Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2010 Nov 1.
Published in final edited form as: Adm Policy Ment Health. 2009 Jul 16;36(6):406–415. doi: 10.1007/s10488-009-0230-2

Antidepressant adherence after psychiatric hospitalization

Kara Zivin 1,2,3, Dara Ganoczy 1, Paul N Pfeiffer 1,2,3, Erin M Miller 2,3, Marcia Valenstein 1,2,3
PMCID: PMC2941212  NIHMSID: NIHMS228942  PMID: 19609666

Abstract

Objective

Depressed patients discharged from psychiatric hospitalizations face increased risks for adverse outcomes including suicide, yet antidepressant adherence rates during this high-risk period are unknown. Using Veterans Affairs (VA) data, we assessed antidepressant adherence and predictors of poor adherence among depressed veterans following psychiatric hospitalization.

Method

We identified VA patients nationwide with depressive disorders who had a psychiatric hospitalization between April 1, 1999 and September 30, 2003, received antidepressant medication, and had an outpatient appointment following discharge. We calculated medication possession ratios (MPRs), a measure of medication adherence, within three and six months following discharge. We assessed patient factors associated with having lower levels of adherence (MPRs <0.8) after discharge.

Results

20,931 and 23,182 patients met criteria for three and six month MPRs. The mean three month MPR was 0.79 (s.d.=0.37). The mean six month MPR was 0.66 (s.d.=0.40). Patients with poorer adherence were male, younger, non-white, and had a substance abuse disorder, but were less likely to have PTSD or other anxiety disorders.

Conclusion

Poor antidepressant adherence is common among depressed patients after psychiatric hospitalization. Efforts to improve adherence at this time may be critical in improving the outcomes of these high-risk patients.

Keywords: antidepressant adherence, psychiatric hospitalization discharge, veterans

Introduction

Antidepressant treatment is an important and effective component in the management of many patients with depressive disorders, particularly those with major depression.(Geddes et al., 2003; Keller, Hirschfeld, Demyttenaere, & Baldwin, 2002; Montgomery, 2006) Among patients who begin new antidepressant treatment in outpatient settings, incomplete adherence increases the likelihood of depression relapse or recurrence.(Katon et al., 2001; Melfi et al., 1998)

Unfortunately, a broad literature demonstrates suboptimal rates of adherence to antidepressant medications following new antidepressant starts among outpatients (e.g., those with no antidepressant prescriptions for the prior six months).(Bull et al., 2002; Cantrell, Eaddy, Shah, Regan, & Sokol, 2006; Katon, von Korff, Lin, Bush, & Ormel, 1992) Poor adherence may arise from side effects,(Burra et al., 2007; Goethe, Woolley, Cardoni, Woznicki, & Piez, 2007) patient beliefs and attitudes towards antidepressant use and mental disorders such as fears of addiction or habituation,(Givens et al., 2006; Melartin et al., 2005; Ozmen et al., 2005) and lack of patient education regarding the importance of continuing medication use even when symptoms improve.(Maidment, Livingston, & Katona, 2002) (Givens et al., 2006; Melartin et al., 2005; Ozmen et al., 2005)

However, despite a substantial literature on antidepressant adherence following treatment initiation for new depression episodes in outpatient settings,(Bambauer, Soumerai, Adams, Zhang, & Ross-Degnan, 2007; Busch, Leslie, & Rosenheck, 2004; Olfson, Marcus, Tedeschi, & Wan, 2006; Robinson et al., 2006; Sewitch, Blais, Rahme, Bexton, & Galarneau, 2007) there are few studies assessing antidepressant adherence following discharge from a psychiatric hospitalization. Although the majority of patients with depression are treated in outpatient settings, patients requiring inpatient care for depression are likely to have more severe depressive disorders, higher rates of disability, poorer outcomes, and higher costs of care.(Goethe et al., 2007) The Goethe et al study was one of the few to examine differences in antidepressant adherence rates among patients with both inpatient and outpatient treatment, finding no differences in adherence by location of initial treatment, with about 25% discontinuing the antidepressant within three months. However, this study had a relatively small sample size and relied on self-reported antidepressant adherence.

Given that suicide rates in the first twelve weeks following inpatient stays are five times higher than the base rate of suicide for the overall VA depression population,(Valenstein et al., 2009) patients emerging from inpatient stays stand to benefit more from improved antidepressant adherence than patients treated in outpatient settings – and they represent an important target population for adherence-enhancing interventions.

Therefore, our study assessed antidepressant adherence in the first three and six months following discharge of depressed VA patients from a psychiatric hospitalization. Using VA pharmacy data, we assessed adherence during these time periods using medication possession ratios (MPRs),(Cantrell et al., 2006; Finley et al., 2002; Valenstein et al., 2002) defined as the total number of days’ supply received divided by the number of days’ supply needed for continuous use. We also examined demographic and clinical characteristics associated with poor adherence.

The goal of the study was to inform future efforts to address adherence issues among depressed patients being discharged from the hospital. We hypothesized that: 1) there would be substantial problems with antidepressant adherence among patients with depression newly discharged from inpatient units, and 2) patients with comorbid psychiatric conditions would have lower rates of adherence than depressed patients without comorbid conditions during these time periods.

Methods

Study populations

We used data on patient demographic characteristics, diagnoses, and pharmacy use from the VA National Registry for Depression (NARDEP), which was created and maintained by the Serious Mental Illness Treatment Research and Evaluation Center (SMITREC) located in Ann Arbor, Michigan.(Blow et al., 2003) The NARDEP integrates outpatient pharmacy data from the VA Pharmacy Benefits Management Group (PBM) with other VA administrative data for patients with depression diagnoses.(Smith & Joseph, 2003)

We examined antidepressant adherence in the three and six months post-discharge from psychiatric hospitalization among VA patients with depression. Specifically, patients were included in the study if they 1) received at least two depression diagnoses or one diagnosis followed by an antidepressant fill between April 1, 1999 and September 30, 2003; 2) were hospitalized for psychiatric reasons during that time; 3) received an antidepressant fill at time of discharge (up to three days before to two days after discharge); 4) had an outpatient visit within the three or six month post-discharge follow-up period; 5) received only one type of antidepressant within the three-or six-month post-discharge periods; and 6) had valid MPRs by having at least 90 total days outside of the hospital following discharge.

