorbidity (not PTSD patients) – 

written individualized stepped-dose reduction (Vicens, et al, 2014)

– In Canada direct patient education was used to discontinue 

benzodiazepines in community-dwelling older adults and was 

found to be effective. (Tannenbaum, et al., 2014)

– A Dutch group found letters sent to long-term benzodiazepine 

users effectively reduced use. (Gorgels, et al., 2005) 

– Patient materials were more effective at creating change than 

those that were aimed at physicians (Pimlott, et al., 2003)

46
47

49

 

Third Wednesday of the Month – 2-3PM (ET)

June 18

 PTSD and Sleep Problems: An Update on Medical Management

 Bruce Capehart, MD

July 16

 Pain and PTSD: Behavioral Mechanisms and Interventions

 Niloo Afari, PhD and Matthew Jakupcak, PhD

Upcoming Topics in Our Monthly 

Lecture Series

(866) 948-7880 or PTSDconsult@va.gov
Questions/Comments?

Use the Q&A box located on the right-hand side of your 

screen.

For more information

Visit the National Center for 

PTSD 

www.ptsd.va.gov

Contact: Nancy.Bernardy@va.gov
Gender Differences in Prescribing among Veterans Diagnosed with Posttraumatic Stress Disorder

Nancy C. Bernardy, PhD

VA National Center for PTSD

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Guidelines in Post Traumatic Stress Disorder: Prescribing Frequencies According to Provider Type. 

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patients with Acute Stress Disorder and Posttraumatic Stress Disorder. Retrieved last accessed 5/2011, 

from Guideline Watch

Bernardy, N., Lund, B., Alexander, B., & Friedman, M. (In press). Increased Polysedative Use in 

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2013, DOI: 10.1111/pme.12321

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differences in prescribing among veterans diagnosed with posttraumatic stress disorder. Journal of 

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dementia: prospective population based study. British Medical Journal 345:e6231 doi: 10.1136/bmj.e6231 

(Published 27 September 2012). 

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Practice Guideline Retrieved 4/17/2014, 2014, from 

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Hoogen, H. J., ... & Zitman, F. G. (2005). Discontinuation of long-term benzodiazepine use by sending a 

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prescription after sending a letter to long-term benzodiazepine users in family practice. Family practice, 

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Gender Differences in Prescribing among Veterans Diagnosed with Posttraumatic Stress Disorder

Nancy C. Bernardy, PhD

VA National Center for PTSD

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the diffusion of prazosin use for the treatment of posttraumatic stress disorder nationally in the 

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1

3

Journal of General Internal Medicine

ISSN 0884-8734

Volume 28

Supplement 2

J GEN INTERN MED (2013) 28:542-548

DOI 10.1007/s11606-012-2260-9

Gender Differences in Prescribing Among

Veterans Diagnosed with Posttraumatic

Stress Disorder

Nancy C. Bernardy, Brian C. Lund,

Bruce Alexander, Aaron B. Jenkyn, Paula

P. Schnurr & Matthew J. Friedman
1

3

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Gender Differences in Prescribing Among Veterans Diagnosed

with Posttraumatic Stress Disorder

Nancy C. Bernardy, PhD1,2, Brian C. Lund, PharmD, MS3, Bruce Alexander, PharmD4,

Aaron B. Jenkyn, BA1

, Paula P. Schnurr, PhD1,2, and Matthew J. Friedman, MD, PhD1,2

1 National Center for PTSD, White River Junction VA Medical Center, White River Junction, VT, USA; 2

The Geisel School of Medicine Dartmouth

College, Hanover, NH, USA; 3

Center for Comprehensive Access & Delivery Research and Evaluation Veterans Affairs Medical Center, Iowa

City, IA, USA; 4 Pharmacy Service, Iowa City VA Health Care System, Iowa City, IA, USA.

OBJECTIVE: The Department of Veterans Affairs

(VA) and Department of Defense (DoD) issued a

revised posttraumatic stress disorder (PTSD) Clinical Practice Guideline (CPG) in 2010 with specific

pharmacotherapy recommendations for evidencebased quality care. The authors examined prescribing frequencies over an 11-year period prior to the

release of the new guideline to determine gender

differences in pharmacotherapy treatment in veterans with PTSD.

METHOD: National administrative VA data from 1999 to

2009 were used to identify veterans with PTSD using

ICD-9 codes extracted from inpatient discharges and

outpatient clinic visits. Prescribing of antidepressants,

antipsychotics and hypnotics was determined for each

year using prescription drug files.

