Skip to main content
Journal of Managed Care & Specialty Pharmacy logoLink to Journal of Managed Care & Specialty Pharmacy
. 2018 Aug;24(8):10.18553/jmcp.2018.24.8.769. doi: 10.18553/jmcp.2018.24.8.769

Effects of the 2009 USPSTF Depression Screening Recommendation on Diagnosing and Treating Mental Health Conditions in Older Adults: A Difference-in-Differences Analysis

Taeho Greg Rhee 1,*, Benjamin D Capistrant 2, Jon C Schommer 3, Ronald S Hadsall 3, Donald L Uden 3
PMCID: PMC6084471  NIHMSID: NIHMS977700  PMID: 30058984

Abstract

BACKGROUND:

Depression is a common mental condition in U.S. older adults. To improve rates of underdiagnosis and undertreatment for depression and other mental health conditions in primary care settings, the U.S. Preventive Services Task Force (USPSTF) updates and disseminates its depression screening guideline regularly.

OBJECTIVE:

To examine the effects of the 2009 USPSTF depression screening recommendation on the 3 following outcomes: diagnoses of mental health conditions, antidepressant prescriptions (overall and potentially inappropriate), and provision of nonpharmacological psychiatric services in office-based outpatient primary care visits made by adults aged 65 or older.

METHODS:

Data from the 2006-2012 National Ambulatory Medical Care Survey (NAMCS), a nationally representative sample of office-based outpatient primary care visits among older adults (n = 15,596 unweighted), were used. NAMCS represents physician practicing patterns of ambulatory medical care services utilization at the national level. Using a series of multivariate difference-in-differences analyses, we estimated effects of the USPSTF depression screening recommendation on the previously mentioned outcomes by comparing pre- (2006-2009) and post- (2010-2012) periods to describe primary care physician practice patterns.

RESULTS:

Differences in any mental health diagnosis by the depression screening status were -34.7% in the pre-2009 period and -20.2% in the post-2009 period, resulting in a differential effect of -14.4% (95% CI = -28.2, -0.6; P = 0.040). No differential effect was found in other outcomes.

CONCLUSIONS:

While there are mixed findings about efficacy and effectiveness of depression screening in the existing literature, more population-based observational research is needed to strengthen and support current USPSTF depression screening recommendation statements in the United States.


What is already known about this subject

  • Older adults are at risk of having depression and other psychiatric disorders, yet they may be often undiagnosed and untreated.

  • U.S. Preventive Services Task Force (USPSTF) regularly updates and disseminates depression screening guidelines for primary care health care providers.

What this study adds

  • This study investigated USPSTF depression screening recommendations for diagnoses of mental health conditions, antidepressant prescriptions, and provision of nonpharmacological psychiatric services among older adults in outpatient care.

  • Study findings show that at the national level the effects of guideline recommendations are minimal.

Aging-related depression is the leading cause of disability and the major contributor for disease burden, and depression and other related mood disorders are often underdiagnosed and undertreated among adults aged 65 and over (hereafter referred to as older adults).1,2 While adults with depression are not likely to make psychiatry-related visits, they still seek care in primary care or other specialty visits, making “these visits particularly important opportunities to detect and initiate treatment of depression.”3 In light of providing care for depression in primary care and other specialty visits, screening for depression has become a “prominent component of the ‘detect-treat-improve’ paradigm for undetected depression” since the mid-1990s.3

In 2002, the U.S. Preventive Services Task Force (USPSTF) recommended depression screening for all eligible adults.4 Subsequently, the 2009 USPSTF practice recommendation stated that depression screening should be provided in eligible adults to “ensure accurate diagnosis, effective treatment, and appropriate follow-up” related to depression and other mental health conditions.5,6 The 2009 USPSTF guideline distinguished 2 different recommendations: a grade B recommendation is given when staff-assisted depression care supports are in place, and a grade C recommendation is given when staff-assisted depression care supports are not present in primary care settings.6 Unlike the grade B recommendation, the grade C recommendation indicates that the USPSTF makes no recommendation for or against routine depression screening service, and the service may be provided based on professional judgment and/or patient preferences.6

While clinical and policy efforts have been made in the past decades, depression screening is still a controversial topic in the existing literature. Advocates of depression screening suggest that it should be actively utilized since both detection and treatment rates of depression are relatively low given the fact that prevalence rates of depression and other mood disorders are high among older adults in ambulatory care settings.7,8 However, critics argue that depression screening may not be a cost-effective approach due to its high false-positive rates.7

In the existing literature, some studies have assessed the policy effect of recent USPSTF guidelines (e.g., mammography use and pediatric urinalysis).9,10 No study has yet assessed the effect of the 2009 depression screening recommendation, including among older adults aged 65 and over. Gaps remain in our understanding of whether the 2009 depression screening recommendation had effects on the following outcomes: diagnoses of depression and other psychiatric disorders, overall and potentially inappropriate antidepressant prescriptions, and provision of nonpharmacological psychiatric services among older adults.