Our rationale for requiring either two diagnoses or a diagnosis and a prescription to identify a patient with depressive disorders was to ensure adequate specificity in our identification of depressive disorder. These criteria are similar to those used in several earlier studies of depression, using administrative databases.(Kerr, McGlynn, Van Vorst, & Wickstrom, 2000; Spettell et al., 2003) Conservatively, we also included patients only if they had an outpatient appointment after VA discharge to ensure that they were receiving their follow up care within the VA and not another health system. Patients were excluded from the analyses if they did not have an antidepressant prescription post-hospitalization, regardless if they had a prescription prior to hospitalization, if they had more than one type of antidepressant prescribed during the three or six month follow up period, or if they died within 90 days of hospitalization discharge.

Patient depression diagnoses were identified from the NARDEP using the International Classification of Diseases, Ninth Revision (ICD-9) diagnostic codes, which are presented in Appendix A. All types of antidepressant medications available from VA pharmacies were included; however amitriptyline, mirtazapine, nortriptyline, and trazodone (e.g., tricyclic or tetracyclic antidepressants) were included in analyses only if doses were ≥75 mg, ≥15 mg, ≥25 mg, and ≥300 mg per day respectively, as these medications are often used for other indications, such as sleep or pain at lower doses.(Richeimer, Bajwa, Kahraman, Ransil, & Warfield, 1997; Wiegand, 2008) (Please see Appendix B for full list of antidepressant medications used) By excluding patients who received only antidepressant medications that are commonly used in low doses used for other indications, we sought to prevent false positive identifications of patients as depressed.

Of the 37,058 patients who received an antidepressant fill at time of psychiatric discharge, 26,051 had at least one outpatient visit in the three months post-discharge and used only one type of antidepressant, and 21,289 (82%) had at least 90 outpatient days during the three months following hospital discharge, allowing calculation of a stable MPR. These patients constituted the three month patient population. During the entire three month period, six patients died; four of these patients had sufficient medication data for MPRs and two did not. 24,345 patients had at least one outpatient visit in the six months post-discharge and used only one type of antidepressant. Of these, 23,582 (97%) had at least 90 outpatient days during the six month post discharge period, allowing calculation of a stable MPR. These patients constituted the six month population. During the entire 6 month period, 322 patients died; 275 had sufficient medication data for MPRs and 47 did not. Seventy six percent of patients had only one type of antidepressant during the three months post discharge and 70% of patients had only one type of antidepressant during the six months post-discharge.

Study measures

Patient characteristics

We obtained data on patient demographic characteristics including age (18-44, 45-64, ≥65), sex, race (black, other, unknown, white), and ethnicity (Hispanic or not) from the NARDEP. Other race included patients of Asian, Native Hawaiian, Pacific Islander, or Native American race/ethnicity and patients who were multi-racial.

Patient clinical characteristics included the following diagnoses in the twelve months prior to discharge including: any substance use disorder, post traumatic stress disorder, any other anxiety disorder, any personality disorder, and bipolar disorder II. Patients with schizophrenia, schizoaffective disorder, and bipolar disorder I were excluded from the study. ICD-9 codes for all clinical diagnoses are presented in Appendix A.

Measures of adherence

Data on medication fills and days supply dispensed were used to calculate MPRs. MPRs were calculated by adding the total number of days’ supply of antidepressant medication that patients received from the outpatient pharmacy during the three and six months post-discharge (up to three days before to two days after discharge). The total number of days’ supply received was divided by the number of days’ supply needed for continuous use during outpatient periods. Any days that patients spend in institutional settings (including VA hospitals or nursing homes) were subtracted from the outpatient days’ supply needed for MPR calculations. In sum, MPR = number of days’ supply of antidepressant received from outpatient pharmacy / number of days’ supply needed for continuous outpatient antidepressant use. An MPR of 1.0 therefore indicates full adherence, whereas an MPR of 0.5 indicates that a patient received only half the medication needed to ensure continuous outpatient use.

We calculated mean adherence (mean MPRs) for the three and six month follow-up groups. We chose three and six month follow up time periods for a course of antidepressant treatment to be in accordance with standard practice for antidepressant treatment for acute and continuation treatment.(National Committee for Quality Assurance, 2003; National Committee for Quality Assurance (NCQA), 2003) Patients with six months of follow-up would also be part of the three month follow-up group. We also categorized antidepressant adherence into poor and good adherence for three and six months post-discharge. Patients with MPRs <0.8 were considered to have poor adherence, while patients with MPRs ≥0.8 were considered to have good antidepressant adherence. While there is no gold standard metric for calculating either adherence or good adherence,(Vermeire, Hearnshaw, Van Royen, & Denekens, 2001) taking 80% of one's prescribed medication regimen has been considered a reasonable cut-point for good adherence in other studies using MPRs.(Cantrell et al., 2006; Jones, Turvey, & Carney-Doebbeling, 2006; Sikka, Xia, & Aubert, 2005)

Analytic framework

First, we completed basic descriptive statistics using Wilcoxon and chi-square tests for means and frequencies. Next, we used logistic regression analysis to examine patient demographic and clinical characteristics associated with poor antidepressant adherence three and six months post-hospitalization. All predictors were included simultaneously, and the statistical significance level was set at p<0.05 for all analyses. All statistical analyses were completed using SAS software version 9.1.

Results

Clinical and demographic characteristics of patients with three (N=20,931) and six month (N=23,182) MPRs are presented in Table 1. The patient populations for both the three and six month MPR cohorts were predominantly male (94-95%), white (72-73%), and middle aged (mean age was 52). Psychiatric comorbidities were quite prevalent, as 59-61% of patients also had a substance use disorder, 32-33% had a PTSD diagnosis, 21% had other anxiety disorders, and 13% had personality disorders.

Table 1.