RESULTS: Women were more likely than men to

receive medication across all classes except prazosin

where men had higher prescribing frequency. The

proportion of women receiving either of the first-line

pharmacotherapy treatments for PTSD, selective serotonin reuptake inhibitors (SSRI) and serotoninnorepinephrine reuptake inhibitors (SNRI), increased

from 56.4 % in 1999 to 65.7 % in 2009, higher rates

than seen in men (49.2 % to 58.3 %). Atypical

antipsychotic prescriptions increased from 14.6 % to

26.3 % and nonbenzodiazepine hypnotics increased

from 3.8 % to 16.9 % for women, higher frequencies

than seen in men for both medications (OR = 1.31,

1.43 respectively). The most notable gender discrepancy was observed for benzodiazepines where prescriptions decreased for men (36.7 % in 1999 to

29.8 % in 2009) but steadily increased for women

from 33.4 % to 38.3 %.

CONCLUSION: A consistent pattern of increased

prescribing of psychotropic medications among women with PTSD was seen compared to men. Prescribing

frequency for benzodiazepines showed a marked

gender difference with a steady increase for women

despite guideline recommendations against use and a

decrease for men. Common co-occurring disorders

and sleep symptom management are important factors of PTSD pharmacotherapy and may contribute to

gender differences seen in prescribing benzodiazepines in women but do not fully explain the apparent

disparity.

KEY WORDS: gender; posttraumatic stress disorder; pharmacology.

J Gen Intern Med 28(Suppl 2):S542–8

DOI: 10.1007/s11606-012-2260-9

© Society of General Internal Medicine 2012

INTRODUCTION

American women represent a disproportionate number of

adults who receive prescriptions for psychotropic medications, with one in four women receiving such medications

compared to 15 % of men.1 This is particularly true of antianxiety drugs where approximately 11 % of middle-aged

American women (ages 45–64) were receiving benzodiazepines in 2010 compared to a rate that was half that seen in

comparable-aged men (5.7 %).1 One possible contributor to

the higher prescribing rates is the fact that over their

lifetimes women suffer more frequently from psychiatric

disorders than men.2 Another factor may be that women are

also more likely to seek and receive mental health treatment

compared to men.3 It is not clear if elevated psychiatric

medication prescribing among women is solely attributable

to greater diagnostic frequency or whether other reasons

such as gender differences in acceptance and receipt of

mental health treatment may contribute to a significant

degree.

VA is committed to identifying and focusing on women

veterans’ unique health care needs. Women are now the

fastest growing cohort within the veteran community and

represent approximately 16 % of military personnel who

have served in Afghanistan and Iraq.4 The rapid growth of

women veterans makes it particularly important to examine

gender differences in one of the most common diagnoses

among veterans seeking care, PTSD. Unfortunately, there

are virtually no data concerning prescribing differences

across genders in VA, despite the prominent role that

pharmacotherapy plays in the management of PTSD.

Approximately 60 % of privately insured patients with

PTSD receive pharmacotherapy for the disorder,5 while

close to 80 % of veterans receiving care for PTSD in VA are

treated with psychiatric medications.6 In the privately

insured patients, women were 11⁄2 times more likely to

S542

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receive psychotropic medications given a PTSD diagnosis

than men, but we do not know if this is the case for women

veterans treated in the VA.5

Given the prominent role that pharmacotherapy has in the

management of PTSD, we sought to characterize gender

differences in demographic characteristics and psychiatric

comorbidity among veterans with PTSD to examine differences in prescribing trends among men and women veterans

over an 11-year period (1999–2009) prior to the release of

the new VA guideline and to determine the extent to which

gender-based differences in prescribing frequencies were

explained by demographic and comorbidity variables.

METHODS

Data Source

National administrative VA data were obtained for fiscal

years 1999 through 2009, including outpatient visit data

and inpatient discharge data from the VA Austin Information Technology Center (Austin, TX) and pharmacy

data from the VA Pharmacy Benefits Management

Services (Hines, IL). Patient-level data were linked

between these sources using a scrambled patient identification number. This study was approved by the

University of Iowa Institutional Review Board and the

Iowa City Veterans Administration Research and Development Committee.

Patients

Veterans with PTSD were identified using diagnostic codes

extracted from inpatient and outpatient clinic visit data.

