Integration models into primary health care the example of late life depression
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Integration Models into Primary Health Care: the Example of Late-life Depression. Benoit H. Mulsant, MD, MS, FRCPC Professor and Vice-Chair Department of Psychiatry University of Toronto Physician in Chief Centre for Addiction and Mental Health. L earning Objectives.

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Integration models into primary health care the example of late life depression

Integration Models into Primary Health Care: the Example of Late-life Depression

Benoit H. Mulsant, MD, MS, FRCPC

Professor and Vice-Chair

Department of Psychiatry

University of Toronto

Physician in Chief

Centre for Addiction and Mental Health


Integration models into primary health care the example of late life depression

Learning Objectives

  • At the conclusion of this session, the participants should be able to:

  • Assess the evidence supporting the efficacy of antidepressant medications in the treatment of late-life depression.

  • Assess the risks of antidepressant medications used in the treatment of late-life depression.

  • Maximize the effectiveness of pharmacotherapy when treating a patient with late-life depression in the primary care sector.


Treating late life depression fighting therapeutic nihilism

Treating Late-Life DepressionFighting therapeutic nihilism

One of the few medical conditions in which treatment can make a rapid and dramatic difference in an elderly patient’s level of function


Integration models into primary health care the example of late life depression

Pinquart, Duberstein, & Lyness

Treatments for later-life depressive conditions: a meta-analytic comparison of pharmacotherapy and psychotherapy

Am J Psych, 163(9):1493-501, 2006

Meta-analysis of 62 placebo-controlled studies (N = 3,921)

Favorable outcomes: Drugs: 66% vs. Placebo: 31%

“Available treatments for depression work,

with effect sizes that are moderate to large…”


Integration models into primary health care the example of late life depression

Outcome of Usual Care for Depressed Patients

Treated by Well-Trained Psychiatrists

  • Six psychiatric clinics in Westchester County (USA)

  • 165 patients with major depression

  • 65% received an antidepressant

  • 45% received an adequate dose for 4+ weeks (academic vs. non-academic sites: 53% vs. 36%, p =0.04)

  • Remission rate after 3 months: 30%

  • Adequate treatment: 3 fold higher likelihood of remission (OR = 3.2; p = 0.04)

Meyers et al (2002) Archives Gen Psych


Treating late life depression closing the efficacy effectiveness gap

Treating Late-Life Depression Closing the Efficacy-Effectiveness Gap

  • Systematic vs. personalized approach

  • Selecting a class and a specific agent

  • Optimal dose

  • Optimal trial duration

  • Management of treatment resistance


Integration models into primary health care the example of late life depression

Outline

  • 1. Argument for a systematic approach (“algorithm”, “clinical pathways”, “stepped care”) vs. an individualized approach (“usual care”)

  • Defining one’s algorithm for late-life depression:

    • What is your first-line intervention?

    • Your second-line intervention?

    • Your third-line intervention?

    • How long should each step lasts?

    • When do you switch? When do you augment?


Integration models into primary health care the example of late life depression

Systematic Approach

Based on best evidence or guidelines

Clinical experience based on large number of patients

Keeping the course: the clinician is protected against personal biases, pressures form the patient or family

Focus is on the patient

Usual Care

Based on fad “du jour”

Little cumulative experience due to small numbers of patients receiving many different medications

Ill-advised or ill-timed changes in treatment

Focus is on the treatment (making decisions is exhausting)

A Tale of Two Approaches


Integration models into primary health care the example of late life depression

Systematic Approach (algorithm, stepped care) vs. Individualized Approach (usual care)

  • Two Examples of Randomized Comparisons for Stepped-Care for Late-Life Depression:

    • IMPACT (Unutzer et al, JAMA, 2002)

    • PROSPECT (Bruce et al, JAMA, 2004)


Prospect a case study

PROSPECT: A Case Study

Patient & Family

Psycho-Education

Physician Education

Identification of

Diagnosis

&

DEPRESSION

SPECIALIST

TREATMENT

ALGORITHM


Prospect treatment algorithm

PROSPECT: Treatment Algorithm


Main features of treatment algorithm

Main Features of Treatment Algorithm

  • Based on evidence and practice guideline

  • Modified for the primary care office

  • Use of psychopharmacological and psychosocial interventions

  • Psychiatric consultation is offered in complex cases

  • Covers acute and continuation/maintenance treatment

  • Covers a wide range of syndromes ranging from mild to severe depression


Prospect algorithm 1

PROSPECT Algorithm (1)