Characteristics of post-discharge depressed patients with three and six month antidepressant medication possession ratios (MPRs)*

3 month MPRs 6 month MPRs
All patients N (%) MPR < 0.80 MPR ≥ 0.80 p-value All patients N (%) MPR < 0.80 MPR ≥ 0.80 p-value
(N=20,931) (N=10,243) (N=10,688) (N=23,182) (N=13,835) (N=9347)
Sex
  Male 19,744 (94.3) 9722 (94.9) 10,022 (93.8) <0.001 21,946 (94.7) 13,132 (94.9) 8814 (94.3) <0.05
  Female 1187 (5.7) 521 (5.1) 666 (6.2) 1236 (5.3) 703 (5.1) 533 (5.7)
Age
  Mean 52.0 (12.4) 50.4 (11.9) 53.5 (12.7) <0.001 52.1 (12.5) 50.4 (12.1) 54.6 (12.7) <0.001
  18-44 5532 (26.4) 3135 (30.6) 2397 (22.4) <0.001 6138 (26.5) 4327 (31.3) 1811 (19.4) <0.001
  45-64 12,314 (58.8) 5921 (57.8) 6393 (59.8) 13,530 (58.4) 7875 (56.9) 5655 (60.5)
  65+ 3085 (14.7) 1187 (11.6) 1898 (17.8) 3514 (15.2) 1633 (11.8) 1881 (20.1)
Race
  White 15,169 (72.5) 6636 (64.8) 8533 (79.8) <0.001 16,644 (71.8) 9027 (65.3) 7617 (81.5) <0.001
  Black 4921 (23.5) 3168 (30.9) 1753 (16.4) 5623 (24.3) 4230 (30.6) 1393 (14.9)
  Other 482 (2.3) 238 (2.3) 244 (2.3) 547 (2.4) 315 (2.3) 232 (2.5)
  Unknown 359 (1.7) 201 (2.0) 158 (1.5) 368 (1.6) 263 (1.9) 105 (1.1)
Hispanic 1179 (5.6) 571 (5.6) 608 (5.7) NS 1299 (5.6) 782 (5.7) 517 (5.5) NS
Substance abuse 12,284 (58.7) 6984 (68.2) 5300 (49.6) <0.001 14,078 (60.7) 9542 (69.0) 4536 (48.5) <0.001
PTSD 6967 (33.3) 3129 (30.6) 3838 (35.9) <0.001 7457 (32.2) 3978 (28.8) 3479 (37.2) <0.001
Personality disorder 2813 (13.4) 1482 (14.5) 1331 (12.5) <0.001 3114 (13.4) 1946 (14.1) 1168 (12.5) <0.001
Other anxiety disorder 4431 (21.2) 1830 (17.9) 2601 (24.3) <0.001 4771 (20.6) 2445 (17.7) 2326 (24.9) <0.001
Open in a new tab
*

all values presented as N (%) indicate frequencies and percents of the study sample.

NS = non-significant

The mean antidepressant MPR among patients with depression in the three month period following psychiatric inpatient discharge was 0.79 (s.d.=0.37, median=0.82, range=0.01-2.75). Almost half (49%) of these patients had MPRs <0.8 during this period, indicating less than ideal adherence, and 27% of patients had MPRs <0.5 during this period. The mean MPR in the six month period following psychiatric inpatient discharge was 0.66 (s.d.=0.40, median=0.66, range=0.01-4.77); 60% of patients had MPRs <0.8, indicating poor adherence over a six-month period, and 41% of patients had MPRs <0.5 during the same period.

Patient demographic and clinical predictors (expressed as odds ratios with 95% confidence intervals) of poor adherence (MPR < 0.8) in the three and six months post-discharge are presented in Table 2. In bivariate analyses, patients with poor adherence were significantly more likely to have substance use disorders and personality disorders, whereas patients with high levels of adherence were more likely to have PTSD and an additional anxiety disorder (p<0.01 for all comparisons).

Table 2.

Predictors of antidepressant adherence post-discharge among patients with three and six month MPRs

3 month predictors of poor adherence (MPR < 0.80) 6 month predictors of poor adherence (MPR < 0.80)
OR unadjusted 95% CI OR adjusted 95% CI OR unadjusted 95% CI OR adjusted 95% CI
Male (reference = female) 1.24 (1.10, 1.40)* 1.31 (1.15, 1.48)* 1.13 (1.01, 1.27)* 1.27 (1.12, 1.43)*
Age (reference = 18-44)
  45-64 0.71 (0.66, 0.76)* 0.78 (0.73, 0.83)* 0.58 (0.55, 0.62)* 0.65 (0.61, 0.70)*
  65+ 0.48 (0.44, 0.52)* 0.70 (0.63, 0.77)* 0.36 (0.33, 0.40)* 0.54 (0.49, 0.59)*
Race (reference = White)
  Black 2.32 (2.17, 2.48)* 2.02 (1.88, 2.16)* 2.56 (2.39, 2.74)* 2.18 (2.03, 2.34)*
  Other 1.25 (1.05, 1.50)* 1.23 (1.02, 1.48)* 1.15 (0.96, 1.36) 1.12 (0.93, 1.33)
  Unknown 1.64 (1.33, 2.02)* 1.45 (1.17, 1.80)* 2.11 (1.68, 2.66)* 1.83 (1.45, 2.31)*
Hispanic 0.98 (0.87, 1.10) 1.14 (1.01, 1.28)* 1.02 (0.91, 1.15) 1.22 (1.08, 1.37)*
Substance abuse 2.18 (2.06, 2.31)* 1.86 (1.75, 1.97)* 2.36 (2.23, 2.49)* 1.94 (1.83, 2.05)*
PTSD 0.79 (0.74, 0.83)* 0.81 (0.76, 0.87)* 0.68 (0.64, 0.72)* 0.70 (0.66, 0.75)*
Personality disorder 1.19 (1.10, 1.29)* 1.13 (1.04, 1.23)* 1.15 (1.06, 1.24)* 1.04 (0.96, 1.13)
Other anxiety disorder 0.68 (0.63, 0.72)* 0.76 (0.71, 0.81)* 0.65 (0.61, 0.69)* 0.74 (0.69, 0.79)*
Open in a new tab
*

indicates significance at the p<0.05 level

After controlling for demographic and clinical characteristics, male gender, younger age, non-white and unknown race, substance abuse, and personality disorder were all significantly associated with poor adherence at three months, whereas PTSD and other anxiety disorders were significantly associated with good adherence. These findings were replicated for adherence at six months except that having a personality disorder was no longer significantly associated with adherence. Given our large sample size, we specifically note characteristics most strongly associated with adherence (e.g. have odds ratios <0.8 or >1.3 which may be less likely to be false positive identifications of predictive factors), which include age, black or unknown race, substance abuse, PTSD, and other anxiety disorders.