Patients were considered to have PTSD during a given year

if they had at least one visit coded for PTSD as either

primary or secondary diagnosis. PTSD was identified using

the International Classification of Diseases, Ninth Revision

(ICD-9) code of 309.81. This case definition has been used

in prior work examining medication use in veterans with

PTSD.6–9 The estimated rate of false-positive cases due to

administrative miscoding is infrequent (<4 %) using this

case definition.10,11

Medication Use

Medication use for each patient was based on having at

least one outpatient prescription fill of any quantity, days’

supply or dosage from within selected therapeutic classes.

Medications were selected based on their classification in

the VA/DOD CPG for PTSD and prior studies of

prescribing practices among veterans with PTSD.6,9,12

These classes included selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors

(SNRIs), atypical antipsychotics, benzodiazepines, nonbenzodiazepine hypnotics (included zolpidem, eszopiclone,

zaleplon and ramelteon) and prazosin. Prazosin was

included in the analysis based on its recommendation in

the CPG for targeting symptoms of sleep disturbances and

nightmares.

Demographic Characteristics and Psychiatric

Comorbidity

Demographic and psychiatric comorbidity variables were

determined during 2009. Demographic variables included

gender, age and urban residence. Urban residence was

determined according to Rural–urban Commuting Areas.13

Military service variables included level of VA serviceconnected disability rating (monetary benefit paid for injury

or illness incurred during active military service) and

service era, categorized as prior to, during, and post

Vietnam era. Time since first PTSD diagnosis was

categorized as new, 1–2 year history or ≥3 year history of

PTSD in VA. Psychiatric comorbidities were identified by

ICD-9 codes using the same case definition as for PTSD,

which required at least one clinic visit coded as either

primary or secondary diagnosis. The psychiatric comorbidities included in the analysis were depressive disorders,

substance use disorders, traumatic brain injury, panic

disorder, generalized anxiety disorder, obsessive-compulsive disorder and social phobia.

Statistical Analysis

Demographic characteristics and psychiatric comorbidity

frequencies were compared between men and women using

a t test for continuous variables and chi-squared test for

categorical variables. Medication prescribing frequencies

were reported separately for men and women spanning the

study time period of 1999–2009. Temporal changes in

gender-based differences in prescribing frequencies were

expressed using odds ratios, where values greater than one

indicated a higher prescribing frequency for women

compared to men.

The influence of demographic characteristics and

psychiatric comorbidity on the likelihood of prescribing

was examined using multiple logistic regression, with

separate analyses conducted for three medication classes

commonly prescribed to veterans with PTSD: SSRI/

SNRIs, atypical antipsychotics and benzodiazepines. The

first step was to report individual multivariable models for

men and women to examine the independent influence of

demographic and comorbidity variables on prescribing and

contrast effects across gender. Comorbidities were selected

for analysis from among DSM-IV Axis I disorders that are

JGIM Bernardy et al.: Gender Differences in Prescribing S543

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commonly co-occurring with PTSD or disorders that are

valid indications or relative contraindications to benzodiazepine use. The second step was to create four logistic

regression models predicting the likelihood of prescribing:

(1) gender effect only, (2) gender effect adjusted for

demographic variables, (3) gender effect adjusted for

comorbidity variables and (4) gender effect adjusted for

both demographic and comorbidity variables. Changes in

odds ratio for the gender effect across these four models

characterized the extent to which gender-based differences

in prescribing frequencies were explained by demographic

and comorbidity variables. All statistical analyses were

conducted using SAS version 9.3 (Cary, NC).

RESULTS

The number of female veterans being treated for PTSD in

the VA health care system tripled during our time frame,

from 10,484 in 1999 or 6.2 % of the population to 36,978 in

2009, which represents 7.5 % of the treated population.

Compared to men, women were younger, more likely to

have an urban residence, less likely to have a serviceconnected disability greater than 50 % and primarily from

the post-Vietnam era (Table 1). Women had higher rates of

all comorbidities examined except for substance use

disorder and traumatic brain injury.

Gender Differences in Prescribing

Women with PTSD were more likely to receive medication

across all classes except prazosin (Table 2). Prescribing

frequency of SSRIs and SNRIs increased for both men and

women. Among women, SSRI/SNRI use increased from

56.4 % in 1999 to 65.7 % in 2009. As prescribing also

increased in men, the gender ratio for SSRI/SNRIs

remained relatively consistent across the 11-year study

period, ranging from 1.34 to 1.57. Gender-based differences, however, were substantial for benzodiazepines.

Prescriptions for men decreased over time, consistent with

treatment guidelines, but conversely increased over time

among women, from 33.4 % in 1999 to 38.3 % in 2009.

