Screening, assessment, and management of depression in VA primary care clinics

Oslin, David W.; Ross, Jennifer; Sayers, Steve; Murphy, John; Kane, Vince; Katz, Ira R.

doi:10.1111/j.1525-1497.2005.0267.x

Cited by 142 publications

(116 citation statements)

References 23 publications

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“…The program was expanded in 2008 to be a routine expectation of care with larger VA primary care settings required to have blended programs incorporating both colocated collaborative care and care management [24]. Strong, preexisting research and quality improvement provided best practices that support PC-MHI including the White River Model for colocated collaborative care [25,26], and Translating Initiatives for Depression into Effective Solutions (TIDES) and the Behavioral Health Laboratory for care management [27][28][29].…”

Section: Pc-mhi Program Implementationmentioning

confidence: 99%

The role of mental and behavioral health in the application of the patient-centered medical home in the Department of Veterans Affairs

Kearney¹,

Post²,

Zeiss

et al. 2011

Behav. Med. Pract. Policy Res.

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Section: Pc-mhi Program Implementationmentioning

confidence: 99%

The role of mental and behavioral health in the application of the patient-centered medical home in the Department of Veterans Affairs

Kearney¹,

Post²,

Zeiss

et al. 2011

Behav. Med. Pract. Policy Res.

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“…For example, the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) 50 , the US Department of Veterans Affairs Behavioral Health Laboratory model 51,52 and the US Department of Defense Behavioral Health Data Portal 53 are all examples of measurement-based care applied to patient populations. In the State of Minnesota, the Depression Improvement Across Minnesota, Offering a New Direction (DIA-MOND) initiative implemented measurement-based care to help benchmark quality improvement efforts as part of a bundled payment initiative for depression care management 54 .…”

Section: Current State Of Measuring Mental Health Care Qualitymentioning

confidence: 99%

Measuring and improving the quality of mental health care: a global perspective

et al. 2018

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Mental disorders are common worldwide, yet the quality of care for these disorders has not increased to the same extent as that for physical conditions. In this paper, we present a framework for promoting quality measurement as a tool for improving quality of mental health care. We identify key barriers to this effort, including lack of standardized information technology-based data sources, limited scientific evidence for mental health quality measures, lack of provider training and support, and cultural barriers to integrating mental health care within general health environments. We describe several innovations that are underway worldwide which can mitigate these barriers. Based on these experiences, we offer several recommendations for improving quality of mental health care. Health care payers and providers will need a portfolio of validated measures of patient-centered outcomes across a spectrum of conditions. Common data elements will have to be developed and embedded within existing electronic health records and other information technology tools. Mental health outcomes will need to be assessed more routinely, and measurement-based care should become part of the overall culture of the mental health care system. Health care systems will need a valid way to stratify quality measures, in order to address potential gaps among subpopulations and identify groups in most need of quality improvement. Much more attention should be devoted to workforce training in and capacity for quality improvement. The field of mental health quality improvement is a team sport, requiring coordination across different providers, involvement of consumer advocates, and leveraging of resources and incentives from health care payers and systems.

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“…The alternative collaborative care models, TIDES and BHL, were each associated with developed programs that included distinct VA-tested implementation methods, tools and training. 31,32,34,39 These programs were open to any VA PC practice through national trainings, ongoing program support staff, and sharing of technologies. These two programs, however, had different histories and goals; TIDES was initially developed and tested through regional networks, whereas BHL was developed at a single site.…”

Section: 53mentioning

confidence: 99%

“…[33][34][35]39 BHL focused on laboratory-specific software that enabled sophisticated algorithm-based telephone assessment by a health technician, with referral of appropriate patients to a care manager. In about 2005, the model began to spread spontaneously.…”

Section: Goalsmentioning

confidence: 99%

“…30 The three models have varying levels of evidence support and requirements for organizational redesign. Collaborative care models, such as TIDES 31,32 or BHL, [33][34][35] are highly evidence-based in terms of effectiveness. However, they require significant system redesign and training, [36][37][38] with or without the addition of collocation.…”

Section: Introductionmentioning

confidence: 99%

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Determinants of Readiness for Primary Care-Mental Health Integration (PC-MHI) in the VA Health Care System

et al. 2012

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BACKGROUND: Depression management can be challenging for primary care (PC) settings. While several evidence-based models exist for depression care, little is known about the relationships between PC practice characteristics, model characteristics, and the practice's choices regarding model adoption. OBJECTIVE: We examined three Veterans Affairs (VA)-endorsed depression care models and tested the relationships between theoretically-anchored measures of organizational readiness and implementation of the models in VA PC clinics. DESIGN: 1) Qualitative assessment of the three VAendorsed depression care models, 2) Cross-sectional survey of leaders from 225 VA medium-to-large PC practices, both in 2007. MAIN MEASURES:We assessed PC readiness factors related to resource adequacy, motivation for change, staff attributes, and organizational climate. As outcomes, we measured implementation of one of the VA-endorsed models: collocation, Translating Initiatives in Depression into Effective Solutions (TIDES), and Behavioral Health Lab (BHL). We performed bivariate and, when possible, multivariate analyses of readiness factors for each model. KEY RESULTS: Collocation is a relatively simple arrangement with a mental health specialist physically located in PC. TIDES and BHL are more complex; they use standardized assessments and care management based on evidence-based collaborative care principles, but with different organizational requirements. By 2007, 107 (47.5 %) clinics had implemented collocation, 39 (17.3 %) TIDES, and 17 (7.6 %) BHL. Having established quality improvement processes (OR 2.30, [1.36,3.87], p=0.002) or a depression clinician champion (OR 2.36, [1.14, 4.88], p=0.02) was associated with collocation. Being located in a VA regional network that endorsed TIDES (OR 8.42, [3.69,19.26], p<0.001) was associated with TIDES implementation. The presence of psychologists or psychiatrists on PC staff, greater financial sufficiency, or greater spatial sufficiency was associated with BHL implementation. CONCLUSIONS: Both readiness factors and characteristics of depression care models influence model adoption. Greater model simplicity may make collocation attractive within local quality improvement efforts. Dissemination through regional networks may be effective for more complex models such as TIDES.

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Screening, assessment, and management of depression in VA primary care clinics

Cited by 142 publications

References 23 publications

The role of mental and behavioral health in the application of the patient-centered medical home in the Department of Veterans Affairs

The role of mental and behavioral health in the application of the patient-centered medical home in the Department of Veterans Affairs

Measuring and improving the quality of mental health care: a global perspective

Determinants of Readiness for Primary Care-Mental Health Integration (PC-MHI) in the VA Health Care System

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