- Email: [email protected]
Differences in prescribing patterns for anxiety and depression between General Internal Medicine and Family Medicine
Journal of Affective Disorders 172 (2015) 153–158
Contents lists available at ScienceDirect
Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad
Research report
Differences in prescribing patterns for anxiety and depression between General Internal Medicine and Family Medicine Jay A. Brieler n, Jeffrey F. Scherrer, Joanne Salas Department of Family and Community Medicine, Saint Louis University School of Medicine, St. Louis, MO 63104, United States
art ic l e i nf o
a b s t r a c t
Article history: Received 29 September 2014 Accepted 30 September 2014 Available online 13 October 2014
Introduction: Depression and anxiety are routinely managed by physicians in Family Medicine (FM) or General Internal Medicine (GIM). Because FM requires more behavioral health training than GIM, we sought to determine if prescribing patterns for patients with anxiety, depression, or both differed between FM vs. GIM providers. Methods: In a cross-sectional design, patient data and provider type were obtained from 2008 to 2013 electronic medical record patient data registry (n ¼27,225 (FM¼ 10,994, GIM¼ 16,231)) Prescription orders were modeled for specific benzodiazepines and antidepressants and by drug class. Covariates included gender, age, race, marital status and comorbidity index. Separate logistic regression models were computed, before and after adjusting for covariates, to estimate the odds of FM vs. GIM providers prescribing benzodiazepine or antidepressant medication to patients with anxiety, depression, and both disorders. Results: After adjusting for covariates, patients with anxiety alone, depression alone, and both had significantly greater odds of receiving an antidepressant (OR ¼2.08;95%CI:1.46–2.96, OR ¼2.13;95% CI:1.48–3.06, and OR ¼2.26;95%CI:1.09–4.66, respectively) if treated by FM vs. GIM. Benzodiazepine prescription did not differ by physician type. Limitations: It is not known if results will generalize to other regions of the United States. Conclusions: Patients with anxiety, depression, and both seen by FM providers, as compared to GIM providers, are more likely to receive antidepressant medications. Further investigation into the determinants of these differences is warranted. Under-treatment in GIM may result in less advantageous outcomes. & 2014 Elsevier B.V. All rights reserved.
Keywords: Depression Anxiety Antidepressants Psychopharmacology Primary care
1. Background Depression and anxiety disorders are very common and carry a significant personal and societal burden (Riolo et al., 2005; Lepine 2002). The majority of patients with anxiety and depression are treated by their primary care provider (PCP) rather than mental health professionals (Riolo et al., 2005; Harman et al., 2006). Numerous studies have identified gaps in the psychiatric care provided by PCPs (Hirschfeld et al., 1997; Bet et al., 2013; Stein et al., 2004; Price et al., 2000). Results from one cross-sectional study indicated that 70% of patients with moderate to severe depression were inadequately treated in the primary care setting compared to 29% of those seen in a specialized mental health care setting (Bet et al., 2013). Another investigation found that only 40% of patients diagnosed with an anxiety disorder and treated by their PCP had received adequate
n
Corresponding author. Tel.: þ 1 314 977 8480; fax: þ 1 314 977 5268. E-mail address: [email protected] (J.A. Brieler).
http://dx.doi.org/10.1016/j.jad.2014.09.056 0165-0327/& 2014 Elsevier B.V. All rights reserved.
medication, and only 25% of those were at a minimally adequate dose (Stein et al., 2004). As PCPs continue to provide a large proportion of the care for patients with anxiety and depression, efforts are warranted to improve the quality of mental health care delivered in primary care settings (Price et al., 2000). Differences in training may explain gaps in care. Psychosocial training during residency differs significantly between GIM and FM, with the requirements of the Accreditation Council for Graduate Medical Education (ACGME) for FM including both a greater quantity and breadth of experience (Accreditation Council for Graduate Medical Education 2014, 2013). FM residents selfreport greater preparedness to diagnose and treat depression in comparison to GIM residents (Wiest et al., 2002). A survey of program directors found that GIM programs require an average of 118 h of psychosocial training compared to 352 h for FM (Gaufberg et al., 2001). Limited evidence suggests differences in specialty are associated with differences in provider behavior. FM physicians are 65% more likely to diagnose depression than GIM physicians (Harman et al., 2001). FM physicians are more likely to ask their
154
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
patients about depression at a rate of 34% vs. 27.3% for GIM (Nichols and Brown, 2000), and FM physicians tend to engage in more psychosocial discussion or counseling (Harman et al., 2006; Paasche-Orlow and Roter, 2003) as compared to GIM physicians. Treatment differences may also exist. Analysis of the National Ambulatory Medical Care Survey (NAMCS) showed no difference between FM and GIM use of antidepressants for elderly patients with depression (Harman et al., 2006). However, this study focused on a specific age group. Results of surveys show that FM physicians self-report being more likely to prescribe selective serotonin reuptake inhibitors than GIM-trained doctors (Gallo et al., 2002; Williams et al., 1999). At this time we are unaware of existing reports comparing GIM physicians and FM physicians' actual prescribing patterns for patients with anxiety, depression or both using data from large medical record cohorts. The purpose of this study was to compare the prescribing patterns of GIM and FM physicians for adult patients with diagnosis of anxiety alone, depression alone and co-occurring anxiety and depression. We hypothesized that patients seen by FM physicians would be more likely to receive antidepressants and less likely to receive benzodiazepines for both anxiety and depression. Second, we hypothesized these differences would remain after controlling for patient demographics and comorbidities. Finally, in post-hoc analyses we investigated whether patients of FM physicians as compared to GIM physicians differentially are prescribed specific agents in both drug classes.
2. Methods 2.1. Subjects Clinical data were obtained from the Department of Family and Community Medicine's Primary Care Patient Data Registry (PCPD). The PCPD Registry was developed by extracting electronic medical record data from clinics staffed by FM and GIM providers at a large academic medical health system located in the St. Louis, Missouri, metropolitan area. The Registry contains ICD-9-CM codes, prescription orders, CPT codes, social history, family history, demographics, laboratory orders, referrals and vital signs. The Registry consists of 27,225 patients (FM¼ 10,994 patients, GIM¼16,231 patients) who had at least one encounter (e.g. office visit, procedure visit, or clinical support) between July 1, 2008 and July 31, 2013. Encounters occurred in any of the three ambulatory care clinics staffed by FM (n¼approximately 11 attending physiciansþ4 mid-levels) and in the case of GIM staffed by faculty, residents, and small number (o5) of mid-level providers (n¼ approximately 100 total). FM residents at this university are trained at a community site with a different electronic record, and were not able to be included in this analysis. Clinics are geographically dispersed throughout the St. Louis metropolitan area. For the present study, children (n¼1847), those with missing race (n¼485), and those with missing gender (n¼1) were excluded resulting in 24,892 patients age 18 90 available for analysis. The study procedures were reviewed and approved by the university IRB.
3. Measures 3.1. Type of primary care The probability of receiving prescriptions was compared between patients who visited FM providers vs. GIM providers.
3.1.1. Depression and anxiety disorder-unspecified Diagnoses were determined by the presence of ICD-9-CM codes at any time during the observation period. To be considered a case, the patient must have had at least two diagnoses for the same condition within a 12 month period. Defining depression by this method has excellent agreement with patient reported depression and written medical record abstraction with a 99% positive predictive value when compared to chart review (Frayne et al., 2010; Solberg et al., 2006). Depression ICD-9 codes included 296.2, 296.3 and 311. Anxiety disorder unspecified was defined by ICD-9 code 300.00. Three categories of depression and anxiety were defined: anxiety disorder unspecified without depression, depression without anxiety disorder unspecified, and both anxiety and depression defined if a patient ever had both diagnoses during the observation period. We did not include ICD codes for other anxiety disorders, including panic and generalized anxiety disorder, as those codes were very infrequently used in primary care.
3.1.2. Benzodiazepines and antidepressants Prescription orders were used to identify the prevalence of specific benzodiazepine and antidepressant use. Dose and duration were not considered in this report. Benzodiazepines included alprazolam, chlordiazepoxide, clonazepam, lorazepam, diazepam, and clorazepate. Antidepressants included the tricyclic antidepressants (TCAs): clomipramine, amitriptyline, desipramine, nortriptyline, doxepin, and imipramine. Selective serotonin re-uptake inhibitors (SSRIs) included citalopram, escitalopram, fluvoxamine, fluoxetine, paroxetine, and sertraline. Serotonin and norepinephrine reuptake inhibitors (SNRIs) included venlafaxine, duloxetine, and desvenlafaxine. Antidepressants not classified were considered as an ‘other’ category and included bupropion, nefazodone, trazodone, and mirtazapine.