Although benzodiazepine prescriptions were less common

initially among women than men (OR = 0.86), this pattern

reversed such that women were much more likely to receive

a benzodiazepine by 2009 (OR = 1.47). At the beginning of

the study period, atypical antipsychotic prescriptions were

similar between men and women (OR = 1.05). Rates

peaked for both genders in 2005 and decreased thereafter,

with higher use ultimately seen among women in 2009 (OR

= 1.31). Low-dose quetiapine was examined separately and

showed an initial tendency for higher use among women

(OR = 1.88), but by 2009 there was no longer any

meaningful gender gap in its prescribing (OR = 1.04).

Non-benzodiazepine hypnotic prescriptions remained stable

in both men and women until zolpidem was placed on the

national formulary in 2007, resulting in a tripling of its

Table 1. Gender Differences in Patient Characteristics, FY09

Characteristic All Women Men Statistics

N=495,309 N=36,978 N=458,331 χ2 or t; DF; p

Demographics

Age in years, mean (SD) 53.8 (14.6) 43.3 (11.9) 54.7 (14.5) 174; 46,321; <0.0001

Age group, years 29,233; 1; <0.0001

<30 54,343 (11.0 %) 6,535 (17.7 %) 47,808 (10.4 %)

30–39 41,453 (8.4 %) 7,221 (19.5 %) 34,232 (7.5 %)

40–49 52,472 (10.6 %) 10,896 (29.5 %) 41,576 (9.1 %)

50–64 282,451 (57.0 %) 11,409 (30.9 %) 271,042 (59.1 %)

≥65 64,590 (13.0 %) 917 (2.5 %) 63,673 (13.9 %)

Urban residence 359,120 (73.1 %) 29,191 (79.6 %) 329,929 (72.6 %) 862; 1; <0.0001

Service connection >50 % 272,189 (55.0 %) 17,798 (46.5 %) 254,991 (55.6 %) 1,151; 1; <0.0001

Service era 41,275; 1; <0.0001

Pre-Vietnam 32,477 (6.6 %) 408 (1.1 %) 32,069 (7.0 %)

Vietnam 278,299 (56.2 %) 4,625 (12.5 %) 273,674 (59.7 %)

Post-Vietnam 184,533 (37.3 %) 31,945 (86.4 %) 152,588 (33.3 %)

PTSD dx duration in VA 644; 1; <0.0001

New diagnosis 109,159 (22.0 %) 9,674 (26.2 %) 99,485 (21.7 %)

1–2 years 115,282 (23.3 %) 9,331 (25.2 %) 105,951 (23.1 %)

3+ years 270,868 (54.7 %) 17,973 (48.6 %) 252,895 (55.2 %)

Comorbidity

Depressive disorder 240,920 (48.6 %) 24,257 (65.6 %) 216,663 (47.3 %) 4 600; 1; <0.0001

Anxiety disorder, any 39,710 (8.0 %) 5,458 (14.8 %) 34,252 (7.5 %) 2,464; 1; <0.0001

Panic disorder 19,084 (3.9 %) 3,027 (8.2 %) 16,057 (3.5 %) 2025; 1; <0.0001

GAD 19,719 (4.0 %) 2,303 (6.2 %) 17,416 (3.8 %) 528; 1; <0.0001

OCD 3,809 (0.8 %) 676 (1.8 %) 3,133 (0.7 %) 587; 1; <0.0001

Social phobia 1,388 (0.3 %) 161 (0.4 %) 1,227 (0.3 %) 34; 1; <0.0001

Substance use disorder 111,010 (22.4 %) 6,594 (17.8 %) 104,416 (22.8 %) 482; 1; <0.0001

Traumatic brain injury 21,652 (4.4 %) 1,249 (3.4 %) 20,403 (4.5 %) 94; 11; <0.0001

S544 Bernardy et al.: Gender Differences in Prescribing JGIM

Author's personal copy
prescribing rate within 2 years. Again, women were

consistently receiving significantly more of these prescriptions than men in 2009 (OR = 1.43). Prazosin prescribing

was distinct in that prescriptions were consistently lower for

women than men, though prazosin use increased in both

genders. Notably, the gender gap in prazosin use decreased

markedly from an odds ratio of 0.14 in 1999 to 0.75 in

2009.

Independent Predictors of Prescribing

Demographic characteristics and psychiatric comorbidities

were then examined as independent predictors of prescribing for SSRI/SNRIs, benzodiazepines and atypical antipsychotics (Table 3). Age had minimal impact on

prescribing for SSRI/SNRIs in either gender but had

substantial effect on prescribing of benzodiazepines and

atypical antipsychotics. Younger reproductive-age women

had lower rates of receipt of both medications. The atypical

antipsychotics showed an inverted U-shaped pattern of

prescribing where lower rates were seen in younger

veterans, increased in middle age and then showed large

decreases in the oldest age group in both men and women.