In this study, we focused on older adults only for 2 reasons. First, they have greater rates of underdiagnosis and undertreatment for depression and other psychiatric disorders, while they have a higher depression rate than any other age group.11 Second, our conceptualization of potentially inappropriate antidepressant use was based on the Beers Criteria, which strictly apply to the older adult population only. We hypothesized that depression screening may help increase diagnosis rates of depression or other psychiatric disorders because the depression screening guideline is a tool to detect depression or other psychiatric disorders in a timely manner. Additionally, a recent study from Rhee et al. (2017) suggests that depression screening was associated with a reduced rate of potentially inappropriate antidepressant prescriptions.11 Based on this, we hypothesized that the depression screening would be associated with a decreased rate of potentially inappropriate antidepressant prescriptions. To address these knowledge gaps, we examined the policy effects of the 2009 USPSTF depression screening recommendation on the previously mentioned outcomes between pre- (2006-2008) and post- (2010-2012) periods in office-based outpatient primary care visits made by older adults.

Methods

Data Source and Study Sample

Data used in this study originated from the 2006-2012 National Ambulatory Medical Care Survey (NAMCS), which is administrated by National Center for Health Statistics of the Centers for Disease Control and Prevention.12 The NAMCS is an annual, cross-sectional survey of visits to office-based physicians in outpatient settings and provides reliable information about the provision and/or use of ambulatory medical care services in the United States.12 Using a complex sampling design, selected physicians took the survey, resulting in a systematic random sample of office-based outpatient visits. Further, NAMCS utilizes an automated patient record form to collect information about the patient’s demographic and clinical characteristics (e.g., clinical diagnosis and medications prescribed) in a sampled visit. The analytic sample used in this study included office-based outpatient primary care visits made by older adults aged 65 and over and had completed data for all covariates (n = 15,596 unweighted). As this study used publicly available data, the research procedure for this study was exempted by the Institutional Review Board at University of Minnesota, Twin Cities. Further details of the survey, including descriptions, questionnaires, sampling methodology, and datasets, are publicly available on the NAMCS website.13

Measures

Dependent Variables.

The 3 main outcomes of interest were diagnosis of mental health conditions, antidepressant prescribing (overall and potentially inappropriate), and provision of nonpharmacological psychiatric services. First, we included the diagnosis of mental health conditions. The NAMCS collects up to 3 clinical diagnoses using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes. Based on Olfson et al.’s work (2014),14 we constructed binary variables (yes or no) for diagnosis of mental health conditions as follow: mood disorders (ICD-9-CM diagnostic codes 293.83, 296, 298.0, 300.4, 301.1, 311, or 313.1), anxiety disorders (ICD-9-CM diagnostic codes 293.84, 300.0, 300.2, 300.3, 308.3, 309.21, or 309.81), psychoses/developmental disorders (ICD-9-CM diagnostic codes 290.0-295.9, 297.0-298.0, 298.3-299.9, 310.0-310.9, or 317-319), and other mental disorders (ICD-9-CM diagnostic codes 290-319, not included in aforementioned codes). We also constructed a comorbid mental disorder diagnosis variable indicating the presence of 2 or more diagnostic groups (mood, anxiety, psychoses/developmental, or other).

Antidepressant prescription was another outcome measure. The NAMCS collected data on up to 8 medications in 2006-2011 and up to 10 medications in 2012. Using the 2015 American Hospital Formulary Service (AHFS) Compendium, Wolters Kluwer’s Drug Facts and Comparisons, and previous studies, we identified prescribed antidepressant medications using generic names (Table 1).8,11,14-18 We constructed a binary variable (yes or no) for overall antidepressant prescriptions. For potentially inappropriate antidepressant prescriptions, we constructed a binary variable (yes or no) using the 2012/2015 Beers Criteria (Table 1 and Table 2).19,20

TABLE 1.