Discussion

This study provides new information on rates of antidepressant adherence from a national sample of depressed patients recently discharged from a psychiatric hospitalization. Although the mean MPR was 0.79 at three months, almost half of the patient population had MPRs <0.8 indicating problematic adherence. The mean MPR at six months was only 0.66 and 60% of patients had MPRs <0.8 over a six month period.

There have been few prior studies that have examined antidepressant adherence after psychiatric hospitalization, even though this is a time of particular vulnerability for patients. Our findings indicate that interventions to address adherence to antidepressant medications may be an important area in which care can be improved for these severely ill patients during the high risk period following discharge.

In line with models of adherence behaviors that emphasize the importance of patient perceptions of illness severity on medication taking behaviors, antidepressant adherence among higher acuity patients after hospitalization appears to be somewhat higher than less acute patients treated in outpatient settings.(Aikens, Nease, Nan, Klinkman, & Schwenk, 2005; Demyttenaere et al., 2008; Horne & Weinman, 1999) Studies examining adherence in outpatient settings have reported adherence rates between 37% and 73% over six months, with several studies indicating outpatient antidepressant adherence as less than 50% during this period.(Akincigil et al., 2007; Bambauer et al., 2006; Bambauer et al., 2007; Burra et al., 2007; Cantrell et al., 2006; Demyttenaere, Van Ganse, Gregoire, Gaens, & Mesters, 1998; Keene, Eaddy, Nelson, & Sarnes, 2005; Maidment et al., 2002; White, Vanderplas, Ory, Dezii, & Chang, 2003)

Higher rates of adherence immediately following hospitalization are congruent with conceptual models adherence behaviors, such as Leventhal's self-regulatory model (SRM)(Brown et al., 2005; Leventhal, Diefenbach, & Leventhal, 1992) or Becker and Maiman's health belief model (HBM).(Adams & Scott, 2000; Becker & Maiman, 1975) Both of these models indicate that patients’ beliefs may influence adherence, such as their perceptions about an illness’ causes, consequences and controllability (SRM) or the benefits and barriers associated with adherence as well as the likelihood of relapse or perceived illness severity (HBM). However, even though providers may be encouraged that recently discharged patients have somewhat higher levels of adherence with antidepressant treatment, they must still stay vigilant regarding poor adherence even in these high acuity patients.

More research is needed to determine the reasons that so many patients have relatively low rates of adherence after hospitalization, even though they are presumably in greater need of treatment. Potentially, patients with depression who have been hospitalized may have more difficulty organizing their daily schedules in a manner that facilitates adherence, and they may have less energy and motivation to continue with medications. These patients may also be more resistant to antidepressant treatment and be less adherent as a result. Additional targeted assistance with adherence may be needed post-discharge, including more vigorous educational efforts, closer clinical monitoring, and potentially the use of adherence aids such as specialized packaging or other tailored reminders.

An interesting finding from this study is the relationship between adherence and psychiatric comorbidity. In this study, depressed patients who had a psychiatric hospitalization had a substantial degree of psychiatric comorbidity. However, while we hypothesized that psychiatric comorbidity would be associated with poorer adherence, we found that some psychiatric comorbidities were associated with poorer adherence (e.g., substance abuse), while others were associated with better adherence (e.g., PTSD and other anxiety disorders). The existing literature is rather limited and mixed with respect to the relationship between depression, psychiatric comorbidity, and antidepressant adherence.

We note that antidepressants are now frequently used and are even the preferred treatment for anxiety disorders in addition to their indication for depression,(Beck et al., 2005; Devane, Chiao, Franklin, & Kruep, 2005) Prior research indicates that there are similar rates of antidepressant adherence among patients with either depression or anxiety.(Sheehan et al., 2008) While having an anxiety disorder and/or PTSD in addition to depression can cause greater impairment than depression alone,(Mittal, Fortney, Pyne, Edlund, & Wetherell, 2006) our findings are consistent with several studies that found depression comorbid with anxiety to be associated with greater adherence than in depression alone.(Busch et al., 2004; Sheehan et al., 2008; Stein, Cantrell, Sokol, Eaddy, & Shah, 2006) However, at least one study reported decreased adherence and increased dropout from treatment among patients with comorbid depression and anxiety,(Lenze, 2003) and another study indicated that reported anxiety is a common reason for antidepressant discontinuation.(Goethe et al., 2007) It is unknown what the specific mechanism is that contributes to increased adherence to antidepressants among depressed patients with comorbid anxiety; however, prior research suggests that patients with comorbid anxiety may have more severe symptoms and a poorer outcome than patients with depression alone, requiring more aggressive treatment.(Ballenger, 2000; Stein et al., 2006) In our study population, we have also found higher rates of suicide among depressed patients with comorbid anxiety disorders.(Pfeiffer, Ganoczy, Ilgen, Zivin, & Valenstein, 2009)

More research is needed to determine whether differences in efficacy, underlying illness, or patient population might result in differences in adherence among depressed patients with comorbid anxiety. Such research could include seeking to identify different attitudes and motivation for treatment among these patients, differential diagnosis approaches to identifying depression with and without comorbid anxiety, and differential patterns of adherence to antidepressants among patients with anxiety disorders.

Other psychiatric disorders such as substance use and personality disorders appear to be associated with decreased antidepressant adherence. This finding is easier to understand and explain, given that substance use or long standing maladaptive patterns may impair patients’ ability and willingness to adhere to prescribed medication regimens. Consistent with our findings, prior research has demonstrated that depression and comorbid alcohol or substance use is associated with decreased antidepressant adherence following new antidepressant starts.(Akincigil et al., 2007; Busch et al., 2004) Patients with comorbid depression and substance use may also be more likely to have treatment-resistant depression, which involves more antidepressant switches.(Crown et al., 2002) There is less published information on depression and personality disorders; however, personality disorder has been shown to be associated with lower adherence to antidepressants(Sirey et al., 2001) and increased risk of suicide when associated with depression.(Hansen, Wang, Stage, & Kragh-Sorensen, 2003) Our study found only a modest relationship between comorbid personality disorder and antidepressant adherence.