An increased percentage of VA service-connected disability

(>50 %) contributed to an increase in prescribing of all

medications for both men and women.

Psychiatric comorbidity had significant impact on prescribing. The likelihood of SSRI/SNRI use was nearly

three-fold higher among patients with co-occurring depressive disorder. Benzodiazepine use was more common for all

anxiety disorder comorbidities, though most dramatically

with panic disorder. Elevated prescribing of atypical

antipsychotics was observed in both men and women with

co-occurring substance use disorder. Traumatic brain injury

was associated with increased prescribing across all

medication classes, except for SSRI/SNRI use in women.

The impact of comorbidity on prescribing was generally

consistent across genders. However, a notable exception

was benzodiazepine use among veterans with comorbid

substance use, which is considered a contraindication

according to guideline recommendations. Among women

veterans, benzodiazepine use was actually higher for

women with co-occurring substance use disorder, whereas

the opposite was true for men.

Gender Effects of Demographic

Characteristics and Comorbidities

The impact of demographic characteristics and psychiatric

comorbidities on gender-based differences in prescribing is

examined in Table 4. Differences in SSRI/SNRI prescribing

were largely attributable to differences in comorbidity

frequency between genders, as shown by the shift in the

gender effect toward a value of one, from an unadjusted

odds ratio of 1.37 to 1.13 after adjustment for psychiatric

comorbidity. In contrast, adjustment for demographic

variables had no effect on the ratio of SSRI/SNRI

prescribing across genders. Competing effects were seen

for benzodiazepine use, where adjustment for demographic

characteristics increased impact of gender, whereas adjustment for comorbidity decreased impact. The net result of

simultaneous adjustment for these effects was a persistence

in gender-based discrepancy in benzodiazepine prescribing

(OR = 1.47) that could not be explained by underlying

difference between genders in demographics or psychiatric

comorbidities. Finally, gender-based differences in atypical

antipsychotic prescribing were primarily attributable to

differences in demographic characteristics, reflected by an

unadjusted odds ratio of 1.31 to 1.08 after the adjustment

for demographics.

DISCUSSION

The primary objective of this work was to examine gender

differences in psychopharmacological prescribing among

veterans with PTSD and determine the extent to which

these differences may be explained by underlying variation

in the frequency of demographic characteristics and

comorbid diagnoses. Women veterans with PTSD are more

likely to have been recently diagnosed, are younger than

men by a decade, have less VA service-connected disability

and are primarily post-Vietnam era. Women were more

likely to have co-occurring depressive and anxiety disorders, whereas men experienced elevated rates of substance

use disorder and traumatic brain injury.

Women veterans were more likely to receive psychotropic medications across all classes except prazosin, which

was more likely in men. The substantial increases in

prescribing of SSRI/SNRIs in women reflect a positive

shift toward evidence-based pharmacological care. This

translates to an additional 18,388 women receiving first-line

recommended medications for the management of PTSD.

When adjusted for psychiatric comorbidities, there are still

higher frequencies of SSRI/SNRIs in women. It is possible

that there are comorbid disorders not accounted for in our

analyses unique to women that contribute to this gender

difference such as premenstrual dysphoric disorder. It is

also possible known sexual side effects cause men to

decline SSRI/SNRIs, and they may represent an undertreated group. In any case, the increased frequency of SSRI/

SNRIs for women with PTSD should be viewed as a

positive outcome.

We observed comparable guideline-concordant prescription patterns with atypical antipsychotics with similar

gender frequencies until a shift occurred in 2003 that saw

an increase for women that stayed elevated compared to

JGIM Bernardy et al.: Gender Differences in Prescribing S545

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those for men. When adjusted for demographic characteristics, there were still elevations in frequency in women that

were not accounted for by different prescribing patterns in

different age groups and for more severe service-connected

disability. It is possible that atypical antipsychotics may be

targeted at insomnia symptoms in women as there is

evidence of gender differences in arousal symptoms.14

However, when we examined low-dose quetiapine separately, no gender differences in prescribing were seen. It is

important to note that during this time there were a number

of studies suggesting that atypical antipsychotics were

effective adjunctive treatments for PTSD, and it is possible

again that men were actually undertreated rather than

overuse seen in women.

