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The American Journal of Managed Care August 2010
Clinical and Economic Outcomes After Introduction of Drug-Eluting Stents
Charanjit S. Rihal, MD, MBA; James L. Ryan, MHA; Mandeep Singh, MBBS; Ryan J. Lennon, MS; John F. Bresnahan, MD; Juliette T. Liesinger, BA; Bernard J. Gersh, MBChB, DPhil; Henry H. Ting, MD, MBA; David R. Holmes, Jr, MD; and Kirsten Hall Long, PhD
Antihypertensive Medication Adherence and Subsequent Healthcare Utilization and Costs
Donald G. Pittman, PharmD; Zhuliang Tao, MPH; William Chen, PhD; and Glen D. Stettin, MD
Statin Therapy for Elevated hsCRP: What Are the Public Health Implications?
Paul M. Ridker, MD
Statin Therapy for Elevated hsCRP: More Evidence Is Needed
Ogochukwu C. Molokwu, PharmD, MScMed
Opening and Continuing the Discussion on Influenza Vaccination Timing
Kellie J. Ryan, MPH Matthew D. Rousculp, PhD, MPH. Reply by Bruce Y. Lee, MD, MBA Julie H. Y. Tai, MD Rachel R. Bailey, MPH
Cost Sharing, Adherence, and Health Outcomes in Patients With Diabetes
Teresa B. Gibson, PhD; Xue Song, PhD; Berhanu Alemayehu, DrPH; Sara S. Wang, PhD; Jessica L. Waddell, MPH; Jonathan R. Bouchard, MS, RPh; and Felicia Forma, BSc
Relationship Between Quality Improvement Processes and Clinical Performance
Cheryl L. Damberg, PhD; Stephen M. Shortell, PhD, MPH, MBA; Kristiana Raube, PhD, MPH; Robin R. Gillies, PhD; Diane Rittenhouse, MD, MPH; Rodney K. McCurdy, MHA; Lawrence P. Casalino, MD, PhD; and John Adams, PhD
Value and the Medical Home: Effects of Transformed Primary Care
Richard J. Gilfillan, MD; Janet Tomcavage, RN, MSN; Meredith B. Rosenthal, PhD; Duane E. Davis, MD; Jove Graham, PhD; Jason A. Roy, PhD; Steven B. Pierdon, MD; Frederick J. Bloom Jr, MD, MMM; Thomas R. Graf, MD; Roy Goldman, PhD, FSA; Karena M. Weikel, BA; Bruce H. Hamory, MD; Ronald A. Paulus, MD, MBA; and Glenn D. Steele Jr, MD, PhD
Insomnia Risks and Costs: Health, Safety, and Quality of Life
Mark R. Rosekind, PhD; and Kevin B. Gregory, BS
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Effect of Inadequate Response to Treatment in Patients With Depression
Russell L. Knoth, PhD; Susan C. Bolge, PhD; Edward Kim, MD, MBA; and Quynh-Van Tran, PharmD
Employees' Willingness to Pay to Prevent Influenza
Stephen S. Johnston, MA; Matthew D. Rousculp, PhD, MPH; Liisa A. Palmer, PhD; Bong-Chul Chu, PhD; Parthiv J. Mahadevia, MD, MPH; and Kristin L. Nichol, MD, MPH, MBA
Anticonvulsant Use After Formulary Status Change for Brand-Name Second-Generation Anticonvulsants
Hemal Patel, PharmD, MBA; Diana C. Toe, PharmD; Shawn Burke, RPh; and Rafia S. Rasu, PhD

Effect of Inadequate Response to Treatment in Patients With Depression

Russell L. Knoth, PhD; Susan C. Bolge, PhD; Edward Kim, MD, MBA; and Quynh-Van Tran, PharmD

Patients with inadequate response to depression treatment used increased resources, were less likely to be employed, and had more presenteeism than those with treatment response.

Objectives: To assess the effects of inadequate response to antidepressant treatment on healthcare resource utilization and on work productivity in patients diagnosed as having major depressive disorder (MDD).


Study Design: This study used data from the 2006 US National Health and Wellness Survey, a cross-sectional survey of adults 18 years and older.


Methods: Patients who self-reported a confirmed diagnosis of depression and were currently taking antidepressant medication were included in the analyses. Adequacy of antidepressant treatment response was determined from responses to the mental health domain of the 8-Item Short Form Health Survey (SF-8). Logistic regression analyses adjusted for demographics, comorbidity, and component scores on the SF-8 were used to determine the associations between inadequacy of treatment response and health outcomes.


Results: Of 5988 patients who met the inclusion criteria for the study, 30.9% were classified as antidepressant treatment responders, 31.2% were partial responders, and 37.9% were nonresponders. Partial response and nonresponse to treatment were associated with greater likelihood of emergency department utilization (odds ratios [ORs], 1.26 and 1.54, respectively; P <.01 for both) and hospitalization (OR, 1.23; P = .05 and OR, 1.39; P <.01, respectively). Similarly, partial response and nonresponse were associated with lower likelihood of current employment (OR, 0.83; P = .01 and OR, 0.63; P <.01, respectively) and with greater likelihood of work productivity loss among the employed (ORs, 1.42 and 1.99, respectively; P <.01 for both).