While this study provides new information on post discharge antidepressant adherence, there are some important limitations of note. MPRs, like many adherence measures, are an imperfect measure of adherence,(Valenstein et al., 2006) although, they yield similar results as compared to other adherence measures.(Cantrell et al., 2006) MPRs are not accurate for patients with less than 90 days of outpatient follow-up. MPRs also do not provide information on medication ingestion and it is possible that patients may repeatedly refill medications but fail to take them regularly. MPRs may also provide inaccurate information about adherence of patients who fill medications outside the VA health system.(Valenstein et al., 2006) However, for patients using mental health services, rates of cross-system use outside the VA are low.(Desai, Rosenheck, & Rothbard, 2001; Desai & Rosenheck, 2002; McCarthy, Zivin, Austin, Kales, & Valenstein, 2008) We note that we did not examine whether patients were taking antidepressants prior to hospitalization and among those patients who were, whether they were more or less adherent to their medications prior to hospitalization. We chose instead to focus on an understudied high-risk period post hospitalization, as there has been substantial literature focused on antidepressant adherence in the absence of hospitalization. We might expect that hospitalization could increase adherence initially upon discharge compared to prior adherence, but this hypothesis should be empirically tested.

We also required patients to have at least one outpatient visit during the three and six month follow-up periods, as a conservative approach to ensure that patients were in outpatient VA settings prior to discharge. In sensitivity analyses (data not shown) we removed this restriction and found slightly lower rates of adherence. Clinical and demographic correlates of adherence did not change.

Finally, we did not account for patients taking other medications, either for psychiatric disorders or medical conditions. While we did not examine patients taking more than one type of antidepressant during the study period, in sensitivity analyses, we found that the results were the similar (e.g., the same predictors were significant in the same direction) for patients taking only one or more than one antidepressant during the study period, and the large majority of patients took only one antidepressant during the study follow up periods. Furthermore, while patients had been hospitalized, we don't know their level of depression severity, or their history of antidepressant use, psychotherapy, or psychiatric hospitalization, or whether they had any caregivers or social supports that might have influenced antidepressant adherence. These factors may also play a role in antidepressant adherence, as well as other factors discussed earlier, such as side effects, attitudes, and education about adherence, which were not measured in this study.

Conclusions

Our data indicate that a substantial proportion (49-60%) of recently hospitalized depressed patients, who are at high risk for adverse outcomes including suicide, is poorly adherent to antidepressant medications. Although most prior literature and adherence interventions have addressed poor adherence among less severely ill outpatients, our findings emphasize the potential importance of adherence enhancing interventions for patients in the periods immediately following hospital discharge. We note that more frequent clinical visits, adherence aids, or strategies that have been adopted to improve depression care among newly diagnosed patients in outpatient settings, such as depression care management, may also improve adherence among these high-risk patients. Depression care managers could address patient side effects, treatment needs, health beliefs, and address questions between physician visits in a timely manner, and potentially decrease early antidepressant discontinuation. Interventions to improve adherence should also focus on particular subgroups of depressed patients, such as those with comorbid substance use disorders, who may need additional supports to increase adherence to antidepressant treatment (e.g., discussions of psychotropic medication adherence incorporated into substance abuse treatment groups). Innovative interventions to increase adherence and future research to evaluate their effectiveness must be a priority.

Acknowledgments

Funding support This study was funded in part by the Department of Veterans Affairs, Health Services Research and Development Service, IIR 04-211-1 (MV), CD2 07-206-1 (KZ), the National Institute of Mental Health, R01-MH078698-01 (MV), and by the Depression Health Services Research Evaluation and Management (DREAM) program in the Comprehensive Depression Center at the University of Michigan.

Appendix A.

Patient Depression and Other Psychiatric Disorder ICD-9 Codes and Corresponding Diagnoses

Depression ICD-9 Codes and Corresponding Diagnoses
Code Diagnosis
293.83 Organic Affective Syndrome
296.2x Major Depressive Affective Disorder Single Episode
296.3x Major Depressive Affective Disorder Recurrent Episode
296.90 Unspecified Affective Psychosis
296.99 Other Specified Affective Psychosis
298.0 Depressive Type Psychosis
300.4 Neurotic Depression
301.12 Chronic Depressive Personality Disorder
309.0 Adjustment Reaction with Brief Depressive Reaction
309.1 Adjustment Reaction with Prolonged Depressive Reaction
311. Depressive Disorder Not Elsewhere Specified
Other Psychiatric Disorder ICD-9 Codes and Corresponding Diagnoses
Disorder Code Diagnosis
Substance Use 303.0x Acute Alcoholic Intoxication in Alcoholism (Unspecified, Continuous, Episodic, and In Remission)
Disorder 303.9x Other and Unspecified Alcholic Dependence (Unspecified, Continuous, Episodic, and In Remission)
304.0x-9x Drug Dependence
Opioid Type Dependence (Unspecified, Continuous, Episodic, and In Remission)
Barbiturate and Similarly Active Sedative or Hypnotic (Unspecified, Continuous, Episodic, and In Remission)
Cocaine Dependence (Unspecified, Continuous, Episodic, and In Remission)
Canabis Dependence (Unspecified, Continuous, Episodic, and In Remission)
Amphetamine and Other Psychostimulant Dependence (Unspecified, Continuous, Episodic, and In Remission)
Hallucinogen Dependence (Unspecified, Continuous, Episodic, and In Remission)
Other Specified Drug Dependence (Unspecified, Continuous, Episodic, and In Remission)
Combinations of Opiod Type Drug with any Other Drug (Unspecified, Continuous, Episodic, and In Remission)
Combinations of Drug Dependence Excluding Opiod Type Drugs (Unspecified, Continuous, Episodic, and In Remission)
Unspecified Drug Dependence (Unspecified, Continuous, Episodic, and In Remission)
291.x Alcoholic Psychoses
Alcohol Withdrawal Delirium
Alcohol Amnestic Syndrome
Other Alcoholic Dementia
Alcohol Withdrawal Hallucinosis
Idiosyncratic Alcohol Intoxication
Alcoholic Jealousy
Other Specified Alcoholic Psychosis
Alcohol Withdrawal
Other Alcoholic Psychosis
Unspecified Alcoholic Psychosis
292.x Drug Psychoses
Drug Withdrawal Syndrome
Paranoid and/or Hallucinatory States Induced By Drugs
Drug Induced Organic Delusional Syndrome
Drug Induced Hallucinosis
Pathological Drug Intoxication
Other Specified Drug Induced Mental Disorders
Drug Induced Delirium
Drug Induced Dementia
Drug Induced Amnestic Syndrome
Drug Induced Organic Affective Syndrome
Other Specified Drug Induced Mental Disorders
Unspecified Drug Induced Mental Disorder
PTSD 309.81 Prolonged Post Traumatic Stress Disorder
Other Anxiety Disorders 300.00-300.02 Anxiety State Unspecified
Panic Disorder
Generalized Anxiety Disorder
300.09 Other Anxiety States
300.10 Hysteria
300.20-300.23 Phobia Unspecified
Agoraphobia with Panic Attacks
Agoraphobia without Panic Attacks
Social Phobia
300.29 Other Isolated or Simple Phobias
Personality Disorders 301.0 Paranoid Personality Disorder
301.20 Schizoid Personality Disorder Unspecified
301.22 Schizotypal Personality Disorder
301.7 Antisocial Personality Disorder
301.83 Borderline Personality
301.50 Histrionic Personality Disorder Unspecified
301.81 Narcissistic Personality
301.82 Avoidant Personality
301.6 Dependent Personality Disorder
301.4 Compulsive Personality Disorder
301.9 Unspecified Personality Disorder
Bipolar Disorder II 296.8x Manic-Depressive Psychosis, Other and Unspecified
Manic-Depressive Psychosis Unspecified
Atypical Manic Disorder
Atypical Depressive Disorder
Other Manic-Depressive Psychosis
Open in a new tab