3.2. Covariates Covariates were selected because they were associated with depression and anxiety and distributed differently in FM vs. GIM clinics. Covariates included gender, age category (18–40 years of age, 41–60 and 460), race (non-white vs. white), marital status (married, not married and unknown), and the Romano adapted Charlson Comorbidity Index which is a score derived from the presence of 17 health conditions associated with morbidity and mortality (Romano et al., 1993). Higher index scores indicate worse health and would likely be associated with more clinic visits, increased probability of detection and use of medication.
3.3. Analytic approach The entire observation period was treated as a cross-sectional study. Patient characteristics were compared between FM and GIM. The prevalence of drug class and individual medications was computed for FM and GIM within each anxiety and depression diagnostic group (i.e. anxiety alone, depression alone and comorbid anxiety and depression). Separate multivariate logistic regression models were computed to estimate the odds of receiving any benzodiazepine and any antidepressant in patients who received care by FM vs. GIM for each anxiety and depression diagnostic group. Full models simultaneously adjusted for all covariates. Measures of statistical significance were expressed by Chi-square p-Values for cross-tabulations and by 95% confidence intervals for odds ratios.
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
155
Table 1 Patient characteristics by FM and GIMa among patients 18 years or older (N ¼24,892). Variable, n (%)
Total (N¼ 24,892)
FM (n¼ 9898)
GIM (n¼ 14,994)
Male Age 18–40 41–60 4 60 Non-white race Marital status Married Other Unknown Mean Comorbidity Index (sd) Anxiety only Depression only Comorbid anxiety and depression
9649 (38.8)
3246 (32.8)
6403 (42.7)
10,502 (42.2) 8773 (35.2) 5617 (22.6) 9600 (38.6)
5099 (51.5) 3434 (34.7) 1365 (13.8) 2906 (29.4)
5403 5339 4252 6694
10,084 (40.5) 134,842 (54.2) 1326 (5.3) 0.72 (1.5) 760 (3.1) 1484 (6.0) 546 (2.2)
4861 (49.1) 4902 (49.5) 135 (1.4) 0.44 (1.1) 424 (4.3) 455 (4.6) 365 (3.7)
5223 (34.8) 8580 (57.2) 1191 (7.9) 0.90 (1.7) 336 (2.2) 1029 (6.9) 181 (1.2)
a
(36.0) (35.6) (28.4) (44.6)
p-Value o 0.0001 o 0.0001
o 0.0001 o 0.0001
o 0.0001 o 0.0001 o 0.0001 o 0.0001
GIM ¼ General Internal Medicine; FM¼ Family Medicine.
4. Results 4.1. Patient characteristics As shown in Table 1, patients were predominately female (61.2%), under 60 years of age (77.4%), and white (61.4%). Approximately 40.5% were married. The average comorbidity index was 0.72 (SD 7 1.5). 3.1% were diagnosed with anxiety disorderunspecified only, 6% with depression only and 2.2% had both diagnoses during the observation period. Compared to FM patients, GIM patients were significantly (p o0.0001) more likely to be older, of non-white race, male, unmarried, and have more medical co-morbidities. GIM patients were more likely to be diagnosed with depression alone, while FM patients were more likely to be diagnosed with anxiety alone or both conditions. 4.2. Medication choice The percent of patients receiving prescriptions by drug class and specific medication are shown in Table 2. Patients with anxiety alone were significantly (p o0.05) less likely to receive benzodiazepines from a FM provider compared to GIM. For this patient group, alprazolam and clonazepam were the most frequently used benzodiazepines by FM. Compared to patients of GIM physicians, those being treated by FM physicians were significantly (p o0.01) more likely to receive clonazepam (11.3% vs. 6.3%) and less likely to receive alprazolam (30.0% FM vs. 39.0% GIM). For patients with depression alone, benzodiazepine prescription did not differ between FM and GIM physicians. Patients with both anxiety and depression were significantly (p o0.01) less likely to receive alprazolam (18.1% vs. 34.3%) and significantly (p o0.01) more likely to receive clonazepam (23.6% vs. 7.8%) if treated by FM compared to GIM. Across diagnostic groups, patients treated by FM providers were more likely to receive anti-depressants as a class than patients treated by GIM providers. Across diagnostic groups, TCA prescriptions did not significantly differ between FM and GIM. Among patients with anxiety alone and depression alone, those treated by FM were significantly (p o0.01) more often prescribed an SSRI compared to those treated by GIM physicians. Patients of FM physicians with anxiety alone were more likely to receive escitalopram and fluoxetine. Patients diagnosed with depression alone were significantly more likely to be prescribed fluoxetine if treated by FM physicians and less likely to receive paroxetine as compared to patients of GIM providers. Among the ‘other’ antidepressants, patients with depression who were treated by FM physicians were significantly more often prescribed bupropion
(31.4% vs. 14.7%) compared to those treated by GIM providers. For patients with both depression and anxiety, those treated by FM, compared to patients of GIM, were more often prescribed any antidepressant, significantly less often prescribed duloxetine (4.9% vs. 9.4%, p o0.05), and significantly more often prescribed bupropion (32.6% vs. 17.1%, po 0.01). 4.3. Multivariate analysis Results of multivariate logistic regression models are shown in Tables 3–5 for patients with anxiety disorder-unspecified only (Table 3), depression alone (Table 4) and patients with both anxiety disorder – unspecified and depression (Table 5). As shown in Table 3, patients with anxiety disorder – unspecified were significantly less likely to receive a prescription for a benzodiazepine from a FM provider as compared to GIM. However, after adjusting for demographics and comorbidity, this was no longer significant. Older age (460 compared to 18–40 years of age) and higher comorbidity index were significantly associated with increased odds of receiving a benzodiazepine among patients with anxiety disorder-unspecified (OR range 1.15–2.06). In terms of antidepressants, FM patients were significantly more likely than GIM patients to receive an antidepressant before (OR¼2.58;95% CI:1.88–3.54) and after adjusting for covariates (OR¼ 2.08;95% CI:1.46–2.96). Among this patient group, older age (460 compared to 18–40 years of age) was significantly associated with lower odds of receiving an antidepressant (OR¼0.35; 95%CI: 0.22–0.55). Among patients with depression only (Table 4) there was no significant association between provider type (FM vs. GIM) and odds of receiving a benzodiazepine. However, those who were older than 60, compared to those 18–40, were significantly more likely to receive a benzodiazepine (OR¼ 1.75; 95%CI:1.10–2.80) and non-white patients were significantly less likely to receive a benzodiazepine (OR ¼0.46; 95%CI:0.31–0.66) than white patients. Higher comorbidity index was also significantly associated with increased odds of receiving a benzodiazepine (OR ¼1.09; 95% CI:1.01–1.17). Patients with depression alone were significantly more likely to receive an antidepressant if treated by FM physicians compared to GIM physicians before (OR¼2.31;95%CI:1.64–3.25) and after accounting for covariates (OR¼ 2.13,95%CI: 1.48–3.06). Among the depressed only patient group, patients who were middle age (41–60 years compared to those 18–40 years of age), had a significantly lower odds of receiving an antidepressant (OR¼ 0.66; 95%CI:0.44–0.98). Compared to married patients, those who were unmarried, divorced, separated, widowed or never married had significantly lower odds of receiving an antidepressant (OR¼0.59; 95%CI:0.43–0.82).