Antidepressant Medications by Class

Tricyclic antidepressants
  Amitriptylinea,b,c
  Amoxapineb
  Clomipraminea,b,c
  Desipramineb
  Doxepina,b,c
  Imipraminea,b,c
  Maprotiline
  Nortriptylineb
  Protriptylineb
  Trimipraminea,b,c
Serotonin modulators
  Nefazodone
  Trazodone
  Vilazodoned
  Vortioxetined
Selective serotonin reuptake inhibitors
  Citalopram
  Escitalopram
  Fluoxetine
  Fluvoxamine
  Paroxetineb
  Sertraline
Monoamine oxidase inhibitors
  Isocarboxazid
  Phenelzine
  Tranylcypromine
  Rasagilinee
  Selegilinee
Serotonin and norepinephrine reuptake inhibitors
  Desvenlafaxine
  Duloxetine
  Levomilnaciprand
  Venlafaxine
  Milnacipranf
Miscellaneous
  Bupropion
  Mirtazapine

aDenotes tertiary tricyclic antidepressants.

bDenotes drugs with strong anticholinergic properties.

cIndicates that it should be avoided, regardless of diagnosis, according to 2012 or 2015 Beers Criteria.

dIndicates that it is not available in National Ambulatory Medical Care Survey.

eDenotes a monoamine oxidase B and is primarily classified as anti-Parkinsonian agents.

fIs primarily classified as fibromyalgia agents.

TABLE 2.

2012/2015 Beers Criteria for Potentially Inappropriate Antidepressant Use in Older Adults Due to Drug-Disease or Drug-Syndrome Interactions That May Exacerbate the Disease or Syndrome19,20

Disease or Syndrome (ICD-9-CM Code) Antidepressant a Rationale Recommendation Quality of Evidence Strength of Recommendation
Cardiovascular
  Syncope (780.2, 992.1) Tertiary TCAs Increase risk of orthostatic hypotension or bradycardia Avoid Moderate Strong
Central nervous system
  Chronic seizures or epilepsy (345, 780.33) Bupropion, maprotiline Lowers seizure threshold; may be acceptable in patients with well-controlled seizures in whom alternative agents have not been effective Avoid Moderate Strong
  Delirium (290.11, 290.3, 290.41, 291.0, 292.81, 293.0, 293.1) TCAs, anticholinergics Induce or worsen delirium in older adults; if discontinuing drugs used chronically, taper to avoid withdrawal symptoms Avoid Moderate Strong
  Dementia and cognitive impairment (290, 291.2, 292.82, 294.10, 294.11, 294.20, 294.21, 331.0, 331.19, 331.82, 331.83) Anticholinergics Avoid because of adverse CNS effects Avoid High Strong
  History of falls or fractures (E880-E888) TCAs, SSRIs Ability to produce ataxia, impaired psychomotor function, syncope, and additional falls Avoid unless safer alternatives are not available High Strong
Gastrointestinal
  Chronic constipation (564) Tertiary TCAs, anticholinergics Can worsen constipation Avoid unless no other alternatives Moderate to low Weak
  Lower urinary tract symptoms, benign prostatic hyperplasia (600) Anticholinergics May decrease urinary flow and cause urinary retention Avoid in men Moderate Inhaled agents: strong; others: weak

aRefer to Table 1 for full description.

CNS = central nervous system; ICD-9-CM = International Classification of Diseases, Ninth Revision, Clinical Modification; TCA = tricyclic antidepressant; SSRI = selective serotonin reuptake inhibitor.

Third, we included nonpharmacological psychiatric service use as an outcome measure. The NAMCS asks 2 questions to assess whether psychotherapy and mental health counseling other than psychotherapy were provided (yes or no).21 Due to the limited sample size, a binary variable (yes or no) was created aggregating these 2 questions.

Independent Variables.

The key exposure of interest was the depression screening status (yes or no). More specifically, the NAMCS asks, “Was the depression screening exam ordered or provided at the visit?” The time indicator variable was also included to identify before and after the 2009 USPSTF depression screening guideline (0 = 2006-2008 [reference category] and 1 = 2009-2012).

Control Variables.

Based on previous studies, we identified the following covariates. We included demographic variables: age (65-74, 75-84, or 85+), gender, race/ethnicity, region (Northeast, Midwest, South, or West), primary source of payment (Medicare, Medicaid, private, or others), reason for visit (acute problem, routine chronic problem, preventive care, or pre- or post-surgery care), and repeat of visits within the past 12 months (none, 1-2, 3-5, or 6+).8,11,17,18,22-24 In addition, we included the following clinical characteristics: type of medical practice (solo or others), metropolitan statistical area (MSA) status (yes or no), time spent with doctor (< 15, 15-20, 21-30, or > 30 minutes), number of chronic conditions (none, 1, 2-3, or 4+), and number of medications (0-2, 3-5, or 6+). The number of chronic conditions was based on 14 chronic conditions (yes or no) collected by the NAMCS (e.g., arthritis, congestive heart failure, and diabetes).21 The repeat of visits variable had the largest missing proportion (14.8%) and was imputed based on age, gender, and the number of medications using the Hotdeck imputation technique.25 Other variables that had missing values included primary source of payment (3.9%), reason for visit (1.7%), and the number of chronic conditions (1.2%). Observations with all of these missing values (6.5%) were systematically excluded, leaving the final sample size of 15,596 visits (unweighted).

