Differences in Depression Care for Men and Women among Veterans with and without Psychiatric Comorbidities

Women's Health Issues xxx-xx (2016) 1–8

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Original article

Differences in Depression Care for Men and Women among Veterans with and without Psychiatric Comorbidities Christine A. Lam, MD, MBA, MSHS a,b,*, Cathy Sherbourne, PhD c, Lillian Gelberg, MD, MSPH d,e,f, Martin L. Lee, PhD a,g, Alexis K. Huynh, PhD, MPH a, Karen Chu, MS a, Jennifer L. Strauss, PhD h,i, Maureen E. Metzger, PhD, MPH j, Edward P. Post, MD, PhD j,k, Lisa V. Rubenstein, MD, MSPH a,b,c,e, Melissa M. Farmer, PhD a a VA HSR&D Center for the Study of Healthcare Innovation, Implementation & Policy, VA Greater Los Angeles Healthcare System, Sepulveda, California b Department of Medicine, UCLA David Geffen School of Medicine, Los Angeles, California c RAND Corporation, Santa Monica, California d Department of Family Medicine, UCLA David Geffen School of Medicine, Los Angeles, California e Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, California f Office of Healthcare Transformation and Innovation, VA Greater Los Angeles Healthcare System, Los Angeles, California g Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, California h Mental Health Services, Department of Veterans Affairs, Washington, DC i Department of Psychiatry, Duke University Medical Center, Durham, North Carolina j VA HSR&D Center for Clinical Management Research, VA Ann Arbor, Ann Arbor, Michigan k University of Michigan Medical School, Ann Arbor, Michigan

Article history: Received 29 February 2016; Received in revised form 31 October 2016; Accepted 7 November 2016

a b s t r a c t Background: Depression is common among primary care patients, affecting more women than men. Women veterans are an extreme but growing minority among patients seeking care from the Department of Veterans Affairs (VA), an organization historically designed to serve men. Little is known about gender differences in depression care quality within VA primary care population. Purpose: This works assesses the gender differences in depression care among veterans using longitudinal electronic measures. Methods: We undertook a cross-sectional study of all veteran VA primary care users with a new episode of depression from federal fiscal year 2010, covering nine geographically diverse regions. We assessed the quality of depression care based on receipt of minimally appropriate depression treatment within 1 year of a new episode of depression and on receipt of depression-related follow-up visits within 180 days. Minimally appropriate treatment and follow-up were operationalized as meeting or exceeding a minimally appropriate threshold for care, based on national quality measures and expert panel consensus. Regression models were used to produce predicted probabilities for each process outcome accounting for the presence or absence of other psychiatric comorbidities. All models were adjusted for model covariates and clinic clusters (404 sites). Main Findings: In 2010, 110,603 veterans with a primary care visit had a new episode of depression; 10,094 (9%) were women. In multivariate analyses, women had modest yet significantly higher rates of minimally appropriate depression treatment than men, whether patients had depression only (79% of women vs. 76% of men; p < .001) or depression along with other psychiatric comorbidities (92% of women vs. 91% or men; p < .001). There were no significant gender

Funding Statement: Funding for this research was supported by a grant from VA Health Services Research & Development (Project #IIR 11–326; PI: Farmer). Dr. Lam is supported by the VA Quality Scholars advanced fellowship program. The views expressed in the manuscript are solely those of the authors, and do not necessarily represent the views of the U.S. Department of Veterans Affairs or the United States government. The authors declare that they do not have conflicts of interest.

Disclosure: 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 or the United States government. * Correspondence to: Christine A. Lam, MD, MBA, MSHS, VA Greater Los Angeles Healthcare System (GLA), 11301 Wilshire Boulevard (111G), Los Angeles, CA 90073. Phone: (310) 478-3711. E-mail address: [email protected] (C.A. Lam).

1049-3867/$ - see front matter Published by Elsevier Inc. on behalf of Jacobs Institute of Women's Health. http://dx.doi.org/10.1016/j.whi.2016.11.001

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differences for rate of receipt of follow-up for depression at 180 days. Interactions between gender and other psychiatric comorbidities were not significant. Conclusions: Our findings suggest that the VA is achieving comparable depression care between genders at minimally appropriate thresholds. Published by Elsevier Inc. on behalf of Jacobs Institute of Women's Health.