Appendix B.

Types of antidepressants included in this study

amitriptyline (high dose only)
amoxapine
atomoxetine
buproprion
citalopram
clomipramine
desipramine
doxepin
duloxetine
escitalopram
fluoxetine
fluvoxamine
imipramine
isocarboxazid
maprotiline
mirtazapine (high dose only)
nefazodone
nortriptyline (high dose only)
paroxetine
phenelzine
protriptyline
sertraline
tranylcypromine
trazodone (high dose only)
trimipramine
venlafaxine
Open in a new tab

Footnotes

Previous presentation: This paper was presented in poster form at the Annual Health Services Research and Development Meeting of the Department of Veterans Affairs, Baltimore, MD, February 2009.

References

  1. Adams J, Scott J. Predicting medication adherence in severe mental disorders. Acta Psychiatrica Scandinavica. 2000;101:119–124. doi: 10.1034/j.1600-0447.2000.90061.x. [DOI] [PubMed] [Google Scholar]
  2. Aikens JE, Nease DE, Nan DP, et al. Adherence to maintenance-phase antidepressant medication as a function of patient beliefs about medication. Annals of Family Medicine. 2005;3:23–30. doi: 10.1370/afm.238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Akincigil A, Bowblis JR, Levin C, et al. Adherence to antidepressant treatment among privately insured patients diagnosed with depression. Medical Care. 2007;45:363–369. doi: 10.1097/01.mlr.0000254574.23418.f6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Ballenger JC. Anxiety and Depression: Optimizing Treatments. Primary Care Companion to the Journal of Clinical Psychiatry. 2000;2:71–79. doi: 10.4088/pcc.v02n0301. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bambauer KZ, Adams AS, Zhang F, et al. Physician alerts to increase antidepressant adherence: fax or fiction? Archives of Internal Medicine. 2006;166:498–504. doi: 10.1001/archinte.166.5.498. [DOI] [PubMed] [Google Scholar]
  6. Bambauer KZ, Soumerai SB, Adams AS, et al. Provider and patient characteristics associated with antidepressant nonadherence: the impact of provider specialty. Journal of Clinical Psychiatry. 2007;68:867–873. doi: 10.4088/jcp.v68n0607. [DOI] [PubMed] [Google Scholar]
  7. Beck CA, Patten SB, Williams JVA, et al. Antidepressant utilization in Canada. Social Psychiatry and Psychiatric Epidemiology. 2005;40:799–807. doi: 10.1007/s00127-005-0968-0. [DOI] [PubMed] [Google Scholar]
  8. Becker MH, Maiman LA. Sociobehavioral Determinants of Compliance with Health and Medical Care Recommendations. Medical Care. 1975;13:10–24. doi: 10.1097/00005650-197501000-00002. [DOI] [PubMed] [Google Scholar]
  9. Blow FC, Owen RE, Valenstein M, et al. VA National Serious Mental Illness Treatment Research & Evaluation Center (SMITREC), VHA Health Services Research & Development; Ann Arbor, MI: 2003. Specialty Care for Veterans with Depression in the VHA 2002 National Depression Registry Report. [Google Scholar]
  10. Brown C, Battista DR, Bruehlman R, et al. Beliefs about antidepressant medications in primary care patients: relationship to self-reported adherence. Medical Care. 2005;43:1203–1207. doi: 10.1097/01.mlr.0000185733.30697.f6. [DOI] [PubMed] [Google Scholar]
  11. Bull SA, Hu XH, Hunkeler EM, et al. Discontinuation of Use and Switching of Antidepressants: Influence of Patient-Physician Communication. JAMA. 2002;288:1403–1409. doi: 10.1001/jama.288.11.1403. [DOI] [PubMed] [Google Scholar]
  12. Burra TA, Chen E, McIntyre RS, et al. Predictors of self-reported antidepressant adherence. Behavioral Medicine. 2007;32:127–134. doi: 10.3200/BMED.32.4.127-134. [DOI] [PubMed] [Google Scholar]
  13. Busch SH, Leslie D, Rosenheck R. Measuring quality of pharmacotherapy for depression in a national health care system. Medical Care. 2004;42:532–542. doi: 10.1097/01.mlr.0000128000.96869.1e. [DOI] [PubMed] [Google Scholar]
  14. Cantrell CR, Eaddy MT, Shah MB, et al. Methods for evaluating patient adherence to antidepressant therapy: a real-world comparison of adherence and economic outcomes. Medical Care. 2006;44:300–303. doi: 10.1097/01.mlr.0000204287.82701.9b. [DOI] [PubMed] [Google Scholar]
  15. Crown WH, Finkelstein S, Berndt ER, et al. The impact of treatment-resistant depression on health care utilization and costs. Journal of Clinical Psychiatry. 2002;63:963–971. doi: 10.4088/jcp.v63n1102. [DOI] [PubMed] [Google Scholar]
  16. Demyttenaere K, Van Ganse E, Gregoire J, et al. Belgian Compliance Study Group Compliance in depressed patients treated with fluoxetine or amitriptyline. International Clinical Psychopharmacology. 1998;13:11–17. doi: 10.1097/00004850-199801000-00002. [DOI] [PubMed] [Google Scholar]
  17. Demyttenaere K, Adelin A, Patrick M, et al. Six-month compliance with antidepressant medication in the treatment of major depressive disorder. International Clinical Psychopharmacology. 2008;23:36–42. doi: 10.1097/YIC.0b013e3282f1c1d8. [DOI] [PubMed] [Google Scholar]
  18. Desai RA, Rosenheck RA, Rothbard A. Cross-system service use among VA mental health patients living in Philadelphia. Administration and Policy in Mental Health. 2001;28:299–309. doi: 10.1023/a:1011137630558. [DOI] [PubMed] [Google Scholar]