Prescribing frequencies for benzodiazepines were the

significant exception. As opposed to decreased prescribing

for men, which is guideline-concordance practice, prescriptions steadily increased for women despite recommendations in the CPG against their use in PTSD because of

safety and efficacy concerns. Chronic use of benzodiazepines can cause cognitive problems, increase the risk of

falls and accidents and have possible detrimental effects on

the recommended psychotherapies for PTSD. With their

abuse and dependence properties, benzodiazepines are

contraindicated in those with comorbid substance use disorder

in patients with PTSD15 as well as contraindicated in those

with TBI.12 Not only did we find increased rates of

prescribing in women, but in women with co-occurring

substance use disorder, rates of benzodiazepine prescriptions

were elevated compared to men, a practice discouraged in the

CPG and one previously noted in a smaller sample.17

Similarly, elevated benzodiazepine prescriptions were seen

in both men and women with TBI, again a contraindicated

practice. The impact of adjustment for demographic characteristics and psychiatric comorbidities on benzodiazepines was

not straightforward. Some increased frequency of prescriptions for benzodiazepines in women is clearly accounted for

by comorbidities and again may be related to co-occurring

disorders that were not controlled for in our analyses.

However, demographic differences also are influential, and

age is one such factor. Reduced prescribing of benzodiazepines in the youngest reproductive-age group of women when

contrasted to their male counterparts is encouraging. Being

older and having a greater service-connected disability

contributed to elevated benzodiazepine prescribing. It is

possible high rates of distress seen in newly returning

veterans from the wars in Iraq and Afghanistan may be a

reason for an increase in benzodiazepine prescribing.16,17 It is

also possible that clinicians prescribe benzodiazepines to

women for symptoms that are not an indication for their use,

including headache, fatigue, chest pain and vertigo.18

Sleep symptom management clearly plays a prominent

role in PTSD pharmacotherapy. It is possible that increased

prescribing of atypical antipsychotics and benzodiazepines

in women is an attempt to address insomnia symptoms. We

are unable to capture insomnia symptoms associated with

PTSD using administrative data but think that it is

important that this be examined in future work. The

extraordinary 10 % increase in zolpidem use in women

from 2007 to 2009 after the drug became available on

formulary confirms how much sleep difficulties are part of

the clinical presentation of PTSD. It is not clear why this

medication increased so much in women compared to men

nor why prazosin would be the exception and more widely

used in men. The increased use of nonbenzodiazepine

hypnotics does not necessarily reflect a considerably safer

Table 2. Gender Differences in Temporal Prescribing Trends

FY99 FY01 FY03 FY05 FY07 FY09

SSRI/SNRI

Women 56.4 % 62.3 % 68.4 % 67.5 % 66.1 % 65.7 %

Men 49.2 % 53.3 % 58.0 % 58.9 % 58.2 % 58.3 %

OR (95 % CI) 1.34 1.45 1.57 1.45 1.40 1.37

(1.28, 1.39) (1.40, 1.51) (1.51, 1.62) (1.41, 1.49) (1.36, 1.44) (1.34, 1.40)

Benzodiazepines

Women 33.4 % 36.3 % 37.3 % 37.5 % 39.1 % 38.3 %

Men 36.7 % 35.2 % 33.4 % 31.7 % 31.3 % 29.8 %

OR (95 % CI) 0.86 1.05 1.18 1.30 1.41 1.47

(0.83, 0.90) (1.01, 1.09) (1.14, 1.23) (1.26, 1.33) (1.38, 1.45) (1.43, 1.50)

Atypical antipsychotics

Women 14.6 % 21.6 % 27.6 % 29.0 % 26.6 % 26.3 %

Men 14.1 % 20.1 % 25.1 % 25.6 % 22.5 % 21.3 %

OR (95 % CI) 1.05 1.09 1.14 1.19 1.25 1.31

(0.99, 1.11) (1.05, 1.15) (1.10, 1.18) (1.15, 1.22) (1.22, 1.29) (1.28, 1.35)

Zolpidem

Women 3.8 % 5.7 % 5.6 % 5.5 % 6.1 % 16.9 %

Men 3.8 % 4.9 % 4.3 % 3.9 % 4.2 % 12.4 %

OR (95 % CI) 1.02 1.18 1.33 1.44 1.48 1.43

(0.92, 1.13) (1.09, 1.28) (1.24, 1.43) (1.35, 1.53) (1.40, 1.56) (1.39,1.48)