Women are serving in the U.S. military at unprecedented rates. They comprise approximately 15.1% of the Department of Defense’s active duty force (Active Duty Master Personnel File, 2014). In 2012, women comprised 6.5% of the veteran population and are projected to comprise 15% of the veteran population by 2035 (Frayne et al., 2014; Office of the Actuary Department of Veterans Affairs, 2011; Yano et al., 2011). Given the rapidly expanding women veteran population, the Department of Veterans Affairs (VA) has made women’s health a priority, including the development of primary care clinics tailored specifically for women, often with access to mental health services, as well as a variety of programs to promote capabilities in women’s health across all VA services (Yano et al., 2011). Depression, one of the most common mental health illnesses, is projected to be the second leading burden of disease by 2030 (Mathers & Loncar, 2006). Among veterans, the diagnostic rate exceeds that of the general primary care population at approximately 14%, compared with 5% to 12% (Goldman, Nielson, & Champion, 1999; National Alliance on Mental Illness, 2009; Simon et al., 2007). Furthermore, women veterans, like women in the general population (Kessler, 2003) have higher odds of depression than male veterans across all age groups (Frayne et al., 2010). Women veterans also have higher rates of depression risk factors, including sexual trauma during military service, homelessness, and poverty (Runnals et al., 2014; Pavao et al., 2013). The multidirectional relationships between depression and other psychiatric disorders, anxiety, traumadsexual and otherwisedand substance abuse increase care complexity for women veterans (Chander & McCaul, 2003; Frayne et al., 2014; Kaufman & Charney, 2000; Office of the Actuary Department of Veterans Affairs (2011); Yano et al., 2011). Care for depression is imperative, not only to decrease mortality risk from suicide, but also to attenuate negative outcomes from chronic diseases such as diabetes and heart disease (Katon, 2003). The VA overwhelmingly is the main source of mental health care for veterans, even for veterans who receive other health care services outside of VA (Liu et al., 2009). Depression, as well as many chronic diseases, is usually first addressed in the primary care setting. Given the importance of primary care as the gatekeeper to more intensive mental health care, VA the has made substantial efforts to improve mental health care as a whole by integrating it within primary care since the mid 2000s (Post, Metzger, Dumas, & Lehmann, 2010). However, little is currently known about whether depression care is comparable for male and female veterans (Runnals et al., 2014). The goal of this study was to examine whether gender differences exist in minimally appropriate depression treatment and follow-up in the VA primary care population, using process measures to identify needs and guide targeted improvement efforts (Farmer et al., 2016). Historically, women have been a minority within VA, with prior studies demonstrating barriers to obtaining care that include inconvenience, lack of knowledge, and negative perceptions of quality of care (Washington, Yano, Simon, & Sun, 2006). We hypothesized that providers may be less attuned to their health issues, particularly depression, and

therefore that women veterans would have lower rates of depression treatment and follow-up than men (Washington, Yano, & Horner, 2006). Nevertheless, veterans with other psychiatric illnesses, such as posttraumatic stress disorder, have been found to be associated with increased health care use (Dobie et al., 2006; Schnurr, Friedman, Senguta, Jankowski, & Holmes, 2000). As such, we secondarily hypothesized that patients with more complex presentations, specifically additional psychiatric comorbidities, may have relatively increased depression care compared with those with less complex presentations. Materials and Methods Conceptual Framework We used the behavioral model for vulnerable populations (Gelberg, Andersen & Leake, 2003), an adaptation of the Andersen model of health services use (Andersen, 1968, 1995; Andersen & Davidson, 2007), as our framework for understanding the effects of gender on depression care (Figure 1). The adapted model includes domains associated with health and psychosocial conditions that may influence health service use and outcomes, including predisposing characteristics (gender, age, additional psychiatric illnesses including posttraumatic stress disorder, anxiety, and alcohol/drug use, cultural factors, social support), enabling personal and organizational characteristics (personal resources and VA service connection/eligibility, clinic characteristics), and health need (depression), that influence individual health behaviors (receipt of depression minimally appropriate treatment and follow-up) associated with a new episode of depression. This study was part of a larger umbrella study (Farmer et al., 2016) that developed, verified, and validated prototype longitudinal electronic process measures for depression care in VA within an evidence-based quality improvement framework, in which examining the minimum appropriate care is the first step to identifying improvement needs. Thus, by nature, the first step is to assess the floor of care rather than the ceiling, given high variation in what may be considered optimal. Because systematic symptom outcomes are not available uniformly in VA administrative data, the measures focus on processes of care that are guideline based, rooted in literature showing process and outcome links, and reviewed and endorsed by a national expert panel (Farmer et al., 2016; Kahn et al., 2007). Data Sources Data came from VA administrative data spanning nine geographically diverse regions in the United States from federal fiscal year 2010 (FY10) and capture the entire primary care population in these nine regions. Health care demographic, diagnostic, and minimally appropriate treatment data came from the VA National Patient Care Database (Hynes, Perrin, Rappaport, Stevens, & Demakis, 2004), a large consolidated database that

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Population Characteristics Predisposing disposi

Demographics • Gender • Age • Race/Ethnicity • Additional psychiatric comorbidities (PTSD, anxiety, alcohol and/or drug use disorders)

E Enabling nablin

Individual • Personal resources Contextual • VA Service Connection • Clinic location

N Need

Health h Beha Behaviors

Evaluated • Detection of new episode of depression

Utilization of Mental Health Services (quality of care) • Minimum appropriate depression treatment* • In-person depression care followup by 180 days†

Outcomes

H lth t Perceived Health Evaluated Health Consumer Satisfaction Quality of Life

Social • Cultural factors (Race/Ethnicity) • Social support (Marital status) Figure 1. Conceptual framework adapted from the behavioral model for vulnerable populations. The dashed box represents the adapted portion of the behavioral model for vulnerable populations used in this paper. *Minimum appropriate depression treatment is defined as minimally appropriate threshold of depression treatment of having received either 60 or more days of depression prescriptions, or 4 or more administratively identified mental health visits, or 3 or more psychotherapy visits (1 ¼ yes) within 1 year of the new episode of depression. yIn-person depression care follow-up at 180 days is a measure of timeliness of in-person visits, defined as having received either three or more mental health specialty, psychotherapy, or primary care visits with International Classification of Diseases, Ninth Edition diagnoses for depression within 180 days of the new episode of depression. Abbreviation: PTSD, posttraumatic stress disorder.

