Psychiatric Times.
No. 9
TREATMENT
Measurement-Based Care for the Treatment of Depression
Easy-to-Use Tools Help Improve Outcomes
By A. John Rush, MD and Madhukar H. Trivedi, MD |
August 30, 2009
Dr Rush is vice chair in the department of clinical sciences at the University of Texas Southwestern Medical Center at Dallas. Dr Trivedi is professor in the department of psychiatry at the University of Texas Southwestern Medical Center at Dallas.
Dr Rush is a consultant for Advanced Neuro-modulation Systems, AstraZeneca, Best Practice Project Management, Bristol-Myers Squibb/Otsuka, GlaxoSmithKline, Magellan Health Services, Merck & Company, Ono Pharma USA, Organon, Pamlab, and Trancept Pharmaceuticals. He is a consultant/speaker for Cyberonics, Forest Pharmaceuticals, and Pfizer. In addition, he receives research support from the National Institute of Mental Health and the Stanley Medical Research Institute.
When to use MBC
MBC includes structured diagnostic interviews, routine assessment of symptom severity and adverse effects at each visit, and a systematic approach to treatment revisions with guidance from algorithms (given the TMAP results). One might argue that when the diagnosis is extremely clear, a structured interview is not necessary. However, our collective experience and research suggests that without a systematic diagnostic approach, important comorbid conditions are often missed—and even the primary diagnosis may not be accurate.9 For example, without a consistent approach to the diagnostic history, bipolar disor-der may be misdiagnosed as unipolar depression.9,28
Symptom measurements entail minimal cost and have the obvious benefit of helping patients learn to manage their condition and to recognize and report relapse in a timely fashion. Thus, the benefits far outweigh the cost, if any. Biggs and associates16 found that a global rating by the clinician or patient was frequently imprecise (and for clinicians, simply wrong). Thus, we recommend symptom measurement as routine practice.
Measurement-based care provides specific and objective information on which to base clinical decisions and should therefore enhance quality of care and treatment outcomes.
Limitations of MBC
Some patients (eg, those who are psychotic, intoxicated, demented) cannot accurately self-report symptoms or may not fully recall prior illness (eg, depressed patients deny previous manic/hypomanic episodes). Clinician-completed ratings are needed in this setting. Reports by “significant others” are also essential to establishing the diagnosis. In our practices we now require all patients to bring a significant other to provide a detailed history. These issues affect the approach but do not obviate the need for MBC.
Presently, MBC focuses on symptom reduction as the primary outcome; of course, the ultimate aim of treatment is functional and symptomatic recovery. Thus, additional assessment of day-to-day function can be very useful; this assessment needs to be done every 3 to 4 months to determine whether a patient requires additional psychosocial/rehabilitative therapy. Many physicians believe that they are at least as accurate at symptom assessment and diagnosis as they would be with measurement tools. Yet we all practice under extreme time pressures and, therefore, by necessity spend less time in diagnostic and symptom assessment than in past decades.
Our personal experiences suggest that such tools as the MINI, QIDS, QIDS-SR16, the FIBSER, and algorithm guidance provide more accurate information without increasing (and, in fact, potentially decreasing) the time and effort needed to accomplish these goals. We suggest that others try these methods to see whether they help in daily practice. Our experience also strongly suggests that patients value the thoroughness of MBC. Most systems of care not only allow but also encourage some outcome assessment.
Conclusion
Measurement tools can help you establish the diagnosis, measure symptomatic outcomes and adverse effects, and inform treatment selection and management quickly and easily. Our experience in research trials and in our private practices indicates that MBC provides clinically critical information that otherwise is missing. Finally, the use of MBC is consonant with treatment approaches used in almost all other chronic medical diseases.
References
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2. Trivedi MH, Rush AJ, Gaynes BN, et al. Maximizing the adequacy of medication treatment in controlled trials and clinical practice: STAR*D measurement-based care.
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4. Spitzer RL, Williams JB, Gibbon M.
The structured Clinical Interview for DSM-III (SCID). New York: New York State Psychiatric Institute; 1986.
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The Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition (SCID-I/P). New York: Biometrics Research, New York State Psychiatric Institute; 2001.
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The Structured Clinical Interview for DSM-IV-TR (SCID-I): User’s Guide and Interview-Research Version. New York: New York Psychiatric Institute, Biometrics Research Department; 2001.
7. Lecrubier Y, Sheehan DV, Weiller E, et al. The MINI International Neuropsychiatric Interview (M.I.N.I.). A short diagnostic structured interview: reliability and validity according to the CIDI.
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8. Sheehan DV, Lecrubier Y, Sheehan KH, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for
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9. Ramirez Basco MV, Bostic JQ, Davies D, et al. Methods to improve diagnostic accuracy in a community mental health setting.
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10. Kashner TM, Rush AJ, Suris A, et al. Impact of structured clinical interviews on physicians’ practices in community mental health settings.
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11. Rush AJ, Crismon ML, Kashner TM, et al. Texas Medication Algorithm Project, phase 3 (TMAP-3): rationale and study design.
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12. Trivedi MH, Rush AJ, Crismon ML, et al. Clinical results for patients with major depressive disorder in the Texas Medication Algorithm Project.
Arch Gen Psychiatry. 2004;61:669-680.
13. Fava M, Rush AJ, Trivedi MH, et al. Background and rationale for the sequenced treatment alternatives to relieve depression (STAR*D) study.
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14. Rush AJ, Fava M, Wisniewski SR, et al. Sequenced treatment alternatives to relieve depression (STAR*D): rationale and design.
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15. Rush AJ, Kraemer HC, Sackeim HA, et al; ACNP Task Force. Report by the ACNP Task Force on response and remission in major depressive disorder.
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16. Biggs MM, Shores-Wilson K, Rush AJ, et al. A comparison of alternative assessments of depressive symptom severity: a pilot study.
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17. Hamilton M. A rating scale for depression.
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22. Zung WW. A self-rating depression scale.
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23. Rush AJ, Trivedi MH, Ibrahim HM, et al. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression.
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24. Rush AJ, Bernstein IH, Trivedi MH, et al. An evaluation of the quick inventory of depressive symptomatology and the hamilton rating scale for depression: a sequenced treatment alternatives to relieve depression trial report.
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25. Trivedi MH, Rush AJ, Ibrahim HM, et al. The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation.
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26. Kroenke K, Spitzer RL, Williams JB. The PHQ-9. Validity of a brief depression severity measure.
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27. Wisniewski SR, Rush AJ, Balasubramani GK, et al. Self-rated global measure of the frequency, intensity, and burden of side effects.
J Psychiatr Pract. 2006;12:71-79.
28. Sharma V, Khan M, Smith A. A closer look at treatment resistant depression: is it due to a bipolar diathesis?
J Affect Disord. 2005;84:251-257.
Evidence-Based References
Trivedi MH, Rush AJ, Crismon ML, et al. Clinical results for patients with major depressive disorder in the Texas Medication Algorithm Project. Arch Gen Psychiatry. 2004;61:669-680.
Trivedi MH, Rush AJ, Wisniewski SR, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163:28-40.
