The Relationship Between Quality and Outcomes in Routine Depression Care

Fortney, John C.; Rost, Kathryn; Zhang, Mingliang; Pyne, Jeff

doi:10.1176/appi.ps.52.1.56

Cited by 43 publications

(38 citation statements)

References 35 publications

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“…However, we recognize that future research needs to address challenges to the internal validity of these findings from selection bias and causal inference issues. In terms of selection bias (Newhouse & McClellan, 1998;Sturm, Unutzer, & Katon, 1999), our inability to use instrumented models in all likelihood downwardly biases the indicator-outcome relationships we report by an estimated 20% or greater (Fortney et al, 2001;Schoenbaum et al, 2002). In terms of inference, we recognize the non-experimental design prevents us from definitively concluding that high-quality depression care improves clinical outcomes; however, experimental studies showing that interventions that improve antidepressant medication management do in fact significantly reduce depressive symptoms (Wells et al, 2000;Rost, Nutting, Smith, Elliott, & Dickinson, 2002;Katon et al, 1995;Katon et al, 1996;Schulberg et al, 1996;Katzelnick et al, 2000;Katon et al, 1999;Simon, VonKorff, Rutter, & Wagner, 2000;Hunkeler et al, 2000), strengthen the causal link between quality and outcomes this study and other investigators observe (see Table 2).…”

Section: Discussionmentioning

confidence: 95%

“…To rule out the possibility that the indicator's impact on severity reflected concurrent psychotherapy, we conducted an analysis in the subgroup of patients whose administrative database records indicated they had no psychotherapy visits in the 6 months following the index visit. We were prohibited from using instrument variables to correct for selection bias by the small sample size; however, previous research suggests that non-instrumented estimates of indicator-outcome relationships are conservative (Schoenbaum et al, 2002;Fortney et al, 2001). Power analyses indicated that the sample size provided us greater than 80% power to detect a .8 effect of the indicator on severity change using a two-sided test with alpha set at .05.…”

Section: Discussionmentioning

confidence: 99%

“…Little is known about whether indicators currently calculated for the population in treatment accurately characterize the population in need because (unlike other chronic conditions) most depressed patients are not in treatment (Rost, Smith, Guise, & Matthews, 1994;). In addition, it is unclear whether HEDIS-based outpatient depression indicators predict improved outcomes in either the population in treatment or the population in need (Rost, Williams, Wherry, & Smith, 1995;Simon et al, 1995;Melfi et al, 1998;Katon et al, 2000;Fortney, Rost, Zhang, & Pyne, 2001;Bull et al, 2002;Schoenbaum et al, 2002); however, multiple studies question whether administrative databases contain too much measurement error to derive valid quality metrics for any condition (Hunt et al, 2000;Cotter, Smith, Rossiter, Pugh, & Bramble, 1999;Bloom, Harris, Thompson, Ahmed, & Thompson, 2000;Kobak et al, 2002;Jones et al, 2000). Conducted as a secondary analysis in a cooperative study database , the first objective of the study was to calculate HEDIS-based outpatient depression indicator rates for the population in need.…”

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confidence: 99%

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Clinical Improvement Associated with Conformance to HEDIS-Based Depression Care

Rost

Dickinson

Fortney

et al. 2005

Ment Health Serv Res

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Background: Employers recently requested a valid metric of depression treatment quality. Such an indicator needs to measure the proportion of the population in need who receive high-quality care, and to predict clinical improvement. Methods: We constructed an administrative database indicator derived from HEDIS criteria for antidepressant medication management, and tested it in 230 employed patients in five health plans. Results: Indicator rates were 7.0% in the population in need. Conformance to indicator criteria in this population was associated with 23.0% improvement in depression severity over 1 year (p = .02). Conclusions: Administrative database indicators that predict clinical improvement are a very rare accomplishment. Existing depression indicators may need to be calculated for the population in need to provide a valid metric for employer purchasers.