Data Analysis

To answer our research questions, we conducted bivariate and multivariable analyses. First, we examined the extent to which demographic and clinical characteristics differed in visits by the time period before (2006-2008) and after (2010-2012) the implementation of 2009 USPSTF depression screening recommendation. We used cross-tabulations and design-based F-tests to investigate differences by depression screening status. Second, we employed a series of difference-in-differences (DID) approaches using multivariate logistic models to investigate if the 2009 USPSTF depression screening recommendation had differential effects on 3 aforementioned outcomes. We chose the DID method because it allows us to compare treatment and comparison groups (i.e., visits with depression screening and visits without depression screening) in terms of selected outcome changes over time relative to the outcomes observed in the pre-2009 time period.26 The strength of the DID approach is that it can minimize bias from unmeasured confounders and control for secular trends that might have affected depression screening rates.26 This was done by regressing each outcome on the indicator variable of depression screening status (yes or no), a time indicator variable (before 2009 [i.e., 2006-2008] or after 2009 [i.e., 2010-2012]), and the interaction of these 2 variables, while adjusting for all other covariates. The DID approach compares the changes in proportions of selected outcomes by pre-2009 and post-2009 time periods (i.e., first difference) and comparing the first differences by the depression screening status (i.e., second difference). We used Stata version 13.1 (StataCorp, College Station, TX) for all analyses, and the svy commands in Stata were employed to account for the complex sample design of the NAMCS (i.e., unequal probability of selection, clustering, and stratification).

Results

Study Sample Characteristics

Table 3 presents demographic and clinical characteristics of office-based outpatient primary care visits made by older adults by the time period before (2006-2008) and after (2010-2012) the implementation of the 2009 USPSTF depression screening recommendation. The depression screening rates were nearly the same (1.9%) in the 2 different time periods. Further, all outcomes of interest were not significantly different between time periods. For demographic characteristics, age, race/ethnicity, and region did not differ significantly between time periods. Gender and the source of payment did differ significantly, such that more visits were made by male older adults (P = 0.001) and covered by Medicare (P < 0.001) in the post-2009 time period. Clinical characteristics, reason for visit, type of medical practice, and MSA status did not differ across time periods. Between 2006 and 2008, 74.4% of patients had 3 or more visits in the past 12 months, and this rate was significantly higher than that of the post-2009 period (68.9%; P < 0.001). The distribution of time spent with a doctor differed significantly across the time periods (P < 0.001). For example, 34.1% of visits had 21 or more minutes spent with a doctor in the post-2009 period, which is significantly higher than that of the pre-2009 period (23.3%). We also observed that the number of multiple chronic conditions and the number of medications prescribed varied by the time period (P = 0.006 and P = 0.001, respectively). For instance, 71.3% of older adults had 2 or more chronic conditions in the post-2009 period, which was higher than that of the pre-2009 period (67.1%). Similarly, 67.7% of older adults who had visits had 3 or more concomitant medications prescribed in the post-2009 period, which was higher than that of the pre-2009 period (63.1%).

TABLE 3.

Selected Baseline Characteristics (Weighted Percent) of Older Adults in Office-Based Outpatient Primary Care Settings by Time Periods, 2006-2012 NAMCS