  19. Desai RA, Rosenheck RA. The impact of managed care on cross-system use of mental health services by veterans in Colorado. Psychiatric Services. 2002;53:1599–1604. doi: 10.1176/appi.ps.53.12.1599. [DOI] [PubMed] [Google Scholar]
  20. Devane CL, Chiao E, Franklin M, et al. Anxiety disorders in the 21st century: status, challenges, opportunities, and comorbidity with depression. American Journal of Managed Care. 2005;11:S344–353. [PubMed] [Google Scholar]
  21. Finley PR, Rens HR, Pont JT, et al. Impact of a collaborative pharmacy practice model on the treatment of depression in primary care. American Journal of Health-System Pharmacy. 2002;59:1518–1526. doi: 10.1093/ajhp/59.16.1518. [DOI] [PubMed] [Google Scholar]
  22. Geddes JR, Carney SM, Davies C, et al. Relapse prevention with antidepressant drug treatment in depressive disorders: a systematic review. Lancet. 2003;361:653–661. doi: 10.1016/S0140-6736(03)12599-8. [DOI] [PubMed] [Google Scholar]
  23. Givens JL, Datto CJ, Ruckdeschel K, et al. Older patients’ aversion to antidepressants - A qualitative study. Journal of General Internal Medicine. 2006;21:146–151. doi: 10.1111/j.1525-1497.2005.00296.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Goethe JW, Woolley SB, Cardoni AA, et al. Selective serotonin reuptake inhibitor discontinuation - Side effects and other factors that influence medication adherence. Journal of Clinical Psychopharmacology. 2007;27:451–458. doi: 10.1097/jcp.0b013e31815152a5. [DOI] [PubMed] [Google Scholar]
  25. Hansen PE, Wang AG, Stage KB, et al. Comorbid personality disorder predicts suicide after major depression: a 10-year follow-up. Acta Psychiatrica Scandinavica. 2003;107:436–440. [PubMed] [Google Scholar]
  26. Horne R, Weinman J. Patients’ beliefs about prescribed medicines and their role in adherence to treatment in chronic physical illness. Journal of Psychosomatic Research. 1999;47:555–567. doi: 10.1016/s0022-3999(99)00057-4. [DOI] [PubMed] [Google Scholar]
  27. Jones LE, Turvey C, Carney-Doebbeling C. Inadequate follow-up care for depression and its impact on antidepressant treatment duration among veterans with and without diabetes mellitus in the Veterans Health Administration. General Hospital Psychiatry. 2006;28:465–474. doi: 10.1016/j.genhosppsych.2006.08.002. [DOI] [PubMed] [Google Scholar]
  28. Katon W, von Korff M, Lin E, et al. Adequacy and duration of antidepressant treatment in primary care. Medical Care. 1992;30:67–76. doi: 10.1097/00005650-199201000-00007. [DOI] [PubMed] [Google Scholar]
  29. Katon W, Rutter C, Ludman EJ, et al. A randomized trial of relapse prevention of depression in primary care. Archives of General Psychiatry. 2001;58:241–247. doi: 10.1001/archpsyc.58.3.241. [DOI] [PubMed] [Google Scholar]
  30. Keene MS, Eaddy MT, Nelson WW, et al. Adherence to paroxetine CR compared with paroxetine IR in a Medicare-eligible population with anxiety disorders. American Journal of Managed Care. 2005;11:S362–369. [PubMed] [Google Scholar]
  31. Keller MB, Hirschfeld RM, Demyttenaere K, et al. Optimizing outcomes in depression: focus on antidepressant compliance. International Clinical Psychopharmacology. 2002;17:265–271. doi: 10.1097/00004850-200211000-00001. [DOI] [PubMed] [Google Scholar]
  32. Kerr EA, McGlynn EA, Van Vorst KA, et al. Measuring antidepressant prescribing practice in a health care system using administrative data: implications for quality measurement and improvement. Joint Commission Journal on Quality Improvement. 2000;26:203–216. doi: 10.1016/s1070-3241(00)26015-x. [DOI] [PubMed] [Google Scholar]
  33. Lenze EJ. Comorbidity of depression and anxiety in the elderly. Current Psychiatry Reports. 2003;5:62–67. doi: 10.1007/s11920-003-0011-7. [DOI] [PubMed] [Google Scholar]
  34. Leventhal H, Diefenbach M, Leventhal EA. Illness Cognition - Using Common-Sense to Understand Treatment Adherence and Affect Cognition Interactions. Cognitive Therapy and Research. 1992;16:143–163. [Google Scholar]
  35. Maidment R, Livingston G, Katona C. Just keep taking the tablets: adherence to antidepressant treatment in older people in primary care. International Journal of Geriatric Psychiatry. 2002;17:752–757. doi: 10.1002/gps.688. [DOI] [PubMed] [Google Scholar]
  36. McCarthy J, Zivin K, Austin K, et al. Does Consideration of Medicare Use Affect VA Evaluations of Treatment for New Episodes of Depression? Administration and Policy in Mental Health. 2008;35:468–476. doi: 10.1007/s10488-008-0190-y. [DOI] [PubMed] [Google Scholar]
  37. Melartin TK, Rytsala HJ, Leskela US, et al. Continuity is the main challenge in treating major depressive disorder in psychiatric care. Journal of Clinical Psychiatry. 2005;66:220–227. doi: 10.4088/jcp.v66n0210. [DOI] [PubMed] [Google Scholar]
  38. Melfi CA, Chawla AJ, Croghan TW, et al. The effects of adherence to antidepressant treatment guidelines on relapse and recurrence of depression. Archives of General Psychiatry. 1998;55:1128–1132. doi: 10.1001/archpsyc.55.12.1128. [DOI] [PubMed] [Google Scholar]
  39. Mittal D, Fortney JC, Pyne JM, et al. Impact of comorbid anxiety disorders on health-related quality of life among patients with major depressive disorder. Psychiatric Services. 2006;57:1731–1737. doi: 10.1176/ps.2006.57.12.1731. [DOI] [PubMed] [Google Scholar]