includes all patient-level encounters within the VA Healthcare System organized by fiscal year and region. VA Pharmacy Benefits Management data in the same year and regions were used and included dispensed prescriptions at the VA for 12 months before and after the first day of FY10 for study analysis. All datasets were the most comprehensive data available within the VA for FY10, but did not capture non-VA health care use. Study Cohort We created our patient cohort, by identifying the index visit as the patient’s first primary care visit after the start of FY10 based on administrative encounter identifiers for primary care visits (referred to as “clinic stop codes” at the VA). From this sample, we included patients who were continuously seen in primary care, defined as at least two visits in one’s home clinic site over a 2-year period, aiming to capture longitudinal patients and exclude one-time visits. To define a new episode of depression (in the need domain of our model), we excluded patients with a history of depression who were diagnosed or fully treated in the 6 months before the index visit. Of the remaining patients, an analytic dataset of patients who had a new episode of depression in FY10 was identified based on International Classification of Diseases, Ninth Edition (ICD-9) codes (293.83, 296.2x, 296.3x, 296.5x, 296.90, 296.99, 298.0x, 300.4x, 309.0x, 309.1x, 311x) and prescriptions for select antidepressants (Farmer et al., 2016). All non-veteran individuals were excluded (e.g., family members of veterans seen at VA in a limited fashion). Measures Our primary process measures (in the health behavior domain of our model) capture receipt of minimally appropriate depression treatment in the succeeding year after detection of a

new episode of depression and in-person timely depression follow-up care at 180 days. Minimally appropriate treatment and follow-up outcomes were operationalized as binary indicators. The latter was defined as having received
60 days of appropriate antidepressant prescriptions not indicated as prescribed for another condition such as pain or sleep and administered at an appropriate dose; or four or more administratively identified mental health specialty visits (not primary care visits); or three or more psychotherapy visits within 1 year of the new episode of depression. Follow-up, a measure of timeliness of in-person visits for depression, was defined as three or more primary care visits with ICD-9 diagnoses for depression, or three or more mental health specialty visits, or three or more psychotherapy visits within 180 days of the new episode of depression. Further details on the measures including codes and lists of antidepressants are described elsewhere (Farmer et al., 2016). Diagnostic, service location, and demographic data, including gender and the predisposing factors age, marital status, and race/ ethnicity, were obtained from the National Patient Care Database. We created a dichotomous indicator of depression only versus depression along with other psychiatric comorbidities, which included patients who had any of the three most common psychiatric diagnoses among veterans that have significant overlap with depression (posttraumatic stress disorder, anxiety, and alcohol/drug use; Seal, Bertenthal, Miner, Sen, & Marmar, 2007). The enabling factor copayment was defined as those required to pay a copayment for health care services or medications, those who are copayment exempt, and not applicable/ unknown. The VA largely determines copayments by percent of disability from service-connected condition, which is an injury or illness incurred or aggravated during active military service (U.S. Department of Veterans Affairs, 2015a, 2015b), and financial status based on income adjusted for household size, geography, and calendar year (U.S. Department of Veterans Affairs, 2013; VA

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Table 1 Patient Characteristics of Veterans with New Episodes of Depression, by Gender

Depression treatment* (overall) Depression only Other psychiatric comorbidities Depression follow-up at 180 daysy (overall) Depression-only Other psychiatric comorbidities Age, yrs (mean) Race/ethnicity White Black Other Unknown/declined/missing Marital status Married Divorced/separated Never married/single Widowed Unknown Co-payment statusz Required Exempt Not applicable/unknown Other psychiatric comorbiditiesx Location of care at VA community-based clinics

c2 (df), Except Where Noted

Men (n ¼ 100,509), n (%) or Mean (SD)

Women (n ¼ 10,094), n (%) or Mean (SD)

Overall (n ¼ 110,603), n (%) or Mean (SD)

82,797 41,645 41,152 63,050 27,327 35,723 57

(82.4) (75.5) (90.8) (62.7) (49.5) (78.8) (16.1)

8,609 4,618 3,991 6,797 3,290 3,507 44

(85.3) (79.7) (92.8) (67.3) (56.8) (81.6) (14.3)

91,406 46,263 45,143 69,847 30,617 39,230 56

(82.6) (75.9) (91.0) (63.2) (50.2) (79.1) (16.3)

54.17 51.22 19.80 83.64 110.47 18.00 78.01

63,764 15,744 5,714 15,287

(63.4) (15.7) (5.7) (15.2)

5,293 2,613 751 1,437

(52.4) (25.9) (7.4) (14.2)

69,057 18,357 6,465 16,724

(62.4) (16.6) (5.8) (15.1)

809.50 (3)***

52,062 24,755 17,181 5,099 1,412

(51.8) (24.6) (17.1) (5.1) (1.4)

3,127 3,397 2,887 472 211

(31.0) (33.7) (28.6) (4.7) (2.1)

55,189 28,152 20,068 5,571 1,623

(49.9) (25.5) (18.1) (5.0) (1.5)

1800.00 (4)***

21,379 74,494 4,636 45,321 23,566

(21.3) (74.1) (4.6) (45.2) (23.5)

1,500 8,100 494 4,299 2,103

(14.9) (80.2) (4.9) (42.6) (20.8)

22,879 82,594 5,130 49,620 25,669

(20.7) (74.7) (4.6) (44.9) (23.2)