156
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
Table 2 Benzodiazepine and antidepressant prescribing patterns between FM and GIMa for patients with anxiety only, depression only, and comorbid depression and anxiety, aged 18 years or older. Drug (class), n (%)
Anxiety alone (n¼760) FM (n ¼424)
GIM (n ¼336) n
Depression alone (n¼ 1484)
Comorbid anxiety/depression (n ¼546)
FM (n¼ 455)
GIM (n¼ 1029)
FM (n¼365)
GIM (n¼181)
Any benzodiazepine Alprazolam Chlordiazepoxide Clonazepam Lorazepam Diazepam Clorazepate
194 (45.7) 127 (30.0) o5 (na)b 48 (11.3) 34 (8.0) 8 (1.9) o5 (na)b
183 (54.5) 131 (39.0)nn o 5 (na)b 20 (6.0)nn 36 (10.7) 15 (4.5)n o 5 (0.3)
68 (15.0) 30 (6.6) o 5 (na)b 20 (4.4) 12 (2.6) 8 (1.8) 0
136 (13.2) 73 (7.1) o 5 (na)b 30 (2.9) 30 (2.9) 17 (1.7) o 5 (0.1)
166 (45.5) 66 (18.1) 0 86 (23.6) 25 (6.9) 19 (5.2) 0
93 (51.3) 62 (34.3)nn o 5 (na)b 14 (7.8)nn 20 (11.1) 10 (5.5) 0
Any antidepressant Any TCA Clomipramine Amitriptyline Desipramine Nortriptyline Doxepin Imipramine
332 (78.3) 32 (7.6) 0 25 (5.9) o5 (na)b o5 (na)b o5 (na)b 0
196 (58.3)nn 23 (6.9) 0 15 (4.5) 0 o 5 (na)b o 5 (na)b 0
410 (90.1) 32 (7.0) 0 27 (5.9) 0 5 (1.1) o 5 (na)b 0
821 (79.8)nn 90 (8.8) 1 (0.1) 60 (5.8) o 5 (na)b 23 (2.2) o 5 (na)b 0
348 (95.3) 41 (11.2) 0 37 (10.1) 0 o 5 (na)b 0 0
156 (86.2)nn 24 (13.3) 0 16 (8.8) o 5 (na)b 7 (3.9)n o 5 (na)b 0
Any SSRI Citalopram Escitalopram Fluvoxamine Fluoxetine Paroxetine Sertraline
270 (63.7) 94 (22.2) 64 (15.1) 0 43 (10.1) 45 (10.6) 76 (17.9)
144 (42.9)nn 58 (17.3) 22 (6.6)nn 0 14 (4.2)nn 29 (8.6) 50 (14.9)
306 (67.3) 105 (23.1) 57 (12.5) o 5 (na)b 87 (19.1) 21 (4.6) 82 (18.0)
606 (58.9)nn 249 (24.2) 96 (9.3) 0 72 (7.0)nn 81 (7.9)nn 193 (18.8)
287 (78.6) 121 (33.2) 68 (18.6) 0 58 (15.9) 39 (10.7) 83 (22.7)
130 (71.8) 53 (29.3) 24 (13.3) 0 19 (10.5) 21 (11.6) 42 (23.2)
Any SNRI Venlafaxine Duloxetine Desvenlafaxine
40 (9.4) 32 (7.6) 7 (1.7) o5 (na)b
27 (8.0) 13 (3.9)n 13 (3.9) o 5 (na)b
86 (18.9) 45 (9.9) 30 (6.6) 14 (3.1)
154 (15.0) 78 (7.6) 83 (8.1) 6 (0.6)nn
69 (18.9) 44 (12.1) 18 (4.9) 9 (2.5)
31 (17.1) 15 (8.3) 17 (9.4)n o 5 (na)b
Any otherc Bupropion Nefazodone Trazodone Mirtazapine
72 (17.0) 43 (10.1) 0 31 (7.3) 8 (1.9)
55 (16.4) 27 (8.0) 0 26 (7.7) 8 (2.4)
175 (38.5) 143 (31.4) 0 41 (9.0) 13 (2.9)
293 (28.5)nn 151 (14.7)nn o 5 (na)b 123 (12.0) 61 (5.9)n
152 (41.6) 119 (32.6) 0 44 (12.1) 12 (3.3)
61 (33.7) 31 (17.1)nn o 5 (na)b 28 (15.5) 9(5.0)
n
po 0.05. p o0.01. a GIM ¼General Internal Medicine; FM¼ Family Medicine. b Cells with less than 5 patients are reported as ‘o 5’ to protect patient privacy and confidentiality. c Monoamine Oxidase Inhibitors represented o 5 total prescriptions as a class across diagnosis. nn
Table 3 Association (OR; 95% CI) between FM vs. GIM and any prescription of benzodiazepine (BDM) and antidepressant medication (ADM) for anxiety only (n¼760).
GIMa FM Male Age (years) 18–40 41–60 4 60 Race White Non-white Marital status Married Other Unknown Comorbidity index
BDM – unadjusted
BDM – adjusted
ADM –unadjusted
ADM – adjusted
1.0 0.71 (0.53–0.94) –
1.0 0.95 (0.68–1.32) 1.04 (0.75–1.43)
1.0 2.58 (1.88–3.54) –
1.0 2.08 (1.46–2.96) 1.10 (0.77–1.57)
–
1.0 1.75 (1.23–2.49) 2.06 (1.34–3.19)
–
1.0 0.79 (0.53–1.17) 0.35 (0.22–0.55)
1.0 0.77 (0.53–1.12)
–
1.0 0.90 (0.61–1.33)
1.0 1.34 (0.98–1.83) 1.80 (0.84–3.85) 1.15 (1.03–1.28)
–
1.0 1.00 (0.71–1.41) 1.43 (0.65–3.13) 1.03 (0.93–1.15)
–
–
–
–
Bold text indicates significant odds ratio, p o 0.05. a
GIM ¼General Internal Medicine; FM¼ Family Medicine.
Among patients with both anxiety and depression diagnoses (Table 5), there was no significant association between provider type (FM vs. GIM) and odds of receiving a benzodiazepine. Higher comorbidity index was significantly associated with odds of receiving a benzodiazepine (OR¼1.13; 95%CI:1.01–1.27). Patients treated
by FM had significantly greater odds of receiving an antidepressant compared to those treated by GIM both before (OR¼ 3.28; 95% CI:1.72–6.25) and after (OR¼ 2.26; 95%CI:1.09–4.66) adjusting for covariates. Compared to patients aged 18–40 years, patients 41–60 and 460 years of age had significantly lower odds of receiving an
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
157
Table 4 Association (OR; 95% CI) between FM vs. GIM and any prescription of benzodiazepine (BDM) and antidepressant medication (ADM) for depression only (n¼ 1484).
GIMa FM Male Age (years) 18–40 41–60 4 60 Race White Non-white Marital status Married Other Unknown Comorbidity index
BDM – unadjusted
BDM – adjusted
ADM –unadjusted
ADM –adjusted
1.0 1.15 (0.84–1.58) –
1.0 1.17 (0.83–1.65) 0.75 (0.53–1.06)
1.0 2.31 (1.64–3.25) –
1.0 2.13 (1.48–3.06) 0.81 (0.60–1.10)
–
1.0 1.47 (0.95–2.28) 1.75 (1.10–2.80)
–
1.0 0.66 (0.44–0.98) 0.73 (0.48–1.12)
–
1.0 0.46 (0.31–0.66)
–
1.0 1.03 (0.76–1.39)
–
1.0 0.79 (0.57–1.10) 0.86 (0.49–1.50) 1.09 (1.01–1.17)
–
1.0 0.59 (0.43–0.82) 0.68 (0.41–1.12) 1.04 (0.97–1.13)
–
–
Bold text indicates significant odds ratio, po 0.05. a
GIM ¼ General Internal Medicine; FM¼ Family Medicine.
Table 5 Association (OR; 95% CI) between FM vs. GIM and any prescription of benzodiazepine (BDM) and antidepressant medication (ADM) for comorbid anxiety/depression (n¼ 546).