Pre-2009 (2006-2008) Post-2009 (2010-2012) Total P Value
Depression screening
  No 98.1 98.1 98.1 0.963
  Yes 1.9 1.9 1.9
Mental disorder diagnosis
  No 93.7 93.1 93.4 0.330
  Yes 6.3 6.9 6.6
Antidepressant prescribed
  No 88.1 87.2 87.7 0.470
  Yes, appropriate 10.4 11.4 10.9
  Yes, potentially inappropriate 1.5 1.4 1.5
Psychotherapy or other mental health counseling provided
  No 99.4 99.3 99.3 0.669
  Yes 0.6 0.7 0.7
Age, years
  65-74 49.7 50.5 50.1 0.227
  75-84 36.8 35.0 35.9
  85+ 13.6 14.5 14.0
Gender
  Female 59.9 56.7 58.3 0.012
  Male 40.1 43.3 41.7
Race/ethnicity
  Non-Hispanic white 77.9 78.2 78.0 0.935
  Non-Hispanic black 9.4 8.6 9.0
  Hispanic 8.3 8.4 8.3
  Othera 4.5 4.9 4.7
Region
  Northeast 17.0 18.6 17.8 0.096
  Midwest 19.7 21.7 20.7
  South 43.4 35.7 39.6
  West 19.8 24.0 21.9
Source of payment
  Private 17.2 14.7 15.9 < 0.001
  Medicare 75.9 82.4 79.1
  Medicaid 4.9 1.6 3.3
  Otherb 2.1 1.3 1.7
Reason for visit
  Acute problem 32.5 31.3 31.9 0.265
  Routine chronic problem 50.9 49.3 50.1
  Preventive care 14.3 16.6 15.4
  Pre- or postsurgery 2.3 2.9 2.6
Repeat of visits
  0 visits 2.6 4.5 3.3 < 0.001
  1-2 visits 23.0 26.6 24.4
  3-5 visits 39.3 39.3 39.3
  6+ visits 35.1 29.6 33.0
Type of medical practice
  Solo 89.0 89.5 89.3 0.832
  Otherc 11.0 10.5 10.7
MSA status
  MSA 80.6 79.7 80.1 0.780
  Non-MSA 19.4 20.3 19.9
Time spent with doctor
  < 15 min. 14.8 14.0 14.4 < 0.001
  15-20 min. 61.8 52.0 56.9
  21-30 min. 16.2 22.0 19.1
  > 30 min. 7.1 12.1 9.6
Multiple chronic conditions
  None 11.1 8.8 10.0 0.008
  1 21.8 19.9 20.9
  2-3 47.4 47.2 47.3
  4+ 19.7 24.1 21.9
Number of medications
  0 11.8 11.1 11.5 0.001
  1-2 25.1 21.2 23.2
  3-5 29.4 25.8 27.6
  6+ 33.7 41.9 37.7
Sample size
  Unweighted sample 6,283 9,313 15,596
  Weighted visits 47,087,308 46,502,737 93,590,045

aIncludes Asians, American Indian/Alaska Natives, Native Hawaiian or Other Pacific Islanders, and multiple races.

bIncludes worker’s compensation, self-pay, no charge, and others.

cIncludes federally qualified health center, non-federal government clinic, family planning clinic, health maintenance organization or other prepaid practice plan, and faculty practice plan.

MSA = metropolitan statistical area; NAMCS = National Ambulatory Medical Care Survey.

Difference-in-Differences

Table 4 presents the adjusted prevalence of selected outcomes in office-based outpatient primary care visits made by older adults by depression screening status and the time period. Overall, the prevalence of diagnosis with any mental disorder significantly decreased from 40.2% in pre-2009 to 26.6% in post-2009 in visits with depression screening. On the other hand, the prevalence of diagnosis with any mental disorders increased from 5.5% in pre-2009 to 6.4% in post-2009 in visits without depression screening. Differences by the depression screening status were -34.7% in the pre-2009 period and -20.2% in the post-2009 period, resulting in a differential effect of -14.4% (95% confidence interval [CI] = -28.2, -0.6; P = 0.040). In subgroup analyses, no differential effect was found in mood disorders, anxiety disorders, or psychosis/developmental disorders. In the case of other disorders that are not mood disorders, anxiety disorders, or psychosis/developmental disorders, the differential magnitude was large (-8.5%), even though it was not statistically significant (95% CI = -17.0, 0.1; P = 0.053). No differential effect due to the 2009 USPSTF depression screening recommendation was found in the cases of antidepressant prescription patterns (P = 0.680) and the utilization of psychiatric services (P = 0.679).

TABLE 4.

Adjusted Proportion of Selected Outcomes Among Older Adults in Office-Based Outpatient Primary Care Settings by Depression Screening, NAMCS 2006-2012

With Depression Screening, % Without Depression Screening, % Difference, % Difference-in-Differences, %
Pre-2009 (2006-2008) Post-2009 (2010-2012) Pre-2009 (2006-2008) Post-2009 (2010-2012) Pre-2009 (2006-2008) Post-2009 (2010-2012) Coefficient 95% CI P Value
Mental disorder diagnosis
  Any mental disorder 40.2 26.6 5.5 6.4 -34.7 -20.2 -14.4 -28.2 -0.6 0.040
  Mood disorder 26.9 20.1 2.0 2.0 -24.9 -18.0 -6.9 -20.9 7.1 0.334
  Anxiety disorder 8.2 4.7 1.7 1.9 -6.5 -2.8 -3.7 -10.9 3.5 0.313
  Psychosis/developmental disorder 6.0 1.2 1.2 1.8 -4.8 0.6 -5.4 -12.2 1.4 0.121
  Other 12.5 4.6 2.9 3.5 -9.6 -1.1 -8.5 -17.0 0.1 0.053
Comorbid mental disorders
  2 or more 0.9 1.7 0.1 0.2 -0.8 -1.5 0.7 -18.7 3.3 0.592
Antidepressant prescription
  Any antidepressant 28.2 25.8 10.9 10.8 -17.3 -15.0 -2.3 -13.1 8.5 0.680
  Potentially inappropriate antidepressant 0.5 -0.1 1.6 1.4 1.1 1.6 -0.5 -1.8 0.8 0.463
Psychiatric service use
  Psychotherapy and mental health counseling 9.1 10.9 0.4 0.4 -8.7 -10.4 1.8 -6.6 10.1 0.679
Sample size
  Unweighted sample 323 15,273 15,596
  Weighted visits 1,748,058 91,841,986 93,590,045