229.93 (2)***

(1)*** (1)*** (1)*** (1)*** (1)*** (1)*** (110601)***

23.21 (1)*** 35.13 (1)***

Abbreviations: SD, standard deviation; VAMC, VA Medical Center. Note: Significance testing carried out by Pearson c2 test for homogeneity for categorical variables and the 2-sample t-test for continuous variables. p Values are denoted by ***p < .001. * Depression treatment is defined as minimally appropriate threshold of depression treatment of having received either
60 days of depression prescriptions, or
4 administratively identified mental health visits, or
3 psychotherapy visits (1 ¼ yes) within 1 year of the new episode of depression. y Depression follow-up at 180 days is a measure of timeliness of in-person visits, defined as having received either
3 mental health specialty, psychotherapy, or primary care visits with International Classification of Diseases, Ninth Edition diagnoses for depression within 180 days of the new episode of depression. z Co-payment status is defined as those required to pay a co-payment for health care services or medications, those who are co-payment exempt, and not applicable/ unknown, determined by percent of disability from service-connected condition, which is a condition incurred or aggravated injury or illness during active military service, and financial status based on income adjusted for household size, geography, and calendar year. x Additional psychiatric comorbidities include the presence of any of the following conditions: posttraumatic stress disorder, anxiety, and alcohol and/or drug use.

Information Resource Center, 2011). Last, we included the organizational enabling factor of location of VA care as a dichotomous indicator of VA medical center versus community-based clinic. Determination of a patients’ home site of care is described elsewhere (Farmer et al., 2016).

patients with depression along with other psychiatric comorbidities. All analyses were conducted in Stata/SE 13.1 (StataCorp, College Station, TX).

Results Statistical Analysis We conducted univariate analyses (Pearson’s c2 test for homogeneity, Student’s two-sample t test) to describe and compare the primary care population of longitudinal patients with a new episode of depression by gender, covariates, and outcomes. We used multivariate logistic regression to estimate separately the association between sex and our two process outcome variables: receipt of minimally appropriate treatment and receipt of follow-up. Given the demographic differences for each sex, we compared models using the full sample to models stratified by sex. Results for the two models were similar for each of our two outcome variables. We therefore used the full sample estimates and regressions in our final analyses. We also tested a model that included an interaction variable between sex and depression along with other psychiatric comorbidities against our two process outcomes. All multivariate models controlled for covariates and allowed for clustering by treatment site. We used full-sample multivariate logistic regressions to calculate predictive probabilities for each depression care outcome for each gender, and for patients with depression only, as well as for

Table 1 presents the univariate gender differences across all covariates and depression care outcomes. The analytic sample of veterans with a new episode of depression (n ¼ 110,603) included mostly men (91%). Women veterans with new depression, compared with male veterans, were significantly younger (mean age, 44 vs. 57 years old), more likely to be African American (25.9% vs. 15.7%), less likely to be married (31.0% vs. 51.8%), more likely to be copayment exempt (80.2% vs. 74.1%), and had slightly lower rates of additional psychiatric comorbidities (42.6% vs. 45.2%). In bivariate analysis of depression outcomes, women veterans, compared with male veterans, were slightly more likely to have received minimally appropriate depression treatment over the year (85.3% vs. 82.4%) and follow-up depression care within 180 days (67.3% vs. 62.7%). Similar sex patterns emerged for patients with depression only or depression along with other psychiatric comorbidities. Only 9% of veterans who had depression along with other psychiatric comorbidities did not receive minimally appropriate treatment over the year, whereas 24.1% of veterans with depression only did not meet the threshold. Similarly, although 20.9% of veterans who had depression along

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Table 2 Multivariate Adjusted Odds Ratios for Each Depression Care Outcome among Veterans

Female Age Race/ethnicity (REF ¼ White veterans) Black veterans Other Unknown/declined/missing Marital status (REF ¼ married) Divorced/separated Never married/single Widowed Unknown Co-pay status (REF ¼ co-pay required) Exempt Not applicable/unknown Other psychiatric comorbidities Location of care at VA community-based clinics Constant Overall c2 statistic

Depression Treatment,* OR (95% CI)

p

Depression Follow-up at 180 Days,y OR (95% CI)

p

1.17 (1.10–1.25) 0.99 (0.99–1.00)

<.001 <.001

0.95 (0.90–1.00) 0.98 (0.98–0.99)

.07 <.001

0.96 (0.89–1.03) 1.04 (0.95–1.14) 1.01 (0.94–1.08)

.22 .43 .78

1.32 (1.23–1.42) 1.32 (1.22–1.43) 1.06 (0.98–1.14)

<.001 <.001 .17

0.95 0.95 0.99 1.15

.01 .10 .80 .06

1.12 1.18 0.99 1.12

(1.08–1.17) (1.12–1.23) (0.92–1.06) (0.98–1.27)

<.001 <.001 .68 .09

1.13 (1.08–1.17) 1.18 (1.07–1.28) 3.21 (3.08–3.35) 0.96 (0.85–1.07) 2.28 (2.04–2.55) 3751.33

<.001 <.001 <.001 .44 <.001

(0.91–0.99) (0.89–1.01) (0.92–1.07) (0.99–1.34)

1.24 (1.19–1.29) 1.33 (1.21–1.46) 3.03 (2.88–3.19) 1.01 (0.91–1.11) 3.95 (3.47–4.51) 2946.36

<.001 <.001 <.001 .89 <.001

Abbreviation: CI, confidence interval; OR, odds ratio; REF, reference group. Note: All models are cluster corrected and controlled for age, race/ethnicity, marital status, co-payment status, other psychiatric co-morbidities including posttraumatic stress disorder, anxiety, and/or drug use, and location of clinic care at a VA medical center versus a VA community-based clinic (not located at a VA medical center). Interactions between gender and additional psychiatric comorbidities were not significant for either outcome, and therefore not included in the final model specifications. * Depression treatment is defined as minimally appropriate threshold of depression treatment of having received either
60 days of depression prescriptions, or
4 administratively identified mental health visits, or
3 psychotherapy visits (1 ¼ yes) within 1 year of the new episode of depression. y Depression follow-up at 180 days is a measure of timeliness of in-person visits, defined as having received either
3 mental health specialty, psychotherapy, or primary care visits with International Classification of Diseases, Ninth Edition diagnoses for depression within 180 days of the new episode of depression.