GIMa FM Male Age (years) 18–40 41–60 4 60 Race White Non-white Marital status Married Other Unknown Comorbidity index
BDM – unadjusted
BDM – adjusted
ADM – unadjusted
ADM –adjusted
1.0 0.79 (0.55–1.13) –
1.0 0.87 (0.58–1.30) 0.83 (0.54–1.28)
1.0 3.28 (1.72–6.25) –
1.0 2.26 (1.09–4.66) 0.93 (0.41–2.08)
–
1.0 1.28 (0.85–1.92) 1.08 (0.65–1.82)
–
1.0 0.30 (0.12–0.78) 0.32 (0.11–0.93)
–
1.0 0.64 (0.40–1.00)
–
1.0 1.27 (0.57–2.84)
–
1.0 1.06 (0.74–1.53) 1.25 (0.55–2.84) 1.13 (1.01–1.27)
–
1.0 0.49 (0.23–1.05) 0.72 (0.18–2.92) 0.89 (0.77–1.04)
–
–
Bold text indicates significant odds ratio, po 0.05. a
GIM ¼ General Internal Medicine; FM¼ Family Medicine.
antidepressant (OR¼ 0.30; 95%CI:0.12–0.78; and OR¼ 0.32; 95% CI:0.11–0.93, respectively). Due to the differences seen in the prescribing of alprazolam and clonazepam, a post-hoc multivariate analysis was performed. After adjusting for age, sex, race, marital status, and co-morbidity, the differences in the anxiety only and depression only groups were no longer significant. In the co-morbid anxiety and depression group, FM providers were more likely to prescribe clonazepam (OR ¼ 3.27;95% CI: 1.70–6.28) and less likely to prescribe alprazolam (OR ¼0.41, 95%CI: 0.26–0.66).
5. Discussion Primary care patients diagnosed with anxiety disorder-unspecified, depression, or both conditions were more than twice as likely to be prescribed an antidepressant if treated by a FM provider compared to those treated by GIM providers. For all diagnosis groups, provider type was not significantly associated with odds of receiving a benzodiazepine. Our findings in adult patients of varying age differ from the NAMCS analysis which found no difference in the prescribing of antidepressants between GIM and FM physicians in an older population. Not only do the data in this study have enhanced
external validity due to the inclusion of a wider age range, but the preservation of effect after controlling for patient demographics and comorbidity increases the likelihood that the differences seen are, in fact, related to the specialty of the provider. Antidepressants, including SSRIs and SNRIs, are considered first-line agents for both depression and anxiety (American Psychiatric Association, 2009, 2010). The rate of antidepressant use by psychiatrists seeing patients with depression is in the range of 86–89% (Paasche-Orlow and Roter, 2003). Thus, the differential use of these medications among primary care specialties represents a difference in the adherence to standards of care, at least at the practice population level. Based on our data, no conclusion can be made on the cause of these differences. One possibility is the differential quantity of behavioral health training in FM as opposed to GIM residency programs. Differential patterns of referral to specialty mental health care and differences in length or severity of mental illness between types of practice are two other potential factors that could contribute to our results. 5.1. Limitations Several limitations must be noted in this analysis. First, our data showed significantly fewer patients diagnosed with anxiety, depression, or both in the GIM population compared to the FM
158
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
cohort. Whether this represents a detection bias or a tendency of certain patients to preferentially choose one type of provider over another is unknown. Our dataset is limited to the geographic area of the St. Louis metropolitan area. To what extent our findings can be generalized to other locations is unclear. In addition, the PCPD registry reflects care provided in an academic medicine setting. The registry data captured includes resident physicians in GIM only. A small number of physician assistants and nurse practitioners were included in the registry data in both groups. It is unclear what, if any, effect these differences would have on the results seen in our data. Many aspects of care were not examined in this study. We do not know the patients' psychiatric medication history or responses. We do not know whether medications were initiated by the primary care providers studied or simply continued based on previous psychiatric care. We did not examine the duration or dosage of treatment provided. These specific items have been identified as important aspects of care that may represent gaps in PCP management of psychiatric illness (Katon et al., 1992), and may represent areas for further study.
6. Conclusions Our data indicate that patients with anxiety and depression seen in FM as opposed to GIM practices are more likely to be prescribed antidepressant medication. This difference suggests that FM providers are in closer alignment with mental health care professionals and published guidelines. If depression is undertreated in GIM, patients are at risk of relapse and a more chronic course of disease. Further investigation is warranted to clarify the nature of these differences across setting and to more specifically explore the possible association between behavioral health training and prescribing patterns.
Role of funding source An educational Grant from the Mindlin Foundation provided partial support for Dr. Scherrer's contribution.
Conflict of interest None.
Acknowledgments None.
References Accreditation Council for Graduate Medical Education, 2014. ACGME program requirements in family medicine. 〈http://www.acgme.org/acgmeweb/Portals/ 0/PFAssets/ProgramRequirements/120_family_medicine_07012014.pdf〉. Accreditation Council for Graduate Medical Education, 2013. ACGME program requirements in internal medicine. 〈https://www.acgme.org/acgmeweb/Por tals/0/PFAssets/2013-PR-FAQ-PIF/140_internal_medicine_07012013.pdf〉. American Psychiatric Association, 2009. Practice Guideline for the Treatment of Panic Disorder, 2nd edition. American Psychiatric Association, 2010. Practice Guideline for the Treatment of Patient with Major Depressive Disorder, third edition. Bet, P., Hugtenburg, J., Penninx, B., Van Balkom, A., Nolen, W., Hoogendijk, W., 2013. Treatment inadequacy in primary and specialized care patients with depressive and/or anxiety disorders. Psychiatry Res. 210, 594–600. Frayne, S.M., Miller, D.R., Sharkansky, E.J., Jackson, V.W., Wang, F., Halanych, J.H., Berlowitz, D.R., Kader, B., Rosen, C.S., Keane, T.M., 2010. Using administrative data to identify mental illness: what approach is best? Am. J. Med. Qual. 25 (1), 42–50. Gallo, J., Meredith, L., Gonzales, J., et al., 2002. Do family physicians and internists differ in knowledge, attitudes, and self-reported approaches for depression? Int. J. Psychiatry Med. 32 (1), 1–20. Gaufberg, E., Joseph, R., Pels, R., Wyshak, G., Wieman, D., Nadelson, C., 2001. Psychosocial training in US internal medicine and family practice residency programs. Acad. Med. 76, 738–742. Harman, J., Schulberg, H., Mulsant, B., Reynolds, C., 2001. Effect of patient and visit characteristics on diagnosis of depression in primary care. J. Fam. Pract. 50, 1068. Harman, J., Veazie, P., Lyness, J., 2006. Primary care physician office visits for depression by older Americans. J. Gen. Intern. Med. 21 (9), 926–930. Hirschfeld, R., Keller, M., Panico, S., et al., 1997. The National Depressive and ManicDepressive Association consensus statement on the undertreatment of depression. J. Am. Med. Assoc. 277, 333–340. Katon, W., Von Korff, M., Lin, E., Bush, T., Ormel, J., 1992. Adequacy and duration of antidepressant treatment in primary care. Med. Care 30, 67–76. Lepine, J., 2002. The epidemiology of anxiety disorders: prevalence and societal costs. J. Clin. Psychiatry 63 (Suppl 14), S4–S8. Nichols, G., Brown, J., 2000. Following depression in primary care. Arch. Fam. Med. 9, 478–482. Paasche-Orlow, M., Roter, D., 2003. The communication patterns of internal medicine and family practice physicians. J. Am. Board Fam. Pract. 16, 485–493. Price, D., Beck, A., Nimmer, C., Bensen, S., 2000. Treatment of anxiety disorders in a primary care HMO setting. Psychiatr. Q. 71 (1), 31–35. Riolo, S.A., Nguyen, T.A., Greden, J.F., King, C.A., 2005. Prevalence of depression by race/ethnicity: findings from the National Health and Nutrition Examination Survey III. Am. J. Public Health 95 (6), 998–1000. Romano, P.S., Roos, L.L., Jollis, J.G., 1993. Adapting a clinical comorbidity index for use with ICD9-CM administrative data: differing perspectives. J. Clin. Epidemiol. 46, 1075–1079. Solberg, L.I., Engebretson, K.I., Sperl-Hillen, J.M., Hroscikoski, M.C., O’Connor, P.J., 2006. Are claims data accurate enough to identify patients for performance measures or quality improvement? The case of diabetes, heart disease, and depression. Am. J. Med. Qual. 21 (4), 238–245. Stein, M., Sherbourne, C., Craske, M., et al., 2004. Quality of care for primary care patients with anxiety disorders. Am. J. Psychiatry 161, 2230–2237. Wiest, F.C., Ferris, T.G., Manjusha, G., Campbell, E.G., Weissman, J.S., Blumenthal, D., 2002. Preparedness of internal medicine and family practice residents for treating common conditions. J. Am. Med. Assoc. 288 (20), 2609–2614. Williams, J., Rost, K., Dietrich, A., Ciotti, M., Zyzanski, S., Cornell, J., 1999. Primary care physicians' approach to depressive disorders. Arch. Fam. Med. 8, 58–67.
