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Adherence to Antidepressant Medications Among Health Plan Members Diagnosed with Major Depression. Ayse Akincigil, John R. Bowblis, Carrie Levin, James T. Walkup, Saira Jan, Stephen Crystal AcademyHealth 2006 Annual Research Meeting Monday, June 26

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adherence to antidepressant medications among health plan members diagnosed with major depression

Adherence to Antidepressant Medications Among Health Plan Members Diagnosed with Major Depression

Ayse Akincigil, John R. Bowblis, Carrie Levin,

James T. Walkup, Saira Jan, Stephen Crystal

AcademyHealth 2006 Annual Research Meeting

Monday, June 26

Supported in part through NIMH grant R01 MH60831, AHRQ grants U18 HS016097 and HS-01182, and a grant by Horizon BCBSNJ

background objectives
Background / Objectives

There is a large amount of evidence that antidepressants are effective in reducing symptoms of depression and preventing relapse; however, poor adherence to medication is a major obstacle to effective care.

We describe characteristics of patients at risk for low adherence, and implications for policy and practice.

methods
Methods
  • A retrospective, observational study of insurance claims.
  • A large insurance company in Northeast, serving three-million lives.
  • Data are constructed from insurance claims, between January 2003 and January 2005.
  • Pharmacy claims are used to construct the outcome measure -- refill persistence.
  • Medical claims are used to identify patients with a new episode of depression.
study population

Index prescription date

Prescription look back period

90 days

Medication window

30

14

Diagnosis look back period

120 days

Index episode start date

(Date of Depression Diagnosis)

Study Population
outcome measures
Outcome Measures

Index prescription date

Effective Acute Phase Treatment

114 days

Effective Continuation Phase Treatment

231 days

30

14

Index episode start date

demographic socio economic characteristics
Gender (67% female)

Age

18-25 (11%)

25-39 (32%)

40-49 (28%)

50-64 (26%)

65 or older (4%)

Demographic, Socio-Economic Characteristics
  • Median household income at the neighborhood (zip-code)
    • <50k (29%)
    • 50k-70k (42%)
    • >70k (29%)
comorbid conditions
Alcohol Abuse (5%)

Substance Abuse (8%)

Anxiety Disorder (28%)

Cancer (18%)

Number of Cardiovascular Risk Factors (18% suffer from one, 6% suffer from 2 or more)

Comorbid Conditions
care patterns for depression episode
Type of Provider on Initial Visit (49% were mental health professional, 51% were general medical care).

Initial antidepressant drug type (4% were on older generation drugs).

28% had a follow-up visit with a psychiatrist.

24% had a follow-up visit with another mental health provider (e.g., psychologists, social workers).

Care Patterns for Depression Episode
non adherence risk factors for 0 8 months continuation phase
Non-Adherence Risk Factors for 0-8 Months (Continuation Phase)
  • Males *
  • Younger age
  • Patients from low income neighborhoods
  • Comorbid substance abuse
  • Comorbid alcohol abuse
  • 2+ CVD

Protective Factors

  • F/U care from a psychiatrist
  • Number of medications other than psychotropics
summary
Summary
  • Adherence rates are low, problem worsens in continuation phase.
  • Males, younger, and living in lower income neighborhoods are particularly at risk.
  • No support to the scenario of “medication crowd-out” among users of multiple medications.
  • Presence of multiple cardiovascular risk factors may crowd out depression.
  • Depression care for those with comorbid substance abuse and alcohol abuse are further complicated due to adherence issues.
  • Having a follow up with a psychiatrist improves odds of adherence.
  • Those who had follow up visits with social workers or psychologists were equally likely to adhere, compared to those with no follow up.