with other psychiatric comorbidities did not receive adequate depression care follow-up visits within 180 days, 49.8% of veterans with depression only did not meet the threshold for appropriate depression follow-up care. All differences were significant at p < .001. The adjusted odds ratios and p values of the multivariate regression for minimally appropriate treatment and follow-up at 180 days are presented in Table 2. On average, women veterans had modest yet statistically significantly increased odds of minimally appropriate depression treatment compared with male veterans. As age increased annually, or if a veteran was divorced/separated, there were significantly decreased odds of receiving minimally appropriate depression treatment; meanwhile, being co-pay exempt and having other psychiatric comorbidities significantly increased the odds of receiving minimally appropriate depression treatment. The effect of location of VA care and race/ethnicity were not significant. Regarding follow-up at 180 days, the odds were not significant by sex. As age increased annually the odds of follow-up significantly decreased; Black veterans or veterans identifying as other ethnic groups had increased odds compared with White veterans. Being divorced/separated, never married/single, co-pay exempt, or having other psychiatric comorbidities significantly increased the odds of receiving follow-up. Location of VA care was not statistically significant for follow-up. The interaction between sex and other psychiatric comorbidities was not significant for either outcome (not shown). Table 3 shows the predicted probabilities along with 95% confidence intervals (CI) from the multivariate logistic regression models by gender and the presence of depression only or depression comorbid with other psychiatric conditions for both depression care outcomes. Contrasts between genders are also shown along with their associated p values. For minimally appropriate depression treatment over one year for those with depression only, the predicted probability for men

was 76% (95% CI, 75%–77%) compared with women at 79% (95% CI, 78%–80%); there was a small statistically significant gender difference, favoring women (difference ¼ 3%; p < .001). For those with depression comorbid with other psychiatric conditions, the predicted probability of minimally appropriate treatment for men was 91% (95% CI, 90%–91%) compared with women at 92% (95% CI, 91%–93%); there was a small statistically significant gender difference, favoring women (difference ¼ 1%; p < .001). For follow-up at 180 days, there were no sex differences for those with depression only and depression comorbid with other psychiatric conditions. The predicted probabilities for follow-up were lower (51%) for patients with depression only, compared with 77% for those with depression comorbid with other psychiatric conditions. Discussion This large, primary care-based examination of gender differences in depression care found that three-quarters of veterans received minimally appropriate depression treatment within 1 year of a new episode of depression, and that women veterans had a significant, slightly higher probability than male veterans of receiving minimally appropriate depression treatment, whether or not other psychiatric comorbidities were present. However, there was only a three-percentage point difference favoring women for those with depression only, and a onepercentage point difference for those with depression and other psychiatric comorbidities. Given these small differences, statistical significance may reflect our large sample size, although a one-to-three percentage point difference reflects approximately 1,106 to 3,310 impacted veterans within our sample. No gender differences were found in the likelihood of minimum appropriate in-person follow-up visits within 180 days of depression diagnosis. Overall our results suggest near equivalence between men and women in depression care among

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Table 3 Predicted Probabilities of Depression Care Outcomes by Genders and Comorbidity, Among Veterans Depression Care Outcome

Depression treatment (1) Depression only (2) Other psychiatric comorbidities Follow-up at 180 days (1) Depression only (2) Other psychiatric comorbidities

Contrast, D

Gender (95% CI) Men

Women

(F vs. M)

0.76 (0.75–0.77) 0.91 (0.90–0.91)

0.79 (0.78–0.80) 0.92 (0.91–0.93)

0.03 0.01

0.52 (0.51–0.54) 0.77 (0.76–0.78)

0.51 (0.49–0.53) 0.77 (0.75–0.78)

0.01 0.01

p <.001 <.001 .07 .08

Abbreviations: CI, confidence interval; OR, odds ratio. Note: All models are cluster corrected and controlled for age, race/ethnicity, marital status, co-payment status, other psychiatric comorbidities including posttraumatic stress disorder, anxiety and/or drug use, and location of clinic care at a VA medical center versus a VA community based clinic (not located at a VA medical center). Interactions between gender and additional psychiatric co-morbidities were not significant for either outcome, and therefore not included in the final model specifications.