Contents lists available at ScienceDirect
Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad
Research report
Differences in prescribing patterns for anxiety and depression between General Internal Medicine and Family Medicine Jay A. Brieler n, Jeffrey F. Scherrer, Joanne Salas Department of Family and Community Medicine, Saint Louis University School of Medicine, St. Louis, MO 63104, United States
art ic l e i nf o
a b s t r a c t
Article history: Received 29 September 2014 Accepted 30 September 2014 Available online 13 October 2014
Introduction: Depression and anxiety are routinely managed by physicians in Family Medicine (FM) or General Internal Medicine (GIM). Because FM requires more behavioral health training than GIM, we sought to determine if prescribing patterns for patients with anxiety, depression, or both differed between FM vs. GIM providers. Methods: In a cross-sectional design, patient data and provider type were obtained from 2008 to 2013 electronic medical record patient data registry (n ¼27,225 (FM¼ 10,994, GIM¼ 16,231)) Prescription orders were modeled for specific benzodiazepines and antidepressants and by drug class. Covariates included gender, age, race, marital status and comorbidity index. Separate logistic regression models were computed, before and after adjusting for covariates, to estimate the odds of FM vs. GIM providers prescribing benzodiazepine or antidepressant medication to patients with anxiety, depression, and both disorders. Results: After adjusting for covariates, patients with anxiety alone, depression alone, and both had significantly greater odds of receiving an antidepressant (OR ¼2.08;95%CI:1.46–2.96, OR ¼2.13;95% CI:1.48–3.06, and OR ¼2.26;95%CI:1.09–4.66, respectively) if treated by FM vs. GIM. Benzodiazepine prescription did not differ by physician type. Limitations: It is not known if results will generalize to other regions of the United States. Conclusions: Patients with anxiety, depression, and both seen by FM providers, as compared to GIM providers, are more likely to receive antidepressant medications. Further investigation into the determinants of these differences is warranted. Under-treatment in GIM may result in less advantageous outcomes. & 2014 Elsevier B.V. All rights reserved.
Keywords: Depression Anxiety Antidepressants Psychopharmacology Primary care
1. Background Depression and anxiety disorders are very common and carry a significant personal and societal burden (Riolo et al., 2005; Lepine 2002). The majority of patients with anxiety and depression are treated by their primary care provider (PCP) rather than mental health professionals (Riolo et al., 2005; Harman et al., 2006). Numerous studies have identified gaps in the psychiatric care provided by PCPs (Hirschfeld et al., 1997; Bet et al., 2013; Stein et al., 2004; Price et al., 2000). Results from one cross-sectional study indicated that 70% of patients with moderate to severe depression were inadequately treated in the primary care setting compared to 29% of those seen in a specialized mental health care setting (Bet et al., 2013). Another investigation found that only 40% of patients diagnosed with an anxiety disorder and treated by their PCP had received adequate
n
Corresponding author. Tel.: þ 1 314 977 8480; fax: þ 1 314 977 5268. E-mail address: [email protected] (J.A. Brieler).
http://dx.doi.org/10.1016/j.jad.2014.09.056 0165-0327/& 2014 Elsevier B.V. All rights reserved.
medication, and only 25% of those were at a minimally adequate dose (Stein et al., 2004). As PCPs continue to provide a large proportion of the care for patients with anxiety and depression, efforts are warranted to improve the quality of mental health care delivered in primary care settings (Price et al., 2000). Differences in training may explain gaps in care. Psychosocial training during residency differs significantly between GIM and FM, with the requirements of the Accreditation Council for Graduate Medical Education (ACGME) for FM including both a greater quantity and breadth of experience (Accreditation Council for Graduate Medical Education 2014, 2013). FM residents selfreport greater preparedness to diagnose and treat depression in comparison to GIM residents (Wiest et al., 2002). A survey of program directors found that GIM programs require an average of 118 h of psychosocial training compared to 352 h for FM (Gaufberg et al., 2001). Limited evidence suggests differences in specialty are associated with differences in provider behavior. FM physicians are 65% more likely to diagnose depression than GIM physicians (Harman et al., 2001). FM physicians are more likely to ask their
154
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
patients about depression at a rate of 34% vs. 27.3% for GIM (Nichols and Brown, 2000), and FM physicians tend to engage in more psychosocial discussion or counseling (Harman et al., 2006; Paasche-Orlow and Roter, 2003) as compared to GIM physicians. Treatment differences may also exist. Analysis of the National Ambulatory Medical Care Survey (NAMCS) showed no difference between FM and GIM use of antidepressants for elderly patients with depression (Harman et al., 2006). However, this study focused on a specific age group. Results of surveys show that FM physicians self-report being more likely to prescribe selective serotonin reuptake inhibitors than GIM-trained doctors (Gallo et al., 2002; Williams et al., 1999). At this time we are unaware of existing reports comparing GIM physicians and FM physicians' actual prescribing patterns for patients with anxiety, depression or both using data from large medical record cohorts. The purpose of this study was to compare the prescribing patterns of GIM and FM physicians for adult patients with diagnosis of anxiety alone, depression alone and co-occurring anxiety and depression. We hypothesized that patients seen by FM physicians would be more likely to receive antidepressants and less likely to receive benzodiazepines for both anxiety and depression. Second, we hypothesized these differences would remain after controlling for patient demographics and comorbidities. Finally, in post-hoc analyses we investigated whether patients of FM physicians as compared to GIM physicians differentially are prescribed specific agents in both drug classes.
2. Methods 2.1. Subjects Clinical data were obtained from the Department of Family and Community Medicine's Primary Care Patient Data Registry (PCPD). The PCPD Registry was developed by extracting electronic medical record data from clinics staffed by FM and GIM providers at a large academic medical health system located in the St. Louis, Missouri, metropolitan area. The Registry contains ICD-9-CM codes, prescription orders, CPT codes, social history, family history, demographics, laboratory orders, referrals and vital signs. The Registry consists of 27,225 patients (FM¼ 10,994 patients, GIM¼16,231 patients) who had at least one encounter (e.g. office visit, procedure visit, or clinical support) between July 1, 2008 and July 31, 2013. Encounters occurred in any of the three ambulatory care clinics staffed by FM (n¼approximately 11 attending physiciansþ4 mid-levels) and in the case of GIM staffed by faculty, residents, and small number (o5) of mid-level providers (n¼ approximately 100 total). FM residents at this university are trained at a community site with a different electronic record, and were not able to be included in this analysis. Clinics are geographically dispersed throughout the St. Louis metropolitan area. For the present study, children (n¼1847), those with missing race (n¼485), and those with missing gender (n¼1) were excluded resulting in 24,892 patients age 18 90 available for analysis. The study procedures were reviewed and approved by the university IRB.
3. Measures 3.1. Type of primary care The probability of receiving prescriptions was compared between patients who visited FM providers vs. GIM providers.
3.1.1. Depression and anxiety disorder-unspecified Diagnoses were determined by the presence of ICD-9-CM codes at any time during the observation period. To be considered a case, the patient must have had at least two diagnoses for the same condition within a 12 month period. Defining depression by this method has excellent agreement with patient reported depression and written medical record abstraction with a 99% positive predictive value when compared to chart review (Frayne et al., 2010; Solberg et al., 2006). Depression ICD-9 codes included 296.2, 296.3 and 311. Anxiety disorder unspecified was defined by ICD-9 code 300.00. Three categories of depression and anxiety were defined: anxiety disorder unspecified without depression, depression without anxiety disorder unspecified, and both anxiety and depression defined if a patient ever had both diagnoses during the observation period. We did not include ICD codes for other anxiety disorders, including panic and generalized anxiety disorder, as those codes were very infrequently used in primary care.
3.1.2. Benzodiazepines and antidepressants Prescription orders were used to identify the prevalence of specific benzodiazepine and antidepressant use. Dose and duration were not considered in this report. Benzodiazepines included alprazolam, chlordiazepoxide, clonazepam, lorazepam, diazepam, and clorazepate. Antidepressants included the tricyclic antidepressants (TCAs): clomipramine, amitriptyline, desipramine, nortriptyline, doxepin, and imipramine. Selective serotonin re-uptake inhibitors (SSRIs) included citalopram, escitalopram, fluvoxamine, fluoxetine, paroxetine, and sertraline. Serotonin and norepinephrine reuptake inhibitors (SNRIs) included venlafaxine, duloxetine, and desvenlafaxine. Antidepressants not classified were considered as an ‘other’ category and included bupropion, nefazodone, trazodone, and mirtazapine.