Conclusions: Patients with MDD who failed to respond to antidepressant treatment as evidenced by poor self-reported mental health status used more healthcare resources, were less likely to be employed, and had more work productivity loss than those who responded to antidepressant therapy.


(Am J Manag Care. 2010;16(8):e188-e196)

Patients with inadequate response to depression treatment used increased healthcare resources and had more presenteeism than those with treatment response.


  • For patients diagnosed as having major depressive disorder (MDD) and treated with antidepressant medication, inadequate response to therapy was associated with healthcare resource utilization that included emergency department and inpatient services.
  • Inadequate response to antidepressants was associated with lower likelihood of employment and with greater likelihood of work productivity loss among the employed.
  • Because inadequate treatment had cost consequences for health plans and for employers, encouraging improvements in the adequacy of treatment for patients with MDD should be of interest to both parties.
Major depressive disorder (MDD) is a serious mental illness characterized by 1 or more major depressive episodes.1 There are several therapies available to treat MDD.2 Initial first-line therapies include the following 3 classes of medications: selective serotonin reuptake inhibitors, serotonin and norepinephrine reuptake inhibitors, and a norepinephrine-dopamine reuptake inhibitor. Older medications such as tricyclic antidepressants and monoamine oxidase inhibitors are typically used only if the patient has not responded to the first-line therapies.3 Treatment response is usually defined as (1) at least 50% improvement on a depression rating scale, typically the Hamilton Rating Scale for Depression, or (2) “much improved” or “very much improved” on the Clinical Global Impressions–Severity of Illness and Clinical Global Impressions–Improvement scales.4 The ultimate goal of therapy is remission, whereby there is an absence of depressive symptoms.3 Between response and nonresponse lies partial response, which is often defined as (1) less than 50% but at least 25% improvement on a depression scale, or (2) “minimal improvement” on the Clinical Global Impressions–Improvement scale.4,5

Unfortunately, the treatment of MDD continues to pose a challenge, and 50% to 70% of patients do not fulfill conventional remission criteria following treatment with at least 1 antidepressant of adequate dosage and duration in clinical trials.4,6-8 Determining treatment resistance prevalence is difficult because definitions vary, but most researchers agree that a patient is considered to have treatment-resistant or treatment-refractory depression (TRD) when at least 2 trials of antidepressants from different pharmacologic classes fail to result in remission.9 Management of TRD involves evaluating the patient for possible conditions that may affect treatment response and using 1 of the following 4 pharmacologic options for increasing efficacy: optimizing, augmenting, combining, and switching.9 The Sequenced Treatment Alternatives to Relieve Depression study,10 a large-scale clinical trial, found that no second-generation antidepressant was more effective than another as a second-line treatment.

In 2000, the total economic burden of treating depression in the United States was $83.1 billion, with workplace costs (including missed workdays and lack of productivity because of illness) accounting for 62% of the total economic burden; other economic burdens included $26.1 billion (31% ofthe total) for treatment costs and $5.4 billion (7%) for suicide-related costs.11 Using medical claims data from 1995 to 2000, Crown et al12 estimated that patients with TRD were at least twice as likely to be hospitalized (for general medical and depression-related conditions) and had at least 12% more outpatient visits compared with patients with depression that did not meet the TRD criteria.

Studies examining depression and lost productivity have typically examined direct costs or indirect costs, and most have not examined costs by treatment response or addressed costs related to presenteeism (impairment while working), absenteeism (missed work), or overall work productivity loss (combination of absenteeism and presenteeism). Our goal was to focus on patients diagnosed as having MDD and currently being treated to determine the consequences of inadequate response to antidepressant treatment. Specifically, the objective was to provide a more complete cost picture using patient-reported outcomes to assess the effects of inadequate response to antidepressant treatment on healthcare resource utilization, work productivity, and activity loss in a large nationwide sample of patients diagnosed as having MDD.


Study Design

This was a cross-sectional study. Data were taken from the 2006 US National Health and Wellness Survey (NHWS), an annual cross-sectional study of approximately 63,000 adults 18 years and older. Potential participants were contacted by the Lightspeed Research (LSR) (Basking Ridge, NJ) Internet panel. Members of the panel were recruited through opt-in e-mail, coregistration with LSR partners, e-newsletter campaigns, banner placements, and internal and external affiliate networks. All potential panelists had to register with the panel through a unique e-mail address and password and had to complete an in-depth demographic registration profile. In total, 1,494,260 members of the LSR panel were contacted to complete the NHWS survey in 2006, and 62,833 responded (4.2% response rate). A stratified random sample procedure was implemented to ensure that the demographic distribution of the responders was equivalent to that of the total US population. Comparisons between the NHWS survey and other national databases have been highlighted elsewhere.13 The 2006 US NHWS consisted of information on demographics, healthcare attitudes and behaviors, disease status, and outcomes. All data were self-reported directly by patients through self-administered Internet-based questionnaires. The NHWS sampling frame consisted of quotas based on sex, age, and race/ethnicity to reflect the demographic population of the US adult population; in addition, the NHWS is geographically representative of the entire United States. The NHWS questionnaire and study protocol were approved by Essex Institutional Review Board, Inc (Lebanon, NJ). Informed consent was obtained from respondents before entering the survey.