the full population of veterans seen in VA primary care with a new episode of depression. This is notable news for VA, particularly given the concerns over equitable care between the sexes (Frayne et al., 2010; Yano et al., 2011), and suggests that VA efforts to improve care, including mental health care, for women veterans over the past two decades (Ross, Garovoy, McCutcheon & Strauss, 2015; Yano, Haskell, & Hayes, 2014) have had an impact. Given the high rate of additional growth in the number of women veterans projected to access care in the VA system in the decades to come, achieving comparable care between the sexes is notable. Overall in multivariate modeling, we found female sex significantly predicted receipt of minimally adequate treatment for depression. Despite this, follow-up rates for men and women veterans are of concern. Only one-half of men and women veterans who had depression only and about three-quarters of those with other comorbid psychiatric illness were predicted to have timely in-person follow-up. Potential explanations for these low rates of follow-up include continued perceived stigmatization of depression leading to nonattendance, lower motivation to attend multiple in-person visits, or preferences for different types of minimally appropriate treatment, limited patient resources and/or support to pay for in-person visits, and the limited availability of providers, particularly in rurally located clinics. In-person follow-up is a critical component of depression quality of care, which can lead to important health-promoting behaviors and outcomes for depressed persons, such as increased rates of exercise, weight control, and chronic disease management, and decreased rates of smoking and substance use (Wells et al., 2013). Timely follow-up can facilitate initiation of treatment (medication or psychotherapy) among those who resist it, and adjustments to care that may enhance both overall success in reducing symptoms and promptness of achieving symptom remission. Early follow-up care also may serve as a critical avenue for initially engaging patients in depression treatment, and our findings highlight opportunities for quality improvement initiatives to better engage patients and ensure appropriate follow-up. This study has limitations. We had a large regionally diverse sample and successfully provided a snapshot of care over FY10, but cannot extrapolate time trends. Because the VA has been aggressively expanding programming and services for women veterans in the past decade (Yano, Haskell, & Hayes, 2014), future work is needed to examine the trends beyond FY10. Our study relied on administrative data, which did not include symptom severity data. Data on race/ethnicity in VA administrative data may be imprecise, particularly in having sufficient numbers of

veterans who identify themselves in the other race/ethnic category (Saha et al., 2008). Non-VA utilization of health care services was not captured, which may be of particular importance for patients who are co-managed for specific veteran benefits (e.g., filling prescriptions) but otherwise receive health care in the community. We attempted to capture other non–face-to-face measures of depression care management, specifically telephone care management. However, in FY10 there were too few data points in the administrative data for telephone care management of depression to be evaluated. Also, the definitions of our outcome measures captured the lowest threshold of care and may overestimate positive clinical process outcomes. Notably, the national expert panel vigorously discussed the pros and cons of increased stringency of measures, and by consensus agreed that the minimum threshold is an appropriate beginning for improvement efforts. Future work is needed to refine more stringent levels of depression care. It is unlikely, however, that these factors would affect our overall conclusions on sex equity. This research focused on a population of patients with a new episode of detected depression, and therefore could not examine potential detection differences for depression by sex. The greater prevalence of depression among women than men is known among providers, and depression may also be perceived as less stigmatizing among women in both the general and veteran populations creating a potential bias in diagnosis where women are more likely to be diagnosed (Kessler, 2003). Therefore, our population may reflect a provider bias in mental health diagnoses by gender, and possibly under-recognition of depression among male veterans. Furthermore, time pressures may limit recognition of depression by providers during visits, as well as other acute medical or social concerns of the patient, and other factors that may unconsciously bias provider expectations. Although our findings do not speak to nuances in disease states, we found that, among patients with a new episode of depression detected, women and men received comparable minimally appropriate depression treatment and follow-up. Implications for Practice and/or Policy Knowing that the VA, the largest health care system in the United States, can achieve parity between men and women for depression care sets a positive benchmark for other large integrated systems, and allows policymakers and providers to focus on other complexities of depression care within primary care for both genders. One such complexity is the influence of comorbid psychiatric illnesses on depression care. In evaluating the effect of having comorbid psychiatric diseases on receipt of depression

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care, we found the difference in receipt of minimally appropriate depression was approximately 13% to 15% higher for those with comorbidities, and 25% higher for follow-up within 180 days, compared with those with depression only. These findings are consistent with findings from Higashi et al. (2007), who found that quality of care, as measured by quality indicators related to processes of care including depression, increased as the number of comorbidities increased. Our findings are potentially explained by increased opportunities to identify depression during visits for other psychiatric conditions, a possible overlap in care for common psychiatric conditions during the same visit, or perhaps providers were more inclined to ask about mental health symptoms more broadly when treating patients with a psychiatric diagnosis. The quality of the patient–provider relationship or other organizational factors, aside from clinic location, may elucidate further mechanisms of increased depression care quality in patients with other psychiatric comorbidities, and are ripe areas for further exploration. Follow-up studies addressing organizational characteristics, such as clinic types, care arrangements and models, and number and types of visits are imperative to deepen our understanding of what factors may help to improve and move forward the overall quality of depression care. Conclusions Our findings suggest that equity in receipt of minimally appropriate depression care for men and women veterans treated in VA settings is at least as good as, or better than the general public (Substance Abuse and Mental Health Services Administration, 2009). Our findings also raise important questions for depression care for both genders regarding the lower rates of early follow-up visits and of treatment completion among those with depression only as compared with those with psychiatric comorbidities. National policymakers and local operations leaders can use these findings to inform their understanding of equitable depression care between men and women in the primary care setting. Acknowledgments The authors acknowledge Dr. David A. Ganz for his detailed editorial support. Earlier versions of this work have been presented at the 2015 VA HSR&D/QUERI National Conference and 2015 VA Quality Scholar Summer Institute. References Active Duty Master Personnel File, Military Academies. (2014). Table of active duty females by rank/grade and service. Available: www.dmdc.osd.mil/appj/ dwp/dwp_reports.jsp. Accessed: January 1, 2016. Andersen, R. (1968). A behavioral model of families’ use of health services. Chicago: Center for Health Administration Studies, University of Chicago. Andersen, R. (1995). Revisiting the behavioral model and access to medical care: Does it matter? Journal of Health Social Behavior, 36(1), 1–10. Andersen, R., & Davidson, P. (2007). Improving access to care in America. San Francisco: Jossey-Bass. Chander, G., & McCaul, M. (2003). Co-occurring psychiatric disorders in women with addictions. Obstetrics and Gynecology Clinics of North America, 30(3), 469–481. Dobie, J. D., Maynard, C., Kivlahan, D. R., Johnson, K. M., Simpson, T., David, A. C., & Bradley, K. (2006). Posttraumatic stress disorder screening status is associated with increased VA medical and surgical utilization in women. Journal of General Internal Medicine, 21, S58–S64. Farmer, M. M., Rubenstein, L. V., Sherbourne, C., Huynh, A., Chu, K., Lam, C. A., . Chaney, E. F. (2016). Depression quality of care: Measuring quality over time using VA electronic medical record data. Journal of General Internal Medicine, 31(Suppl 1), 36–45.