3.2. Covariates Covariates were selected because they were associated with depression and anxiety and distributed differently in FM vs. GIM clinics. Covariates included gender, age category (18–40 years of age, 41–60 and 460), race (non-white vs. white), marital status (married, not married and unknown), and the Romano adapted Charlson Comorbidity Index which is a score derived from the presence of 17 health conditions associated with morbidity and mortality (Romano et al., 1993). Higher index scores indicate worse health and would likely be associated with more clinic visits, increased probability of detection and use of medication.
3.3. Analytic approach The entire observation period was treated as a cross-sectional study. Patient characteristics were compared between FM and GIM. The prevalence of drug class and individual medications was computed for FM and GIM within each anxiety and depression diagnostic group (i.e. anxiety alone, depression alone and comorbid anxiety and depression). Separate multivariate logistic regression models were computed to estimate the odds of receiving any benzodiazepine and any antidepressant in patients who received care by FM vs. GIM for each anxiety and depression diagnostic group. Full models simultaneously adjusted for all covariates. Measures of statistical significance were expressed by Chi-square p-Values for cross-tabulations and by 95% confidence intervals for odds ratios.
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
155
Table 1 Patient characteristics by FM and GIMa among patients 18 years or older (N ¼24,892). Variable, n (%)
Total (N¼ 24,892)
FM (n¼ 9898)
GIM (n¼ 14,994)
Male Age 18–40 41–60 4 60 Non-white race Marital status Married Other Unknown Mean Comorbidity Index (sd) Anxiety only Depression only Comorbid anxiety and depression
9649 (38.8)
3246 (32.8)
6403 (42.7)
10,502 (42.2) 8773 (35.2) 5617 (22.6) 9600 (38.6)
5099 (51.5) 3434 (34.7) 1365 (13.8) 2906 (29.4)
5403 5339 4252 6694
10,084 (40.5) 134,842 (54.2) 1326 (5.3) 0.72 (1.5) 760 (3.1) 1484 (6.0) 546 (2.2)
4861 (49.1) 4902 (49.5) 135 (1.4) 0.44 (1.1) 424 (4.3) 455 (4.6) 365 (3.7)
5223 (34.8) 8580 (57.2) 1191 (7.9) 0.90 (1.7) 336 (2.2) 1029 (6.9) 181 (1.2)
a
(36.0) (35.6) (28.4) (44.6)
p-Value o 0.0001 o 0.0001
o 0.0001 o 0.0001
o 0.0001 o 0.0001 o 0.0001 o 0.0001
GIM ¼ General Internal Medicine; FM¼ Family Medicine.
4. Results 4.1. Patient characteristics As shown in Table 1, patients were predominately female (61.2%), under 60 years of age (77.4%), and white (61.4%). Approximately 40.5% were married. The average comorbidity index was 0.72 (SD 7 1.5). 3.1% were diagnosed with anxiety disorderunspecified only, 6% with depression only and 2.2% had both diagnoses during the observation period. Compared to FM patients, GIM patients were significantly (p o0.0001) more likely to be older, of non-white race, male, unmarried, and have more medical co-morbidities. GIM patients were more likely to be diagnosed with depression alone, while FM patients were more likely to be diagnosed with anxiety alone or both conditions. 4.2. Medication choice The percent of patients receiving prescriptions by drug class and specific medication are shown in Table 2. Patients with anxiety alone were significantly (p o0.05) less likely to receive benzodiazepines from a FM provider compared to GIM. For this patient group, alprazolam and clonazepam were the most frequently used benzodiazepines by FM. Compared to patients of GIM physicians, those being treated by FM physicians were significantly (p o0.01) more likely to receive clonazepam (11.3% vs. 6.3%) and less likely to receive alprazolam (30.0% FM vs. 39.0% GIM). For patients with depression alone, benzodiazepine prescription did not differ between FM and GIM physicians. Patients with both anxiety and depression were significantly (p o0.01) less likely to receive alprazolam (18.1% vs. 34.3%) and significantly (p o0.01) more likely to receive clonazepam (23.6% vs. 7.8%) if treated by FM compared to GIM. Across diagnostic groups, patients treated by FM providers were more likely to receive anti-depressants as a class than patients treated by GIM providers. Across diagnostic groups, TCA prescriptions did not significantly differ between FM and GIM. Among patients with anxiety alone and depression alone, those treated by FM were significantly (p o0.01) more often prescribed an SSRI compared to those treated by GIM physicians. Patients of FM physicians with anxiety alone were more likely to receive escitalopram and fluoxetine. Patients diagnosed with depression alone were significantly more likely to be prescribed fluoxetine if treated by FM physicians and less likely to receive paroxetine as compared to patients of GIM providers. Among the ‘other’ antidepressants, patients with depression who were treated by FM physicians were significantly more often prescribed bupropion
(31.4% vs. 14.7%) compared to those treated by GIM providers. For patients with both depression and anxiety, those treated by FM, compared to patients of GIM, were more often prescribed any antidepressant, significantly less often prescribed duloxetine (4.9% vs. 9.4%, p o0.05), and significantly more often prescribed bupropion (32.6% vs. 17.1%, po 0.01). 4.3. Multivariate analysis Results of multivariate logistic regression models are shown in Tables 3–5 for patients with anxiety disorder-unspecified only (Table 3), depression alone (Table 4) and patients with both anxiety disorder – unspecified and depression (Table 5). As shown in Table 3, patients with anxiety disorder – unspecified were significantly less likely to receive a prescription for a benzodiazepine from a FM provider as compared to GIM. However, after adjusting for demographics and comorbidity, this was no longer significant. Older age (460 compared to 18–40 years of age) and higher comorbidity index were significantly associated with increased odds of receiving a benzodiazepine among patients with anxiety disorder-unspecified (OR range 1.15–2.06). In terms of antidepressants, FM patients were significantly more likely than GIM patients to receive an antidepressant before (OR¼2.58;95% CI:1.88–3.54) and after adjusting for covariates (OR¼ 2.08;95% CI:1.46–2.96). Among this patient group, older age (460 compared to 18–40 years of age) was significantly associated with lower odds of receiving an antidepressant (OR¼0.35; 95%CI: 0.22–0.55). Among patients with depression only (Table 4) there was no significant association between provider type (FM vs. GIM) and odds of receiving a benzodiazepine. However, those who were older than 60, compared to those 18–40, were significantly more likely to receive a benzodiazepine (OR¼ 1.75; 95%CI:1.10–2.80) and non-white patients were significantly less likely to receive a benzodiazepine (OR ¼0.46; 95%CI:0.31–0.66) than white patients. Higher comorbidity index was also significantly associated with increased odds of receiving a benzodiazepine (OR ¼1.09; 95% CI:1.01–1.17). Patients with depression alone were significantly more likely to receive an antidepressant if treated by FM physicians compared to GIM physicians before (OR¼2.31;95%CI:1.64–3.25) and after accounting for covariates (OR¼ 2.13,95%CI: 1.48–3.06). Among the depressed only patient group, patients who were middle age (41–60 years compared to those 18–40 years of age), had a significantly lower odds of receiving an antidepressant (OR¼ 0.66; 95%CI:0.44–0.98). Compared to married patients, those who were unmarried, divorced, separated, widowed or never married had significantly lower odds of receiving an antidepressant (OR¼0.59; 95%CI:0.43–0.82).
