As clinicians, we routinely make critical decisions for our patients with depression. Because of the uncertainty of factors that affect diagnosis and treatment, clinicians may find an objective, quick measurement tool helpful. Measurement-based care (MBC) provides specific and objective information on which to base clinical decisions and should therefore enhance quality of care and treatment outcomes.1-3
MBC rests on these assumptions.
• Compared with general questions that are typically asked during a patient evaluation, specific measurements (administered by clinicians or self-reported by patients) provide more accurate information on which to establish a diagnosis, assess treatment outcomes, and modify treatments.
• Patients who complete these mea-surement tests will better understand their disorder and treatment effects, which will enable them to better manage their depression.
• Medical records that include the results of specific measurements will assist subsequent clinicians in understanding the results of prior treatments.
• The routine use of the same mea-surements in practice and clinical research studies will help clinicians translate research findings into their own practices.
• For most outpatients with depression, self-report methods are available that are free and that take little time and effort.
Researchers have used criterion-based diagnostic methods for years. After DSM-III was introduced in 1980, the Structured Clinical Interviews for DSM-III (SCID) (and later for DSM-IV) were developed to obtain lifetime diagnoses.4,5 Briefer structured interviews were then developed, including the Mini-International Neuropsychiatric Interview (MINI), which assesses only current diagnoses, and the MINI-Plus, which elicits information about current and past diagnoses.6-8 The MINI takes 30 to 40 minutes to administer, while the MINI-Plus may take up to 60 minutes.
Studies have shown that structured or semistructured interviews provide more accurate diagnoses than typical practice. For example, clinically rendered diagnoses were compared with those made based on SCID results.9 Major diagnostic differences were found in 40% of outpatients with clinical diagnoses of schizophrenia or bipolar or major depressive disorders. In addition, when clinicians were provided with a diagnosis that was determined using SCID, they changed the chart diagnosis in a substantial proportion of cases and prescribed fewer medications.10
Once a diagnosis has been made and therapy has been initiated, the regimen must often be modified because of intolerance, adverse effects, or other less-than-desirable symptomatic outcomes. Medication and somatic therapies are typically aimed at treating symptoms, but psychotherapy and disease self-management may also address other aspects of treatment (eg, medication adherence, social/occu-pational function, self-esteem). The Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies showed that diligent assessment of symptoms and adverse effects enhances outcomes.11-14
The goal of therapy for depression is symptom remission and, ultimately, sustained remission and functional recovery.15 Most patients require more than 1 treatment revision (eg, altered dosage, treatment, or delivery). When implementing guideline-driven or evidence-based care, initial treatment is continued until remission or maximal symptom improvement is obtained or until the patient cannot tolerate the regimen. Thereafter, the dosage or type of treatment may be changed.
Specific implementation is associated with a significant number of errors that do not reflect clinical need (such as too rapid or too slow treatment change). Some clinicians try an antidepressant for too short a duration (eg, only 2 to 4 weeks) and then change medication if the patient globally sees “no benefit.” Because patients with depression have negative cognitive biases, they are less likely to recognize modest improvements when asked global questions about their symptom response. Thus, a medication that has some modest effect after 2 to 4 weeks may be mistaken as “ineffective” by the patient and then stopped, when its continued use could have produced remission. Yet, when itemized symptom measurements are used, clinicians can often detect some meaningful degree of improvement, leading to the continuation of treatment—perhaps with a dose escalation rather than a treatment change. This scenario highlights the drawbacks of depending on global judgment rather than a more careful, detailed assessment to make appropriate treatment decisions.16
Conversely, a clinician may continue a treatment that affords some improvement but not remission—even after optimal therapeutic effect could be expected. Perhaps the clinician and his or her patient with depression are willing to settle for “better, but not well” (ie, a response) as a good enough outcome. Or perhaps the clinician is not aware that the patient is still experiencing substantial symptoms. Again, a sensitive symptom measurement provides better and more accurate information about “residual” symptoms that could be diminished by adjusting the dosage or type of treatment.
The impetus for developing symptom measurements came from research trial needs. The gold standard has been the clinician-rated 17-item Hamilton Rating Scale for Depression (HAM-D-17), which is also available in longer formats.17,18 The Montgomery-sberg Depression Rating Scale (MADRS) was developed from a long list of items, 10 of which are optimal for differentiating drug efficacy from placebo in trials.19 MADRS items are sensitive to symptom changes with treatment. Neither the HAM-D-17 nor the MADRS, however, includes all 9 DSM-IV diagnostic symptom domain criteria that define a major depressive episode.
1. Rush AJ. Strategies and tactics in the management of maintenance treatment for depressed patients. J Clin Psychiatry. 1999;60(suppl 14):21-26.
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. Neuropsychopharmacology. 2007;32: 2479-2489.
3. Trivedi MH, Daly EJ. Measurement-based care for refractory depression: a clinical decision support model for clinical research and practice. Drug Alcohol Depend. 2007;88:S61-S71.
4. Spitzer RL, Williams JB, Gibbon M. The structured Clinical Interview for DSM-III (SCID). New York: New York State Psychiatric Institute; 1986.
5. First MB, Spitzer RL, Gibbon M, et al. 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.
6. First MB, Spitzer RL, Williams JB, et al. 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. Eur Psychiatry. 1997; 12:224-231.
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 DSM-IV and ICD-10. J Clin Psychiatry. 1998;59(suppl 20):22-33.
9. Ramirez Basco MV, Bostic JQ, Davies D, et al. Methods to improve diagnostic accuracy in a community mental health setting. Am J Psychiatry. 2000;157: 1599-1605.
10. Kashner TM, Rush AJ, Suris A, et al. Impact of structured clinical interviews on physicians’ practices in community mental health settings. Psychiatr Serv. 2003;54:712-718.
11. Rush AJ, Crismon ML, Kashner TM, et al. Texas Medication Algorithm Project, phase 3 (TMAP-3): rationale and study design. J Clin Psychiatry. 2003;64: 357-369.
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. Psychiatr Clin North Am. 2003;26:457-494.
14. Rush AJ, Fava M, Wisniewski SR, et al. Sequenced treatment alternatives to relieve depression (STAR*D): rationale and design. Control Clin Trials. 2004;25:119-142.
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. Neuropsychopharmacology. 2006;31:1841-1853.
16. Biggs MM, Shores-Wilson K, Rush AJ, et al. A comparison of alternative assessments of depressive symptom severity: a pilot study. Psychiatry Res. 2000; 96:269-279.
17. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56-62.
18. Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol. 1967; 6:278-296.
19. Montgomery SA, Åsberg M. A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979;134:382-389.
20. Beck AT, Steer RA, Brown G. Beck Depression Inventory Manual. 2nd ed. San Antonio, TX: Psychological Corporation; 1996.
21. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67: 361-370.
22. Zung WW. A self-rating depression scale. Arch Gen Psychiatry. 1965;12:63-70.
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. Biol Psychiatry. 2003;54: 573-583.
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. Biol Psychiatry. 2006;59:493-501.
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. Psychol Med. 2004;34:73-82.
26. Kroenke K, Spitzer RL, Williams JB. The PHQ-9. Validity of a brief depression severity measure. J Gen Intern Med. 2001;16:606-613.
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.
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.