Prazosin

Women 0.2 % 0.7 % 1.9 % 3.5 % 5.0 % 7.1 %

Men 1.5 % 1.6 % 2.6 % 4.8 % 6.4 % 9.3 %

OR (95 % CI) 0.14 0.41 0.73 0.73 0.76 0.75

(0.09, 0.21) (0.32, 0.51) (0.64, 0.82) (0.67, 0.79) (0.72, 0.80) (0.72, 0.78)

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alternative to benzodiazepines. Safety concerns in nonbenzodiazepine hypnotics have been noted with elevated

hazards of dying compared to those prescribed no hypnotics.19 It is imperative that if these patterns reflect an

attempt to assist with sleep symptom management that

different treatment approaches be considered that include

cognitive behavioral therapy for insomnia (CBT-I) and safer

medication options.

Table 4. Impact of Adjustment for Demographic Characteristics and Psychiatric Comorbidity on Gender-Based Differences in Prescribing,

Multivariable Logistic Regression, FY09

Model SSRI/SNRI Benzodiazepine Atypical antipsychotics

OR (95 % CI)* c statistic OR (95 % CI) c statistic OR (95 % CI) c statistic

Unadjusted 1.37 0.511 1.47 0.514 1.31 0.510

(1.34, 1.40) (1.43, 1.50) (1.28, 1.35)

Demographics only 1.34 0.567 1.63 0.608 1.08 0.605

(1.31, 1.37) (1.60, 1.67) (1.05, 1.10)

Comorbidity only 1.13 0.630 1.27 0.590 1.25 0.607

(1.10, 1.15) (1.24, 1.30) (1.22, 1.28)

Demographics and comorbidity 1.15 0.658 1.47 0.653 1.08 0.652

(1.12, 1.18) (1.44, 1.51) (1.05, 1.11)

*Odds ratio and 95 % confidence interval for the likelihood of receiving medication in women compared to men

Table 3. Demographic Characteristics and Psychiatric Comorbidity as Independent Predictors of Prescribing, Multivariable Logistic

Regression, FY09

Diagnosis SSRI/SNRI Benzodiazepine Atypical antipsychotics

Women Men Women Men Women Men

OR (95 % CI) OR (95 % CI) OR (95 % CI) OR (95 % CI) OR (95 % CI) OR (95 % CI)

Demographics

Age group, years

<30 0.80 0.85 0.59 0.78 0.58 0.66

(0.75, 0.86) (0.82, 0.87) (0.55, 0.64) (0.75, 0.80) (0.54, 0.63) (0.64, 0.69)

30–39 0.96 1.01 0.78 0.93 0.81 0.89

(0.89, 1.02) (0.98, 1.04) (0.73, 0.83) (0.90, 0.96) (0.75, 0.87) (0.86, 0.92)

40–49 Reference Reference Reference Reference Reference Reference

50–64 1.02 0.96 1.01 1.00 0.85 0.87

(0.96, 1.09) (0.93, 0.99) (0.95, 1.07) (0.96, 1.03) (0.79, 0.90) (0.84, 0.90)

≥65 0.88 0.85 0.84 0.86 0.36 0.59

(0.72, 1.06) (0.81, 0.88) (0.70, 1.01) (0.83, 0.90) (0.28, 0.47) (0.57, 0.62)

Urban residence 0.90 0.88 0.90 0.86 0.94 0.95

(0.85, 0.95) (0.86, 0.89) (0.85, 0.95) (0.84, 0.87) (0.88, 0.99) (0.94, 0.97)

Service connection >50 % 1.26 1.29 1.47 1.46 1.28 1.19

(1.20, 1.32) (1.27, 1.31) (1.40, 1.54) (1.43, 1.48) (1.22, 1.35) (1.17, 1.21)

Service era

Pre-Vietnam 0.70 0.80 0.92 1.07 0.98 0.80

(0.54, 0.92) (0.77, 0.82) (0.71, 1.20) (1.03, 1.11) (0.68, 1.42) (0.77, 0.84)

Vietnam Reference Reference Reference Reference Reference Reference

Post-Vietnam 0.89 1.00 0.82 0.92 0.96 1.32

(0.82, 0.97) (0.98, 1.03) (0.76, 0.89) (0.90, 0.95) (0.88, 1.04) (1.28, 1.36)

PTSD dx duration in VA

New diagnosis 0.76 0.69 0.63 0.53 0.58 0.47

(0.71, 0.80) (0.68, 0.70) (0.59, 0.67) (0.52, 0.54) (0.54, 0.62) (0.46, 0.48)