Note: Controlled for all other covariates.

CI = confidence interval; NAMCS = National Ambulatory Medical Care Survey.

Discussion

This is the first population-based observational study to examine the effects of the 2009 USPSTF depression screening recommendation in office-based outpatient visits made by older adults. Overall, the diagnosis of any mental disorder had a differential effect (-14.4%; 95% CI = -28.2, -0.6). While there is no clear explanation from this population-based observational data, there are 2 plausible reasons for this phenomenon. One would be that primary care physicians have different medical practice patterns compared to psychiatrists, who are specialized in mental health diagnoses and psychopharmacological interventions. The other possibility may be patient perceptions. Older patients, unlike their younger counterparts, may still be sensitive to stigma related to mental health issues. Besides these, there might be unobserved confounders that can explain this finding. Future research, however, is needed to better understand such medical practice patterns and how they may affect mental health outcomes of older patients.

No differential effect was found in terms of overall and potentially inappropriate antidepressant prescribing patterns and provision of nonpharmacological psychiatric services. First, these findings are consistent with previous studies, which show no or uncertain improvement of depression-related outcomes due to depression screening.27,28 This may be due to a broadly defined guideline in the USPSTF depression screening recommendation statements, which did not specify which depression screening instruments should be used in primary care practices. Other possible reasons include acceptability or credibility issues regarding depression screening among patients and health care providers (e.g., uncertainty with respect to the evidence).

One of the important clinical implications is the quality of current depression screening tools in primary care practice. For example, false-positive rates of existing screening tools are relatively high,29 such that primary care physicians do not order follow-up tests for mental health diagnoses other than depression. Alternatively, primary care physicians may not be well informed about procedures when several screening tools are available with little evidence of such tools.29 According to the American Geriatrics Society, the Patient Health Questionnaire-2 is recommended as an initial depression screening tool and a 15-item Geriatric Depression Scale as a follow-up test for older adults.30 In other words, screening tools are meant as a way to alert primary care physicians to the possible presence of a mental health condition and should be followed by more assessments. However, using nationally representative secondary data, our study is limited to investigating the details of primary care physician practice patterns for utilizing depression screening. Future research is needed to better understand the adherence of primary care physicians to the depression screening guideline and its related outcomes.

A recent study found that depression screening was associated with a decreased rate of potentially inappropriate antidepressant prescriptions in older adults using the same data source.11 Based on our findings and their rationale, it seems that depression screening is still useful, as the provision of depression screening was associated with a decreased rate of potentially inappropriate antidepressant prescriptions in visits made by older adults11; this phenomenon, however, was not likely due to recent USPSTF guideline implementation. Future research is still needed to characterize causal pathways for depression screening, diagnoses, and treatments of depression and other psychiatric disorders to further guide the utility of depression screening guidelines for health care providers in primary care settings.

Limitations

Our study has several limitations. First, the 2009 USPSTF depression screening recommendation distinguishes that the screening service use is recommended if and only if staff-assisted depression care supports are in place (i.e., grade B recommendation). Otherwise, the screening service may be provided depending on individual circumstances (i.e., grade C recommendation).5 Because the NAMCS does not collect information regarding staff-assisted depression care supports, careful interpretations of the study findings are needed. Currently, no publicly available national data allow us to collect such information. In addition, detailed depression screening strategies are not known in the NAMCS. Future research should address such issues (e.g., types and intensity of depression screening) when examining the roles of depression screening on diagnosing and treating depression and other mental health conditions.

Second, due to the nature of the survey design, the NAMCS only captures up to 3 diagnoses in a sampled visit, and diagnoses from any previous visit are not known. In addition, problems with transferring clinical information across different health care providers or sites may have contributed to missing psychiatric diagnoses in the NAMCS data, as documented elsewhere.31 Thus, the NAMCS may have underreported the rates of depression screening, mental health diagnosis, and/or treatment. These limitations should be carefully considered when interpreting our findings.