Prospect algorithm 2

PROSPECT Algorithm (2)


Prospect results

PROSPECT: Results


Prospect cumulative probability of remission

PROSPECT: Cumulative Probability of Remission

All comparisons: p < 0.001Alexopoulos et al (2005) Am J Psych


Prospect probability of being treated

PROSPECT: Probability of Being Treated

All comparisons: p < 0.001

Alexopoulos et al (2009) Am J Psych


Psychoeducation is essential for successful antidepressant treatment

Psychoeducation is Essential for Successful Antidepressant Treatment

  • Address the patient’s personal illness model

  • It takes 2-6 weeks to show beneficial effects

  • Side effects occur right away

  • Patients must be encouraged and supported to be take dose regularly as prescribed

  • Reassure that side effects usually wear off

  • Need for continuation and maintenance treatment

Mulsant et al (2003) CNS Spectrum; 8: 27-34


Response rates in 13 studies of treatment resistant late life depression

Response Rates in 13 Studies of Treatment-Resistant Late-Life Depression

Cooper et al (2011) Am J Psych; 168: 681-688


Integration models into primary health care the example of late life depression

Outline

  • 1. Argument for a systematic approach (“algorithm”, “clinical pathways”, “stepped care”) vs. an individualized approach (“usual care”)

  • Defining one’s algorithm for late-life depression:

    • What is your first-line intervention?

    • Your second-line intervention?

    • Your third-line intervention?

    • How long should each step lasts?

    • When do you switch? When do you augment?


Integration models into primary health care the example of late life depression

Possible Criteria for Choosing an Antidepressants for an Older Adult

Efficacy

Tolerability

Safety

Cost


Response rates in eight published randomized placebo controlled trials

Response Rates (%) in Eight Published Randomized Placebo-Controlled Trials

*

*

*

*

1. Tollefson et al (1995) Int Psychogeriatrics; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 –4. Roose et al (2004) Am J Psych; 161:2050-9– 5. Kasper et al (2005) Am J Geri Psych; 13:884-91 –

6. Schatzberg & Roose (2006) Am J Geri Psych; 14:361-70 – 7. Bose et al. (2008) Am J Geri Psych; 16:14-20 – 8. Raskin et al (2007) Am J Psychiatry; 164:900-9


Fluoxetine in the treatment of late life depression marked site variability in remission rates

Fluoxetine in the treatment of late-life depression Marked site variability in remission rates

Small et al (1996) Int J Geri Psych; 11:1089-95


Integration models into primary health care the example of late life depression

Citalopram in the treatment of depression in the very oldMarked site variability in response and remission rates

Roose et al (2004) Am J Psych; 161:2050-9


Integration models into primary health care the example of late life depression

Possible Criteria for Choosing an Antidepressants for an Older Adult

Efficacy

Tolerability

Safety

Cost


Discontinuation rates attributed to adverse effects in eight rpcts

Discontinuation Rates (%) Attributed to Adverse Effects in Eight RpCTs

*

*

*

*

*

1. Tollefson et al (1995) Int Psychogeriatr; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 –4. Roose et al (2004) Am J Psych; 161:2050-9– 5. Kasper et al (2005) Am J Geri Psych;13:884-91 –

6. Schatzberg & Roose (2006). Am J Geriatr Psychiatry; 14:361370 - 7. Bose et al. (2008) Am J Geriatr Psychiatry; 16:14-20 –

8. Raskin et al (2007) Am J Psychiatry; 164:900-9


Overall discontinuation rates in eight rpcts

Overall Discontinuation Rates (%) in Eight RpCTs

*

1. Tollefson et al (1995) Int Psychogeriatr; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 –4. Roose et al (2004) Am J Psych; 161:2050-9– 5. Kasper et al (2005) Am J Geri Psych;13:884-91 –

6. Schatzberg & Roose (2006). Am J Geri Psych; 14:361-70 -- 7. Bose et al. (2008) Am J Geri Psych; 16:14-20 – 8. Raskin et al (2007) Am J Psychiatry; 164:900-9


Integration models into primary health care the example of late life depression

What is new since 2001?