1–2 years 1.06 0.98 0.80 0.73 0.84 0.70

(1.00, 1.13) (0.96, 0.99) (0.76, 0.85) (0.72, 0.74) (0.79, 0.89) (0.69, 0.72)

3+ years Reference Reference Reference Reference Reference Reference

Comorbidity

Depressive disorder 2.88 2.61 1.36 1.41 1.04 1.43

(2.75, 3.01) (2.58, 2.64) (1.30, 1.42) (1.39, 1.43) (0.99, 1.10) (1.41, 1.45)

Panic disorder 1.72 1.71 3.48 4.51 1.31 1.55

(1.57, 1.89) (1.65, 1.77) (3.21, 3.78) (4.36, 4.67) (1.21, 1.42) (1.50, 1.61)

GAD 1.31 1.41 1.92 2.46 1.12 1.30

(1.19, 1.45) (1.36, 1.46) (1.75, 2.10) (2.38, 2.54) (1.02, 1.24) (1.26, 1.35)

OCD 1.65 1.88 1.53 1.62 2.14 2.29

(1.37, 1.99) (1.72, 2.05) (1.30, 1.80) (1.50, 1.74) (1.82, 2.51) (2.12, 2.46)

Social phobia 1.44 1.61 1.30 1.58 1.20 1.34

(0.97, 2.13) (1.40, 1.84) (0.93, 1.81) (1.40, 1.78) (0.85, 1.70) (1.19, 1.52)

Substance use disorder 1.29 1.10 1.11 0.92 2.71 1.92

(1.22, 1.37) (1.08, 1.11) (1.05, 1.18) (0.90, 0.93) (2.56, 2.87) (1.89, 1.95)

Traumatic brain injury 1.00 1.16 1.23 1.32 1.14 1.21

(0.88, 1.13) (1.12, 1.20) (1.09, 1.39) (1.27, 1.36) (1.00, 1.30) (1.17, 1.25)

Each column is a separate multiple logistic regression model

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This study has several limitations. The use of administrative data allows us to describe prescribing trends among

veterans with PTSD and to determine predictors of

prescribing but does not allow us to fully determine the

justifications for the prescribed medications. While we were

able to determine rates of comorbid disorders using

administrative data, it is difficult to confirm their accuracy,

and there are other co-occurring disorders that may be

relevant that were not captured. Nor can we confirm the

timing (e.g., current active problem as in the case of a cooccurring SUD or distant history) or severity of the cooccurring disorders examined. It is also possible that there

may be gender-specific coding biases.

This work highlights important findings regarding gender

and PTSD that speak to the need for additional work in

several areas. We found differences between men and women

that are not explained by comorbidities, especially in the area

of prescribing of benzodiazepines. It is encouraging to see

prescriptions written for first-line pharmacotherapy treatments for women with PTSD. Reduced benzodiazepine

findings in men are also encouraging, but we are left with

more questions than we have answers regarding the increased

prescribing frequency of benzodiazepines in women. It is still

possible that the observed gender differences in prescribing

are for what might be considered “appropriate reasons” that

take into account other co-occurring disorders or that they

reflect a greater willingness among women toward taking

medications for mental health problems rather than decision

making among prescribers. It is also possible the complexity

of these patients may cause clinicians to respond to treatment

failures by indiscriminately trying different medications. VA

has an opportunity to develop policies and interventions that

will improve the care that women veterans returning from

war receive for PTSD and decrease the heavy burden of

greater comorbid mental health disorders, particularly in the

treatment of SUD and TBI. Provider education is sorely

needed for this primarily reproductive-aged cohort to inform

clinicians about gender differences in side effects, medication

dosing and particularly about sex differences in pharmacokinetics of psychotropic medications in order to provide

access to quality PTSD care for our veteran women.

Acknowledgments: This project was supported by the Mental

Health QUERI, Department of Veterans Affairs (MH-QUERI) (RRP

11-001). Dr. Lund received additional support from the VA Health

Services Research and Development Service (CDA 10-017; REA 09-

220). None of these sponsors had any role in the study design,

methods, analyses and interpretation, or in preparation of the

manuscript and the decision to submit it for publication. The views

expressed in this article are those of the authors and do not

necessarily reflect the position or policy of the Department of

Veterans Affairs.

Conflict of Interest: The authors declare that they do not have a

conflict of interest.

Corresponding Author: Nancy C. Bernardy, PhD; National

Center for PTSD, White River Junction VA Medical Center, 215

North Main, White River Junction, VT 05001, USA

(e-mail: Nancy.Bernardy@va.gov).

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