Strengths of the study include the use of a quasi-experimental DID method to evaluate the effect of the 2009 depression screening recommendation at the national level.25 This study adds value to existing literature because no population-based observational study was conducted to support previous studies, as they solely used a randomized controlled trial (RCT) approach.28,32,33 While RCT studies focus on efficacy of depression screening in ideal settings, population-based observational studies, such as our study, can evaluate the effectiveness of depression screening with greater validity in real-world settings. For this reason, our study can inform clinical implications of practicing depression screening in primary care settings at the national level.

Conclusions

This study provides evidence that the 2009 USPSTF depression screening recommendation was associated with a decreased rate of diagnosing any mental disorder but had no effect on antidepressant prescribing patterns and provision of nonpharmacological psychiatric services in office-based outpatient visits made by older adults. In 2016, the USPSTF disseminated its updated recommendation, which remains unchanged that a grade B recommendation is given regardless of staff-assisted depression care supports status.34,35 Such a recommendation is notably different from the Canadian Task Force on Preventive Health Care, which recently recommended against depression screening in 2013 because of the evidence that no RCT study supports the effectiveness of depression screening on depression outcomes in primary care settings.33 Since evidence of efficacy and effectiveness of depression screening remains mixed, additional population-based observational research with rigorous designs is needed in the near future to strengthen and support current USPSTF depression screening recommendation statements in the United States.