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Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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Clinical Improvement Associated with Conformance to HEDIS-Based Depression Care

Rost

Dickinson

Fortney

et al. 2005

Ment Health Serv Res

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“…Evidence-based guidelines are available to facilitate clinical decisionmaking, and guideline-concordant treatment improves outcomes [2]. Yet despite the high prevalence of depression, its associated disability, and availability of effective treatments, only 17-36% of depressed patients receive guideline-concordant care [1-5].…”

Section: Introductionmentioning

confidence: 99%

Association of General Medical and Psychiatric Comorbidities With Receipt of Guideline-Concordant Care for Depression

Ettner

Azocar²,

Branstrom³

et al. 2010

Psychiatric Services

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Objective The objective is to describe the effect of medical and psychiatric comorbidities on receipt of guideline-concordant depression care. Methods 2003-6 pharmacy, medical and behavioral claims and enrollment data from OptumHealth were linked for 1,835 adults with a new depression diagnosis or antidepressant fill. Multiple logistic regression was used to estimate the association of comorbidities with receipt of guideline-concordant pharmacotherapy, psychotherapy, and any therapy. Results Respectively 11%, 23% and 33% of study patients received guideline-concordant psychotherapy, pharmacotherapy and any therapy. Having a psychiatric but no medical comorbidity was associated with higher rates of guideline-concordant psychotherapy and overall guideline concordance; the converse was true for having a medical but no psychiatric comorbidity. Associations of comorbidities were with the probability of receiving any therapy, not improved guideline-concordance among patients already receiving therapy. Conclusions Patients with medical comorbidities may not receive psychotherapy referrals, perhaps due to well-established relationships with their primary care providers.

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“…[7][8][9] However, empirical evidence has yielded mixed results for the effectiveness of treating subthreshold depression. 10,11 The conflicting findings surrounding subthreshold depression may be partially explained by the heterogeneity of the condition being studied; many different definitions of subthreshold depression have been used in the past. 12 To standardize the assessment of subthreshold depression, the DSM-IV-TR 13 has published research criteria for the proposed diagnosis of minor depressive disorder.…”

mentioning

confidence: 99%

Primary Care Evaluation of Mental Disorders (PRIME-MD) Screening for Minor Depressive Disorder in Primary Care

Tamburrino¹,

Lynch²,

Nagel³

et al. 2009

Prim. Care Companion J. Clin. Psychiatry

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Objective: Individuals visiting a primary care practice were screened to determine the prevalence of depressive disorders. The DSM-IV-TR research criteria for minor depressive disorder were used to standardize a definition for subthreshold symptoms.Method: Outpatients waiting to see their physicians at 3 community family medicine sites were invited to complete a demographic survey and the Primary Care Evaluation of Mental Disorders Patient Questionnaire (PRIME-MD PQ). Those who screened positive for depression on the PRIME-MD PQ were administered both the PRIME-MD Clinician Evaluation Guide (CEG) mood module and the Hamilton Depression Rating Scale (HDRS) by telephone. Data were collected over a 2-year period (1996)(1997)(1998).Results: 1,752 individuals completed the PRIME-MD PQ with 478 (27.3%) scoring positive for depression. Of these 478 patients, 321 received telephone follow-up using the PRIME-MD CEG mood module and the HDRS. PRIME-MD diagnoses were major depressive disorder (n = 85, 26.5%), dysthymia (n = 31, 9.6%), minor depressive disorder (n = 51, 15.9%), and no depression diagnosis (n = 154, 48.0%). The mean HDRS scores by diagnosis were major depressive disorder (20.3), dysthymia (12.9), minor depressive disorder (11.7), and no depression diagnosis (5.8). Post hoc analyses using Dunnett's C test indicated differences between each of the 4 groups at P ≤ .05, with the exception that dysthymia and minor depressive disorder were not significantly different.Conclusions: Minor depressive disorder was more prevalent than dysthymia and had similar symptom severity to dysthymia as measured by the HDRS. More research using standardized definitions and longitudinal studies is needed to clarify the natural course and treatment indications for minor depressive disorder.

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The Relationship Between Quality and Outcomes in Routine Depression Care

Abstract: This community-based, nonexperimental study found a positive relationship between the quality of care for depression and clinical outcomes for patients with major depression in routine practice settings.

Cited by 43 publications

References 35 publications

Clinical Improvement Associated with Conformance to HEDIS-Based Depression Care

Clinical Improvement Associated with Conformance to HEDIS-Based Depression Care

Association of General Medical and Psychiatric Comorbidities With Receipt of Guideline-Concordant Care for Depression

Primary Care Evaluation of Mental Disorders (PRIME-MD) Screening for Minor Depressive Disorder in Primary Care

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