Study Sample

The study sample consisted of participants in the 2006 US NHWS who met the following study criteria: (1) received a diagnosis of depression from a health professional (“Has your depression been diagnosed by a health professional? Yes or no.”) and (2) currently taking an antidepressant medication (“Please indicate which of the following prescription medications you currently use to treat your depression. Please select all that apply.”) Respondents who self-reported a diagnosis of depression and current use of antidepressant medication were included in the analyses. Respondents who self-reported a diagnosis of bipolar disorder or current use of antipsychotic medication were excluded from the analyses.

The study sample was then stratified based on self-reported current mental health status using the mental health domain of the 8-Item Short Form Health Survey (SF-8). The SF-8 consists of 8 questions that correspond directly to 8 subscales of the 36-Item Short Form Health Survey. These 8 subscales are physical functioning, role limitations due to physical health problems, bodily pain, general health, vitality, social functioning, role limitations due to emotional problems, and mental health. A mental health component summary score and a physical component summary score are derived from the SF-8. For both summary measures, the mean (SD) normative score for the US population is 50 (10), with higher scores indicating better physical or mental well-being.14

Sample stratification was based on participant response to the following question on the SF-8: “During the past 4 weeks, how much have you been bothered by emotional  problems(such as feeling anxious, depressed, or irritable?”). Response options included “not at all,” “slightly,” “moderately,” “quite a lot,” or “extremely.” Respondents were stratified into 1 of the following 3 groups: treatment responders (defined by a response of “not at all” or “slightly” and used as the reference group in regression analyses), partial responders (defined by a response of “moderately”), or nonresponders (defined by a response of “quite a lot” or “extremely”).

Study Measures

Patient Demographics. Patient demographics included sex, age as a continuous variable, race/ethnicity (white vs nonwhite), marital status (married or living with partner vs not), and education (having a college degree vs no college degree).

Comorbid Conditions. Physical comorbidity was assessed by attempting to mimic the Charlson Comorbidity Index (CCI).15 The CCI is a measure of comorbidity burden that is calculated by weighting the presence of comorbidities by their severity. In this study, the presence of congestive heart failure, myocardial infarction, peripheral vascular disease, cerebrovascular disease, chronic obstructive pulmonary disease, connective tissue disease, ulcer disease, mild liver disease, diabetes mellitus, cancer, and human immunodeficiency virus was each weighted by its severity as outlined by Charlson et al15 and summed. The CCI was considered a continuous variable. Additional psychiatric comorbidity was assessed. Respondents were classified as having a psychiatric comorbid condition if any of the following conditions were experienced in the past 12 months: anxiety, generalized anxiety disorder, obsessive-compulsive disorder, panic disorder, phobias, post-traumatic stress disorder, and social anxiety disorder. In analysis, psychiatric condition was dummy coded as yes (1 point) or no (0 points).

Healthcare Resource Utilization. Healthcare resource utilization was assessed for the previous 6 months by obtaining information on emergency department (ED) services and hospitalizations. Patients were asked the following questions: “How many times have you been to the emergency room for your own medical condition in the past 6 months?” and “What is the total number of days you were hospitalized for your own medical condition in the past 6 months?”

Employment Status. Patients’ employment status was determined by asking: “What is your employment status?” Responses included “employed full-time,” “employed part-time,” “self-employed,” “not employed but looking for work,” “not employed and not looking for work,” “retired,” “on disability,” “student,” or “homemaker.” Patients reporting “employed full-time,” “employed part-time,” or “self-employed” were considered employed, while all others were considered not employed.

Absenteeism and Presenteeism Among Employed Patients. As part of the NHWS, indirect costs were assessed using the general health version of the Work Productivity and Activity Impairment (WPAI) questionnaire.16 The WPAI assesses absenteeism (the percentage of work time missed because of one’s health in the past 7 days), presenteeism (the percentage of impairment experienced while at work in the past 7 days because of one’s health), overall work productivity loss (an overall impairment estimate that is a combination of absenteeism and presenteeism), and activity impairment (the percentage of impairment in daily activities because of one’s health in the past 7 days). All employed respondents provided data for absenteeism, presenteeism, and overall work productivity loss (as those not employed could not answer questions about hours worked or hours missed from work). All respondents provided data for activity impairment.

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