REFERENCES

  • 1.World Health Organization. Depression: fact sheet. 2017. Available at: http://www.who.int/mediacentre/factsheets/fs369/en/. Accessed June 1, 2018.
  • 2.Wiese BS. Geriatric depression: the use of antidepressants in the elderly. Br Columbia Med J. 2011;53(7):341-47. [Google Scholar]
  • 3.Palmer SC, Coyne JC.. Screening for depression in medical care: pitfalls, alternatives, and revised priorities. J Psychosom Res. 2003;54(4):279-87. [DOI] [PubMed] [Google Scholar]
  • 4.U.S. Preventive Services Task Force. Screening for depression: recommendations and rationale. Ann Intern Med. 2002;136(10):760-64. [DOI] [PubMed] [Google Scholar]
  • 5.U.S. Preventive Services Task Force. Screening for depression in adults: U.S. preventive services task force recommendation statement. Ann Intern Med. 2009;151(11):784-92. [DOI] [PubMed] [Google Scholar]
  • 6.U.S. Preventive Services Task Force. Depression in adults: screening. 2015. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/UpdateSummaryDraft/depression-in-adults-screening1?ds= 1&s=depression. Accessed June 2, 2018.
  • 7.Mojtabai R. Does depression screening have an effect on the diagnosis and treatment of mood disorders in general medical settings?: an instrumental variable analysis of the National Ambulatory Medical Care Survey. Med Care Res Rev. 2011;68(4):462-89. [DOI] [PubMed] [Google Scholar]
  • 8.Rhee TG, Schommer JC, Capistrant BD, Hadsall RL, Uden DL.. Potentially inappropriate antidepressant prescriptions among older adults in office-based outpatient settings: national trends from 2002 to 2012. Adm Policy Ment Health. 2018;45(2):224-35. [DOI] [PubMed] [Google Scholar]
  • 9.Block LD, Jarlenski MP, Wu AW, Bennett WL.. Mammography use among women ages 40-49 after the 2009 U.S. Preventive Services Task Force recommendation. J Gen Intern Med. 2013;28(11):1447-53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Filice CE, Green JC, Rosenthal MS, Ross JS.. Pediatric screening urinalysis: a difference-in-differences analysis of how a 2007 change in guidelines impacted use. BMC Pediatr. 2014;14:260. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Rhee TG, Capistrant BD, Schommer JC, Hadsall RS, Uden DL.. Effects of depression screening on diagnosing and treating mood disorders among older adults in office-based primary care outpatient settings: an instrumental variable analysis. Prev Med. 2017;100:101-11. [DOI] [PubMed] [Google Scholar]
  • 12.National Center for Health Statistics. About the ambulatory health care surveys. 2017. Available at: http://www.cdc.gov/nchs/ahcd/about_ahcd.htm. Accessed June 2, 2018.
  • 13.National Center for Health Statistics. Ambulatory health care data: questionnaires, datasets, and related documentation. 2017. Available at: http://www.cdc.gov/nchs/ahcd/ahcd_questionnaires.htm. Accessed June 2, 2018.
  • 14.Olfson M, Blanco C, Wang S, Laje G, Correll CU.. National trends in the mental health care of children, adolescents, and adults by office-based physicians. JAMA Psychiatry. 2014;71(1):81-90. [DOI] [PubMed] [Google Scholar]
  • 15.American Society of Health-System Pharmacists. American Hospital Formulary Service (AHFS) Drug Information. Bethesda, MD: American Society of Health-System Pharmacists; 2015. [Google Scholar]
  • 16.Wolters Kluwer. Clinical drug information. Facts and comparisons. 2015. Available at: http://www.wolterskluwercdi.com/. Accessed June 2, 2018.
  • 17.Maust DT, Oslin DW, Marcus SC.. Effect of age on the profile of psychotropic users: results from the 2010 National Ambulatory Medical Care Survey. J Am Geriatr Soc. 2014;62(2):358-64. [DOI] [PubMed] [Google Scholar]
  • 18.Olfson M, Marcus SC.. National patterns in antidepressant medication treatment. Arch Gen Psychiatry. 2009;66(8):848-56. [DOI] [PubMed] [Google Scholar]
  • 19.American Geriatrics Society Beers Criteria Update Expert Panel. American Geriatrics Society updated Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2012;60(4):616-31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.American Geriatrics Society Beers Criteria Update Expert Panel. American Geriatrics Society 2015 updated Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2015;63(11):2227-46. [DOI] [PubMed] [Google Scholar]
  • 21.National Center for Health Statistics. 2012 NAMCS micro-data file documentation. Available at: ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NAMCS/doc2012.pdf. Accessed June 7, 2018.
  • 22.Rhee TG, Choi YC, Ouellet GM, Ross JS.. National prescribing trends for high-risk anticholinergic medications in older adults. J Am Geriatr Soc. March 26, 2018. [E-pub ahead of print]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Rhee TG. Continuing versus new antidepressant use in older adults: U.S. prescribing trends from 2006 to 2015. Eur Geriatr Med. In press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Rhee TG, Mohamed S, Rosenheck RA.. Antipsychotic prescriptions among adults with major depressive disorder in office-based outpatient settings: national trends from 2006 to 2015. J Clin Psychiatry. 2018;79(2):17m11970. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Mander A, Clayton D.. HOTDECK: Stata Module to Impute Missing Values Using the Hotdeck Method. Boston College Department of Economics. 2007. [Google Scholar]
  • 26.Khandker SR, Koolwal GB, Samad HA.. Handbook on Impact Evaluation: Quantitative Methods and Practices. Washington, DC: World Bank; 2010. [Google Scholar]
  • 27.Thombs BD, Ziegelstein RC.. Does depression screening improve depression outcomes in primary care? BMJ. 2014;348:g1253. [DOI] [PubMed] [Google Scholar]
  • 28.Thombs BD, Ziegelstein RC, Roseman M, Kloda LA, Ioannidis JP.. There are no randomized controlled trials that support the United States Preventive Services Task Force Guideline on screening for depression in primary care: a systematic review. BMC Med. 2014;12:13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Bland RC, Streiner DL.. Why screening for depression in primary care is impractical. CMAJ. 2013;185(9):753-54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Maurer DM. Screening for depression. Am Fam Physician. 2012;85(2):139-44. [PubMed] [Google Scholar]
  • 31.Mojtabai R, Olfson M.. Proportion of antidepressants prescribed without a psychiatric diagnosis is growing. Health Aff (Millwood). 2011;30(8):1434-42. [DOI] [PubMed] [Google Scholar]
  • 32.O’Connor EA, Whitlock EP, Beil TL, Gaynes BN.. Screening for depression in adult patients in primary care settings: a systematic evidence review. Ann Intern Med. 2009;151(11):793-803. [DOI] [PubMed] [Google Scholar]
  • 33.Thombs BD, Ziegelstein RC.. Depression screening in primary care: why the Canadian task force on preventive health care did the right thing. Can J Psychiatry. 2013;58(12):692-96. [DOI] [PubMed] [Google Scholar]
  • 34.Siu AL, US Preventive Services Task Force (USPSTF), Bibbins-Domingo K, et al. Screening for depression in adults: US Preventive Services Task Force recommendation statement. JAMA. 2016;315(4):380-87. [DOI] [PubMed] [Google Scholar]
  • 35.U.S. Preventive Services Task Force. Final recommendation statement: depression in adults—screening. 2016. Available at: https://www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/depression-in-adults-screening1. Accessed June 2, 2018.

Articles from Journal of Managed Care & Specialty Pharmacy are provided here courtesy of Academy of Managed Care Pharmacy

RESOURCES