The effects of primary care depression treatment on patients' clinical status and employment.

OBJECTIVE To evaluate the effects of depression treatment in primary care on patients' clinical status and employment, over six months. DATA SOURCES/STUDY SETTING Data are from a randomized controlled trial of quality improvement for depression that included 938 adults with depressive disorder in 46 managed primary care clinics in five states. STUDY DESIGN Observational analysis of the effects of evidence-based depression care over six months on health outcomes and employment. Selection into treatment is accounted for using instrumental variables techniques, with randomized assignment to the quality improvement intervention as the identifying instrument. DATA COLLECTION/EXTRACTION METHODS Patient-reported clinical status, employment, health care use, and personal characteristics; health care use and costs from claims data. PRINCIPAL FINDINGS At six months, patients with appropriate care, compared to those without it, had lower rates of depressive disorder (24 percent versus 70 percent), better mental health-related quality of life, and higher rates of employment (72 percent versus 53 percent), each p<.05. CONCLUSIONS Appropriate treatment for depression provided in community-based primary care substantially improves clinical and quality of life outcomes and employment.

[1]  W. Katon,et al.  Cost-effectiveness of a collaborative care program for primary care patients with persistent depression. , 2001, The American journal of psychiatry.

[2]  V. Wilcox-Gök,et al.  The Labor Market Effects of Mental Illness: The Case of Affective Disorders , 2000 .

[3]  David E. Booth,et al.  Analysis of Incomplete Multivariate Data , 2000, Technometrics.

[4]  C. Sherbourne,et al.  Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial. , 2000, JAMA.

[5]  K. Wells,et al.  Quality of care for primary care patients with depression in managed care. , 1999, Archives of family medicine.

[6]  R. Neugebauer,et al.  Mind matters: the importance of mental disorders in public health's 21st century mission. , 1999, American journal of public health.

[7]  K. Wells,et al.  Evidence-based care for depression in managed primary care practices. , 1999, Health affairs.

[8]  J. Stoker,et al.  The Department of Health and Human Services. , 1999, Home healthcare nurse.

[9]  K. Harris,et al.  Who is the marginal patient? Understanding instrumental variables estimates of treatment effects. , 1998, Health services research.

[10]  A. Rush,et al.  Workplace performance effects from chronic depression and its treatment. , 1998, Journal of health economics.

[11]  G. Simon,et al.  Assessing the feasibility of using computerized pharmacy refill data to monitor antidepressant treatment on a population basis: a comparison of automated and self-report data. , 1998, Journal of clinical epidemiology.

[12]  R. Sturm Instrumental variable methods for effectiveness research , 1998 .

[13]  R. Kessler,et al.  The impact of psychiatric disorders on work loss days , 1997, Psychological Medicine.

[14]  C. Vázquez,et al.  Lifetime and 12‐month prevalence of DSM‐III‐R mental disorders among the homeless in Madrid: a European study using the CIDI , 1997, Acta psychiatrica Scandinavica.

[15]  J. Heckman Instrumental Variables: A Study of Implicit Behavioral Assumptions in One Widely Used Estimator , 1997 .

[16]  R. Kessler,et al.  The Impact of Psychiatric Disorders on Labor Market Outcomes , 1997 .

[17]  W. Katon,et al.  A multifaceted intervention to improve treatment of depression in primary care. , 1996, Archives of general psychiatry.

[18]  J. Lave,et al.  Treating major depression in primary care practice. Eight-month clinical outcomes. , 1996, Archives of general psychiatry.

[19]  S. Beach,et al.  Subclinical depression and performance at work , 1996, Social Psychiatry and Psychiatric Epidemiology.

[20]  R. Morriss Mental Illness in General Health Care: An International Study , 1995 .

[21]  James J. Heckman,et al.  Randomization as an Instrumental Variable , 1995 .

[22]  D. Rice,et al.  The Economic Burden of Affective Disorders , 1995, British Journal of Psychiatry.

[23]  R. J. Hayes,et al.  Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials. , 1995, JAMA.

[24]  K. Wells,et al.  How can care for depression become more cost-effective? , 1995, JAMA.

[25]  E. Berndt,et al.  The economic burden of depression in 1990. , 1993, The Journal of clinical psychiatry.

[26]  Joshua D. Angrist,et al.  Identification of Causal Effects Using Instrumental Variables , 1993 .

[27]  F. Goodwin,et al.  The de facto US mental and addictive disorders service system. Epidemiologic catchment area prospective 1-year prevalence rates of disorders and services. , 1993, Archives of general psychiatry.

[28]  J. Mintz,et al.  Treatments of depression and the functional capacity to work. , 1992, Archives of general psychiatry.

[29]  W. Katon,et al.  Epidemiology of depression in primary care. , 1992, General hospital psychiatry.

[30]  J Ormel,et al.  Recognition, management, and course of anxiety and depression in general practice. , 1991, Archives of general psychiatry.

[31]  L. George,et al.  Depression, disability days, and days lost from work in a prospective epidemiologic survey. , 1990, JAMA.

[32]  A. Stewart,et al.  The functioning and well-being of depressed patients. Results from the Medical Outcomes Study. , 1989, JAMA.

[33]  S. Young Treatment of mental disorders. , 1979, Science.

[34]  Jerry A. Hausman,et al.  An Instrumental Variable Approach to Full-Information Estimators for Linear and Non-Linear Econometric Models , 1975 .

[35]  C. Sherbourne,et al.  The quality of care for depressive and anxiety disorders in the United States. , 2001, Archives of general psychiatry.

[36]  K. Wells,et al.  Treatment research at the crossroads: the scientific interface of clinical trials and effectiveness research. , 1999, The American journal of psychiatry.

[37]  K. Wells The design of Partners in Care: evaluating the cost-effectiveness of improving care for depression in primary care , 1999, Social Psychiatry and Psychiatric Epidemiology.

[38]  J. Newhouse,et al.  Econometrics in outcomes research: the use of instrumental variables. , 1998, Annual review of public health.

[39]  J. Heckman Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations. , 1997 .

[40]  L. Coffey Caring for depression. , 1996, Healthplan.

[41]  Alan D. Lopez,et al.  The global burden of disease: a comprehensive assessment of mortality and disability from diseases injuries and risk factors in 1990 and projected to 2020. , 1996 .

[42]  J. Brown,et al.  The paradox of guideline implementation: how AHCPR's depression guideline was adapted at Kaiser Permanente Northwest Region. , 1995, The Joint Commission journal on quality improvement.

[43]  R. Kessler,et al.  Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. , 1994, Archives of general psychiatry.

[44]  E. Ahearn Practice guidelines for major depressive disorder in adults. T. Byram Karasu, MD, et al. American Psychiatric Association, Washington D.C., 1993 57 pp., $22.50 , 1994 .

[45]  C. Attkisson,et al.  Depression in primary care : screening and detection , 1990 .

[46]  A. Caso [Depression and its treatment]. , 1971, Gaceta medica de Mexico.