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Frayne, S., Phibbs, C., Friedman, S., Berg, E., Ananth, L., Iqbal, S., . Herrera, L. (2010). Sourcebook: Women veterans in the Veterans Health Administration. Volume 1. Sociodemographic characteristics and use of V.H.A. care. Washington, DC: U.S. Department of Veterans Affairs. Frayne, S. M., Phibbs, C. S., Saechao, F., Maisel, N. C., Friedman, S. A., Finlay, A., . Iqbal, S. (2014). Sourcebook: Women veterans in the Veterans Health Administration. Volume 3: Sociodemographic, utilization, costs of care and health profile. Washington, DC: U.S. Department of Veterans Affairs. Gelberg, L., Andersen, R. M., & Leake, B. D. (2003). The behavioral model for vulnerable populations: Application to medical care use and outcomes for homeless people. Health Services Research, 34(6), 1273–1302. Goldman, L. S., Nielson, N. H., & Champion, H. C. (1999). Awareness, diagnosis, and treatment of depression. Journal of General Internal Medicine, 14(9), 569–580. Higashi, T., Wenger, N. S., Adams, J. L., Fung, C., Roland, M., McGlynn, E. A., . Shekelle, P. G. (2007). Relationship between number of medical conditions and quality of care. New England Journal of Medicine, 356(24), 2496–2504. Hynes, D. M., Perrin, R. A., Rappaport, S., Stevens, J. M., & Demakis, J. G. (2004). Informatics resources to support health care quality improvement in the Veterans Health Administration. Journal of the American Medical Informatics Association, 11(5), 344–350. Kahn, K. L., Tisnado, D. M., Adams, J. L., Liu, H., Chen, W. P., Hu, F. A., . Damberg, C. L. (2007). Does ambulatory process of care predict healthrelated quality of life outcomes for patients with chronic disease? Health Services Research, 42(1 Pt 1), 63–83. Katon, W. (2003). Clinical and health services relationships between major depression, depressive symptoms, and general medical illness. Biological Psychiatry, 54(3), 216–226. Kaufman, J., & Charney, D. (2000). Comorbidity of mood and anxiety disorders. Depression and Anxiety, 12(Suppl 1), 69–76. Kessler, R. (2003). Epidemiology of women and depression. Journal of Affective Disorders, 74, 5–13. Liu, C., Bolkan, C., Chan, D., Yano, E., Rubenstein, L. V., & Chaney, E. (2009). Dual use of VA and non-VA services among primary care patients with depression. Journal of General Internal Medicine, 24(3), 305–311. Mathers, C., & Loncar, D. (2006). Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med, 3(11), 2011–2030. National Alliance on Mental Illness. (2009). Depression and veterans fact sheet. Available: www.ouhsc.edu/TVServices/misc/GEC/Sorocco/NAMIFact2009. pdf. Accessed: July 16, 2014. Office of the Actuary Department of Veterans Affairs. (2011). Veteran population projections: FY2010 to FY2040. Available: http://www.va.gov/vetdata/docs/ QuickFacts/Population_quickfacts.pdf. Accessed: January 23, 2015. Pavao, J., Turchik, J., Hyun, J., Karpenko, J., Saweikis, M., McCutcheon, S., . Kimerling, R. (2013). Military sexual trauma among homeless veterans. Journal of General Internal Medicine, 28(S2), 536–541. Post, E. P., Metzger, M., Dumas, P., & Lehmann, L. (2010). Integrating mental health into primary care within the Veterans Health Administration. Families, Systems & Health, 28(2), 83–90. Ross, I., Garovoy, N., McCutcheon, S., & Strauss, J. L. (2015). The woman veteran experience. In Ritchie, E. C., & Naclerio, A. (Eds.), Women at war. New York: Oxford University Press. Runnals, J. J., Garovoy, N., McCutcheon, S. J., Robbins, A. T., Mann-Wrobel, M. C., & Elliott, A. (2014). Systematic review of women veterans’ mental health. Womens Health Issues, 24(5), 485–502. Saha, S., Freeman, M., Toure, J., Tippens, K. M., Weeks, C., & Ibrahim, S. (2008). Racial and ethnic disparities in the VA health care system: A systematic review. Journal of General Internal Medicine, 23(5), 654–671. Seal, K., Bertenthal, D., Miner, C., Sen, S., & Marmar, C. (2007). Bringing the war back home: Mental health disorders among 103,788 US veterans returning from Iraq and Afghanistan seen at Department of Veterans Affairs facilities. Archives of Internal Medicine, 167(5), 476–482. Schnurr, P. P., Friedman, M. J., Sengupta, A., Jankowski, M. K., & Holmes, T. (2000). PTSD and utilization of medical treatment services among male Vietnam veterans. Journal Nervous and Mental Disease, 188, 496–504. Simon, G. E., Katon, W. J., Lin, E. H., Rutter, C., Manning, W. G., Von Korff, M., . Young, B. A. (2007). Cost-effectiveness of systematic depression treatment among people with diabetes mellitus. Archives of General Psychiatry, 64(1), 65–72. Substance Abuse and Mental Health Services Administration. (2009). Results from the 2008 National Survey on Drug Use and Health: National findings. Available: http://archive.samhsa.gov/data/NSDUH/2k8nsduh/2k8Results.htm. Accessed: January 23, 2015. U.S. Department of Veterans Affairs. (2015a). Federal benefits for veterans, dependents and survivors. Available: www.va.gov/opa/publications/benefits_ book/benefits_chap02.asp. Accessed: August 1, 2015. U.S. Department of Veterans Affairs. (2015b). Health benefits: Financial assessment. U.S. Department of Veterans Affairs. Available: www.va.gov/ healthbenefits/cost/financial_assessment.asp. Accessed: October 15, 2015.