  40. Montgomery SA. Guidelines in major depressive disorder, and their limitations. International Journal of Psychiatry in Clinical Practice. 2006;10:3–9. doi: 10.1080/13651500600940492. [DOI] [PubMed] [Google Scholar]
  41. National Committee for Quality Assurance . Antidepressant medication management (effective continuation phase treatment) National Commitee for Quality Assurance (NCQA); Washington, DC: 2003. [Google Scholar]
  42. National Committee for Quality Assurance (NCQA) Antidepressant medication management (effective acute treatment phase) National Committee for Quality Assurance (NCQA); Washington, DC: 2003. [Google Scholar]
  43. Olfson M, Marcus SC, Tedeschi M, et al. Continuity of antidepressant treatment for adults with depression in the United States. American Journal of Psychiatry. 2006;163:101–108. doi: 10.1176/appi.ajp.163.1.101. [DOI] [PubMed] [Google Scholar]
  44. Ozmen E, Ogel K, Aker T, et al. Public opinions and beliefs about the treatment of depression in urban Turkey. Social Psychiatry and Psychiatric Epidemiology. 2005;40:869–876. doi: 10.1007/s00127-005-0985-x. [DOI] [PubMed] [Google Scholar]
  45. Pfeiffer PN, Ganoczy D, Ilgen M, et al. Depression and Anxiety. 2009. Comorbid anxiety as a suicide risk factor among depressed veterans. in press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Richeimer SH, Bajwa ZH, Kahraman SS, et al. Utilization patterns of tricyclic antidepressants in a multidisciplinary pain clinic: A survey. Clinical Journal of Pain. 1997;13:324–329. doi: 10.1097/00002508-199712000-00010. [DOI] [PubMed] [Google Scholar]
  47. Robinson RL, Long SR, Chang S, et al. Higher Costs and Therapeutic Factors Associated With Adherence to NCQA HEDIS Antidepressant Medication Management Measures: Analysis of Administrative Claims. Journal of Managed Care Pharmacy. 2006;12:43–54. doi: 10.18553/jmcp.2006.12.1.43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Sewitch MJ, Blais R, Rahme E, et al. Receiving guideline-concordant pharmacotherapy for major depression: Impact on ambulatory and inpatient health service use. Canadian Journal of Psychiatry-Revue Canadienne De Psychiatrie. 2007;52:191–200. doi: 10.1177/070674370705200311. [DOI] [PubMed] [Google Scholar]
  49. Sheehan DV, Keene MS, Eaddy M, et al. Differences in medication adherence and healthcare resource utilization patterns: older versus newer antidepressant agents in patients with depression and/or anxiety disorders. CNS Drugs. 2008;22:963–973. doi: 10.2165/00023210-200822110-00005. [DOI] [PubMed] [Google Scholar]
  50. Sikka R, Xia F, Aubert RE. Estimating medication persistency using administrative claims data. American Journal of Managed Care. 2005;11:449–457. [PubMed] [Google Scholar]
  51. Sirey JA, Bruce ML, Alexopoulos GS, et al. Stigma as a barrier to recovery: Perceived stigma and patient-rated severity of illness as predictors of antidepressant drug adherence. Psychiatric Services. 2001;52:1615–1620. doi: 10.1176/appi.ps.52.12.1615. [DOI] [PubMed] [Google Scholar]
  52. Smith MW, Joseph GJ. Pharmacy data in the VA health care system. Medical Care Research and Review. 2003;60:92S–123S. doi: 10.1177/1077558703256726. [DOI] [PubMed] [Google Scholar]
  53. Spettell CM, Wall TC, Allison J, et al. Identifying physician-recognized depression from administrative data: consequences for quality measurement. Health Services Research. 2003;38:1081–1102. doi: 10.1111/1475-6773.00164. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Stein MB, Cantrell CR, Sokol MC, et al. Antidepressant adherence and medical resource use among managed care patients with anxiety disorders. Psychiatric Services. 2006;57:673–680. doi: 10.1176/ps.2006.57.5.673. [DOI] [PubMed] [Google Scholar]
  55. Valenstein M, Copeland LA, Blow FC, et al. Pharmacy data identify poorly adherent patients with schizophrenia at increased risk for admission. Medical Care. 2002;40:630–639. doi: 10.1097/00005650-200208000-00002. [DOI] [PubMed] [Google Scholar]
  56. Valenstein M, Ganoczy D, McCarthy JF, et al. Antipsychotic Adherence Over Time Among Patients Receiving Treatment for Schizophrenia: A Retrospective Review. Journal of Clinical Psychiatry. 2006;67:1542–1550. doi: 10.4088/jcp.v67n1008. [DOI] [PubMed] [Google Scholar]
  57. Valenstein M, Kim HM, Ganoczy D, et al. Higher-risk periods for suicide among VA patients receiving depression treatment: Prioritizing suicide prevention efforts. Journal of Affective Disorders. 2009;112:50–58. doi: 10.1016/j.jad.2008.08.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Vermeire E, Hearnshaw H, Van Royen P, et al. Patient adherence to treatment: three decades of research. A comprehensive review. Journal of Clinical Pharmacy and Therapeutics. 2001;26:331–342. doi: 10.1046/j.1365-2710.2001.00363.x. [DOI] [PubMed] [Google Scholar]
  59. White TJ, Vanderplas A, Ory C, et al. Economic impact of patient adherence with antidepressant therapy within a managed care organization. Disease Management & Health Outcomes. 2003;11:817–822. [Google Scholar]
  60. Wiegand MH. Antidepressants for the Treatment of Insomnia A Suitable Approach? Drugs. 2008;68:2411–2417. doi: 10.2165/0003495-200868170-00001. [DOI] [PubMed] [Google Scholar]

RESOURCES