156
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
Table 2 Benzodiazepine and antidepressant prescribing patterns between FM and GIMa for patients with anxiety only, depression only, and comorbid depression and anxiety, aged 18 years or older. Drug (class), n (%)
Anxiety alone (n¼760) FM (n ¼424)
GIM (n ¼336) n
Depression alone (n¼ 1484)
Comorbid anxiety/depression (n ¼546)
FM (n¼ 455)
GIM (n¼ 1029)
FM (n¼365)
GIM (n¼181)
Any benzodiazepine Alprazolam Chlordiazepoxide Clonazepam Lorazepam Diazepam Clorazepate
194 (45.7) 127 (30.0) o5 (na)b 48 (11.3) 34 (8.0) 8 (1.9) o5 (na)b
183 (54.5) 131 (39.0)nn o 5 (na)b 20 (6.0)nn 36 (10.7) 15 (4.5)n o 5 (0.3)
68 (15.0) 30 (6.6) o 5 (na)b 20 (4.4) 12 (2.6) 8 (1.8) 0
136 (13.2) 73 (7.1) o 5 (na)b 30 (2.9) 30 (2.9) 17 (1.7) o 5 (0.1)
166 (45.5) 66 (18.1) 0 86 (23.6) 25 (6.9) 19 (5.2) 0
93 (51.3) 62 (34.3)nn o 5 (na)b 14 (7.8)nn 20 (11.1) 10 (5.5) 0
Any antidepressant Any TCA Clomipramine Amitriptyline Desipramine Nortriptyline Doxepin Imipramine
332 (78.3) 32 (7.6) 0 25 (5.9) o5 (na)b o5 (na)b o5 (na)b 0
196 (58.3)nn 23 (6.9) 0 15 (4.5) 0 o 5 (na)b o 5 (na)b 0
410 (90.1) 32 (7.0) 0 27 (5.9) 0 5 (1.1) o 5 (na)b 0
821 (79.8)nn 90 (8.8) 1 (0.1) 60 (5.8) o 5 (na)b 23 (2.2) o 5 (na)b 0
348 (95.3) 41 (11.2) 0 37 (10.1) 0 o 5 (na)b 0 0
156 (86.2)nn 24 (13.3) 0 16 (8.8) o 5 (na)b 7 (3.9)n o 5 (na)b 0
Any SSRI Citalopram Escitalopram Fluvoxamine Fluoxetine Paroxetine Sertraline
270 (63.7) 94 (22.2) 64 (15.1) 0 43 (10.1) 45 (10.6) 76 (17.9)
144 (42.9)nn 58 (17.3) 22 (6.6)nn 0 14 (4.2)nn 29 (8.6) 50 (14.9)
306 (67.3) 105 (23.1) 57 (12.5) o 5 (na)b 87 (19.1) 21 (4.6) 82 (18.0)
606 (58.9)nn 249 (24.2) 96 (9.3) 0 72 (7.0)nn 81 (7.9)nn 193 (18.8)
287 (78.6) 121 (33.2) 68 (18.6) 0 58 (15.9) 39 (10.7) 83 (22.7)
130 (71.8) 53 (29.3) 24 (13.3) 0 19 (10.5) 21 (11.6) 42 (23.2)
Any SNRI Venlafaxine Duloxetine Desvenlafaxine
40 (9.4) 32 (7.6) 7 (1.7) o5 (na)b
27 (8.0) 13 (3.9)n 13 (3.9) o 5 (na)b
86 (18.9) 45 (9.9) 30 (6.6) 14 (3.1)
154 (15.0) 78 (7.6) 83 (8.1) 6 (0.6)nn
69 (18.9) 44 (12.1) 18 (4.9) 9 (2.5)
31 (17.1) 15 (8.3) 17 (9.4)n o 5 (na)b
Any otherc Bupropion Nefazodone Trazodone Mirtazapine
72 (17.0) 43 (10.1) 0 31 (7.3) 8 (1.9)
55 (16.4) 27 (8.0) 0 26 (7.7) 8 (2.4)
175 (38.5) 143 (31.4) 0 41 (9.0) 13 (2.9)
293 (28.5)nn 151 (14.7)nn o 5 (na)b 123 (12.0) 61 (5.9)n
152 (41.6) 119 (32.6) 0 44 (12.1) 12 (3.3)
61 (33.7) 31 (17.1)nn o 5 (na)b 28 (15.5) 9(5.0)
n
po 0.05. p o0.01. a GIM ¼General Internal Medicine; FM¼ Family Medicine. b Cells with less than 5 patients are reported as ‘o 5’ to protect patient privacy and confidentiality. c Monoamine Oxidase Inhibitors represented o 5 total prescriptions as a class across diagnosis. nn
Table 3 Association (OR; 95% CI) between FM vs. GIM and any prescription of benzodiazepine (BDM) and antidepressant medication (ADM) for anxiety only (n¼760).
GIMa FM Male Age (years) 18–40 41–60 4 60 Race White Non-white Marital status Married Other Unknown Comorbidity index
BDM – unadjusted
BDM – adjusted
ADM –unadjusted
ADM – adjusted
1.0 0.71 (0.53–0.94) –
1.0 0.95 (0.68–1.32) 1.04 (0.75–1.43)
1.0 2.58 (1.88–3.54) –
1.0 2.08 (1.46–2.96) 1.10 (0.77–1.57)
–
1.0 1.75 (1.23–2.49) 2.06 (1.34–3.19)
–
1.0 0.79 (0.53–1.17) 0.35 (0.22–0.55)
1.0 0.77 (0.53–1.12)
–
1.0 0.90 (0.61–1.33)
1.0 1.34 (0.98–1.83) 1.80 (0.84–3.85) 1.15 (1.03–1.28)
–
1.0 1.00 (0.71–1.41) 1.43 (0.65–3.13) 1.03 (0.93–1.15)
–
–
–
–
Bold text indicates significant odds ratio, p o 0.05. a
GIM ¼General Internal Medicine; FM¼ Family Medicine.
Among patients with both anxiety and depression diagnoses (Table 5), there was no significant association between provider type (FM vs. GIM) and odds of receiving a benzodiazepine. Higher comorbidity index was significantly associated with odds of receiving a benzodiazepine (OR¼1.13; 95%CI:1.01–1.27). Patients treated
by FM had significantly greater odds of receiving an antidepressant compared to those treated by GIM both before (OR¼ 3.28; 95% CI:1.72–6.25) and after (OR¼ 2.26; 95%CI:1.09–4.66) adjusting for covariates. Compared to patients aged 18–40 years, patients 41–60 and 460 years of age had significantly lower odds of receiving an
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
157
Table 4 Association (OR; 95% CI) between FM vs. GIM and any prescription of benzodiazepine (BDM) and antidepressant medication (ADM) for depression only (n¼ 1484).
GIMa FM Male Age (years) 18–40 41–60 4 60 Race White Non-white Marital status Married Other Unknown Comorbidity index
BDM – unadjusted
BDM – adjusted
ADM –unadjusted
ADM –adjusted
1.0 1.15 (0.84–1.58) –
1.0 1.17 (0.83–1.65) 0.75 (0.53–1.06)
1.0 2.31 (1.64–3.25) –
1.0 2.13 (1.48–3.06) 0.81 (0.60–1.10)
–
1.0 1.47 (0.95–2.28) 1.75 (1.10–2.80)
–
1.0 0.66 (0.44–0.98) 0.73 (0.48–1.12)
–
1.0 0.46 (0.31–0.66)
–
1.0 1.03 (0.76–1.39)
–
1.0 0.79 (0.57–1.10) 0.86 (0.49–1.50) 1.09 (1.01–1.17)
–
1.0 0.59 (0.43–0.82) 0.68 (0.41–1.12) 1.04 (0.97–1.13)
–
–
Bold text indicates significant odds ratio, po 0.05. a
GIM ¼ General Internal Medicine; FM¼ Family Medicine.
Table 5 Association (OR; 95% CI) between FM vs. GIM and any prescription of benzodiazepine (BDM) and antidepressant medication (ADM) for comorbid anxiety/depression (n¼ 546).
GIMa FM Male Age (years) 18–40 41–60 4 60 Race White Non-white Marital status Married Other Unknown Comorbidity index
BDM – unadjusted
BDM – adjusted
ADM – unadjusted
ADM –adjusted
1.0 0.79 (0.55–1.13) –
1.0 0.87 (0.58–1.30) 0.83 (0.54–1.28)
1.0 3.28 (1.72–6.25) –
1.0 2.26 (1.09–4.66) 0.93 (0.41–2.08)
–
1.0 1.28 (0.85–1.92) 1.08 (0.65–1.82)
–
1.0 0.30 (0.12–0.78) 0.32 (0.11–0.93)
–
1.0 0.64 (0.40–1.00)
–
1.0 1.27 (0.57–2.84)
–
1.0 1.06 (0.74–1.53) 1.25 (0.55–2.84) 1.13 (1.01–1.27)
–
1.0 0.49 (0.23–1.05) 0.72 (0.18–2.92) 0.89 (0.77–1.04)
–
–
Bold text indicates significant odds ratio, po 0.05. a
GIM ¼ General Internal Medicine; FM¼ Family Medicine.
antidepressant (OR¼ 0.30; 95%CI:0.12–0.78; and OR¼ 0.32; 95% CI:0.11–0.93, respectively). Due to the differences seen in the prescribing of alprazolam and clonazepam, a post-hoc multivariate analysis was performed. After adjusting for age, sex, race, marital status, and co-morbidity, the differences in the anxiety only and depression only groups were no longer significant. In the co-morbid anxiety and depression group, FM providers were more likely to prescribe clonazepam (OR ¼ 3.27;95% CI: 1.70–6.28) and less likely to prescribe alprazolam (OR ¼0.41, 95%CI: 0.26–0.66).