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U.S. Department of Veterans Affairs. (2013). Means test and geographic-based means test and maximum annual rates of pension for calendar year 2014. Available: www.va.gov/healthbenefits/resources/publications/IB10-497_ means_test_GMT_pension_threshold_oct_13.pdf. Accessed: October 12, 2015. V.A. Information Resource Center. (2011). V.H.A. medical S.A.S. outpatient and inpatient encounters dataset FY2009: VIReC Research user guide. Hines, IL: U.S. Department of Veterans Affairs. Washington, D. L., Yano, E. M., Simon, B., & Sun, S. (2006a). To use or not to use: What influences why women veterans choose VA health care. Journal of General Internal Medicine, 21, S11–S18. Washington, D. L., Yano, E. M., & Horner, R. (2006b). The health and health care of women veterans: Perspectives, new insights, and future research. Journal of General Internal Medicine, 21, S3–S4. Wells, K., Jones, L., Chung, B., Dixon, E. L., Tang, L., Gilmore, J., . Miranda, K. (2013). Community-partnered cluster-randomized comparative effectiveness trial of community engagement and planning or resources for services to address depression disparities. Journal of General Internal Medicine, 28(10), 1268–1278. Yano, E. M., Bastian, L. A., Bean-Mayberry, B., Eisen, S., Frayne, S., Hayes, P., . Washington, D. L. (2011). Using research to transform care for women veterans: Advancing the research agenda and enhancing research-clinical partnerships. Womens Health Issues, 21(4 Suppl), S573–S583. Yano, E. M., Haskell, S., & Hayes, P. (2014). Delivery of gender sensitive comprehensive primary care to women veterans: Implications for VA patient aligned care teams. Journal of General Internal Medicine, 29(S2), 703–707.

Martin L. Lee, PhD, is an Adjunct Professor in UCLA’s Department of Biostatistics. His research interests include clinical trial design, particularly as they pertain to biologic and biotechnologically produced proteins, statistical test procedures for bioequivalency studies, and pharmacoeconomic modeling.

Alexis K. Huynh, PhD, MPH, is a health care policy analyst and health services researcher at VA HSR&D Center for the Study of Healthcare Innovation, Implementation and Policy, with expertise in mixed methods research designs, program evaluation, implementation science, and public health.

Karen Chu, MS, is a statistical analyst at the VA HSR&D Center for Innovation for the Study of Healthcare Innovation, Implementation and Policy, experienced working with complex datasets, including medical claims datasets, national survey data, quality-of-life, and clinical trial data.

Jennifer L. Strauss, PhD, is National Women’s Mental-Health Program Manager for Mental Health Services, VA, and Associate Professor of Psychiatry and Behavioral Sciences, Duke University. She develops policy for women veterans, and has interests in PTSD, military sexual trauma, and collaborative disease management.

Maureen E. Metzger, PhD, MPH, is National Program Manager for Primary Care-Mental Health Integration at VA. Her interests include the use of patientreported outcomes in clinical care and quality improvement, population health applications of administrative data, and program implementation and evaluation.

Author Descriptions Christine A. Lam, MD, MBA, MSHS, during this project, was a VA Quality Scholar and Internist, VA Greater Los Angeles Healthcare System, and Assistant Project Scientist, UCLA. Her interests include women’s health, quality improvement, and collaborative disease management in the primary care setting.

Cathy Sherbourne, PhD, is a sociologist and senior policy researcher at RAND. Her research includes health outcome measurement for adults and children, satisfaction, and analyses of life stress, social and role functioning, social support, with a focus on mental health issues.

Lillian Gelberg, MD, MSPH, a family physician, health services researcher, and professor at UCLA and the VA Greater Los Angeles Healthcare System, conducts clinical trials to improve healthcare for homeless populations, reduce risky drug use, and promote healthy lifestyles in low-income populations.

Edward P. Post, MD, PhD, is Associate Professor of Internal Medicine, University of Michigan. He directs the national Primary Care-Mental Health Integration program for VA, and his research interests include mental health services, medical comorbidity, and collaborative disease management in primary care.

Lisa V. Rubenstein, MD, MSPH, is a Professor of Medicine and Public Health at VA Greater Los Angeles Healthcare System and UCLA, and senior natural scientist at the RAND. Her research focuses on redesigning health care systems through quality improvement and implementation research.

Melissa M. Farmer, PhD, is a core investigator at the VA HSR&D Center for Innovation for the Study of Healthcare Innovation, Implementation and Policy. Her research focuses on women’s health, cardiovascular risk-reduction and disease prevention, organizational variations in care, and performance/quality measurement.