Role of newer antidepressants?

  • Escitalopram • Desvenlafaxine • Duloxetine

    Role of atypical antipsychotics?

  • Quetiapine XR •Aripiprazole

    New Safety Concerns

  • Venlafaxine • Citalopram & Escitalopram

  • Atypical antipsychotics


Response rates older vs newer medications

Response Rates (%): Older vs. Newer Medications

*

*

*

*

*

1. Tollefson et al (1995) Int Psychogeriatrics; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 – 5. Kasper et al (2005) Am J Geri Psych;13:884-91 – 7. Bose et al. (2008) Am J Geri Psych; 16:14-20 – 8. Raskin et al (2007) Am J Psych; 164:900-9 – 9. Katila et al (2012) Am J Geri Psych


Discontinuation rates attributed to adverse effects older vs newer medications

Discontinuation Rates Attributed to Adverse Effects: Older vs. Newer Medications

1. Tollefson et al (1995) Int Psychogeriatrics; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 – 5. Kasper et al (2005) Am J Geri Psych;13:884-91 – 7. Bose et al. (2008) Am J Geri Psych; 16:14-20 – 8. Raskin et al (2007) Am J Psych; 164:900-9 – 9. Katila et al (2012) Am J Geri Psych


Integration models into primary health care the example of late life depression

What is new since 2001?

Role of newer antidepressants?

  • Escitalopram • Desvenlafaxine • Duloxetine

    Role of atypical antipsychotics?

  • Quetiapine•Aripiprazole

    New Safety Concerns

  • Venlafaxine • Citalopram & Escitalopram

  • Atypical antipsychotics


Integration models into primary health care the example of late life depression

Atypical Antipsychotics and Risk of Sudden Cardiac Death Among Patients of All Age

Ray WA et al (2009) New England Journal of Medicine; 360:225-35


Integration models into primary health care the example of late life depression

What is new since 2001?

Role of newer antidepressants?

  • Escitalopram • Desvenlafaxine • Duloxetine

    Role of atypical antipsychotics?

  • Quetiapine•Aripiprazole

    New Safety Concerns

  • Venlafaxine • Citalopram & Escitalopram

  • Atypical antipsychotics


Antidepressants for the older adult potential safety concerns

Drug-drug interactions1

Hyponatremia2

Falls3,4

Hip fractures5,6

GI bleeds7

Cardiovascular effects,8,9

Cognitive impairment10,11,12

Suicide13

Bone metabolism14, 15

Antidepressants for the Older AdultPotential Safety Concerns

1. Mulsant & Pollock, BG (2004). American Psychiatric Publishing Textbook of Geriatric Psychiatry, 3rd Edition – 2. Fabian et al (2004) Arch Int Med; 164:327-32 – 3. Joo et al (2002) J Clin Psych; 63:936-41 – 4. Thapa et al (1998) NEJM; 339:875-82 – 5. Liu et al (1998) Lancet;351:1303-7 – 6. Richards et al (2007) Arch Int Med; 167:188-95 – 7. Yuan et al (2006) Am J Med; 119:719-27 – 8. Johnson et al (2006) Am J Geri Psych; 14:796-802 – 9. Oslin et al (2003) J Clin Psych; 64:875–882 – 10. Furlan et al (2001) Am J Geri Psych; 9:429-38 – 11. Ridout et al (2003) Hum Psychopharm; 18:261 – 12. Wingen et al (2005) J Clin Psych; 66:436-43 – 13. Jurlink et al (2006) Am J Psych;163:813-21 – 14. Diem et al (2007) Arch Intern Med; 167:1240-5 – 15: Richards et al (2007) Arch Intern Med 167:188–94


Integration models into primary health care the example of late life depression

Augmentation v. SwitchingTolerability and Safety

Discontinuation due to Adverse Events:

51% augmentation v. 8% switching

Falls:

42% augmentation v. 24% switching

Whyte et al (2004) J. Clin Psych; 65: 1634-1641


Conclusions late life depression

Conclusions: Late-Life Depression

  • Can be effectively treated

  • Success requires a systematic approach

  • Success requires persistence

  • DO NOT GIVE UP!


Questions and discussion

Questions and Discussion


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