5. Discussion Primary care patients diagnosed with anxiety disorder-unspecified, depression, or both conditions were more than twice as likely to be prescribed an antidepressant if treated by a FM provider compared to those treated by GIM providers. For all diagnosis groups, provider type was not significantly associated with odds of receiving a benzodiazepine. Our findings in adult patients of varying age differ from the NAMCS analysis which found no difference in the prescribing of antidepressants between GIM and FM physicians in an older population. Not only do the data in this study have enhanced
external validity due to the inclusion of a wider age range, but the preservation of effect after controlling for patient demographics and comorbidity increases the likelihood that the differences seen are, in fact, related to the specialty of the provider. Antidepressants, including SSRIs and SNRIs, are considered first-line agents for both depression and anxiety (American Psychiatric Association, 2009, 2010). The rate of antidepressant use by psychiatrists seeing patients with depression is in the range of 86–89% (Paasche-Orlow and Roter, 2003). Thus, the differential use of these medications among primary care specialties represents a difference in the adherence to standards of care, at least at the practice population level. Based on our data, no conclusion can be made on the cause of these differences. One possibility is the differential quantity of behavioral health training in FM as opposed to GIM residency programs. Differential patterns of referral to specialty mental health care and differences in length or severity of mental illness between types of practice are two other potential factors that could contribute to our results. 5.1. Limitations Several limitations must be noted in this analysis. First, our data showed significantly fewer patients diagnosed with anxiety, depression, or both in the GIM population compared to the FM
158
J.A. Brieler et al. / Journal of Affective Disorders 172 (2015) 153–158
cohort. Whether this represents a detection bias or a tendency of certain patients to preferentially choose one type of provider over another is unknown. Our dataset is limited to the geographic area of the St. Louis metropolitan area. To what extent our findings can be generalized to other locations is unclear. In addition, the PCPD registry reflects care provided in an academic medicine setting. The registry data captured includes resident physicians in GIM only. A small number of physician assistants and nurse practitioners were included in the registry data in both groups. It is unclear what, if any, effect these differences would have on the results seen in our data. Many aspects of care were not examined in this study. We do not know the patients' psychiatric medication history or responses. We do not know whether medications were initiated by the primary care providers studied or simply continued based on previous psychiatric care. We did not examine the duration or dosage of treatment provided. These specific items have been identified as important aspects of care that may represent gaps in PCP management of psychiatric illness (Katon et al., 1992), and may represent areas for further study.
6. Conclusions Our data indicate that patients with anxiety and depression seen in FM as opposed to GIM practices are more likely to be prescribed antidepressant medication. This difference suggests that FM providers are in closer alignment with mental health care professionals and published guidelines. If depression is undertreated in GIM, patients are at risk of relapse and a more chronic course of disease. Further investigation is warranted to clarify the nature of these differences across setting and to more specifically explore the possible association between behavioral health training and prescribing patterns.
Role of funding source An educational Grant from the Mindlin Foundation provided partial support for Dr. Scherrer's contribution.
Conflict of interest None.
Acknowledgments None.
References Accreditation Council for Graduate Medical Education, 2014. ACGME program requirements in family medicine. 〈http://www.acgme.org/acgmeweb/Portals/ 0/PFAssets/ProgramRequirements/120_family_medicine_07012014.pdf〉. Accreditation Council for Graduate Medical Education, 2013. ACGME program requirements in internal medicine. 〈https://www.acgme.org/acgmeweb/Por tals/0/PFAssets/2013-PR-FAQ-PIF/140_internal_medicine_07012013.pdf〉. American Psychiatric Association, 2009. Practice Guideline for the Treatment of Panic Disorder, 2nd edition. American Psychiatric Association, 2010. Practice Guideline for the Treatment of Patient with Major Depressive Disorder, third edition. Bet, P., Hugtenburg, J., Penninx, B., Van Balkom, A., Nolen, W., Hoogendijk, W., 2013. Treatment inadequacy in primary and specialized care patients with depressive and/or anxiety disorders. Psychiatry Res. 210, 594–600. Frayne, S.M., Miller, D.R., Sharkansky, E.J., Jackson, V.W., Wang, F., Halanych, J.H., Berlowitz, D.R., Kader, B., Rosen, C.S., Keane, T.M., 2010. Using administrative data to identify mental illness: what approach is best? Am. J. Med. Qual. 25 (1), 42–50. Gallo, J., Meredith, L., Gonzales, J., et al., 2002. Do family physicians and internists differ in knowledge, attitudes, and self-reported approaches for depression? Int. J. Psychiatry Med. 32 (1), 1–20. Gaufberg, E., Joseph, R., Pels, R., Wyshak, G., Wieman, D., Nadelson, C., 2001. Psychosocial training in US internal medicine and family practice residency programs. Acad. Med. 76, 738–742. Harman, J., Schulberg, H., Mulsant, B., Reynolds, C., 2001. Effect of patient and visit characteristics on diagnosis of depression in primary care. J. Fam. Pract. 50, 1068. Harman, J., Veazie, P., Lyness, J., 2006. Primary care physician office visits for depression by older Americans. J. Gen. Intern. Med. 21 (9), 926–930. Hirschfeld, R., Keller, M., Panico, S., et al., 1997. The National Depressive and ManicDepressive Association consensus statement on the undertreatment of depression. J. Am. Med. Assoc. 277, 333–340. Katon, W., Von Korff, M., Lin, E., Bush, T., Ormel, J., 1992. Adequacy and duration of antidepressant treatment in primary care. Med. Care 30, 67–76. Lepine, J., 2002. The epidemiology of anxiety disorders: prevalence and societal costs. J. Clin. Psychiatry 63 (Suppl 14), S4–S8. Nichols, G., Brown, J., 2000. Following depression in primary care. Arch. Fam. Med. 9, 478–482. Paasche-Orlow, M., Roter, D., 2003. The communication patterns of internal medicine and family practice physicians. J. Am. Board Fam. Pract. 16, 485–493. Price, D., Beck, A., Nimmer, C., Bensen, S., 2000. Treatment of anxiety disorders in a primary care HMO setting. Psychiatr. Q. 71 (1), 31–35. Riolo, S.A., Nguyen, T.A., Greden, J.F., King, C.A., 2005. Prevalence of depression by race/ethnicity: findings from the National Health and Nutrition Examination Survey III. Am. J. Public Health 95 (6), 998–1000. Romano, P.S., Roos, L.L., Jollis, J.G., 1993. Adapting a clinical comorbidity index for use with ICD9-CM administrative data: differing perspectives. J. Clin. Epidemiol. 46, 1075–1079. Solberg, L.I., Engebretson, K.I., Sperl-Hillen, J.M., Hroscikoski, M.C., O’Connor, P.J., 2006. Are claims data accurate enough to identify patients for performance measures or quality improvement? The case of diabetes, heart disease, and depression. Am. J. Med. Qual. 21 (4), 238–245. Stein, M., Sherbourne, C., Craske, M., et al., 2004. Quality of care for primary care patients with anxiety disorders. Am. J. Psychiatry 161, 2230–2237. Wiest, F.C., Ferris, T.G., Manjusha, G., Campbell, E.G., Weissman, J.S., Blumenthal, D., 2002. Preparedness of internal medicine and family practice residents for treating common conditions. J. Am. Med. Assoc. 288 (20), 2609–2614. Williams, J., Rost, K., Dietrich, A., Ciotti, M., Zyzanski, S., Cornell, J., 1999. Primary care physicians' approach to depressive disorders. Arch. Fam. Med. 8, 58–67.