Case-Finding for Depression Among Medical Outpatients in the Veterans Health Administration
Mental Illness Research, Education, VA Connecticut Healthcare System, West Haven, Connecticut 06516, USA. Medical Care
(Impact Factor: 3.23).
03/2006; 44(2):175-81. DOI: 10.1097/01.mlr.0000196962.97345.21
We sought to determine the rates and predictors of screening, screening positive, follow-up evaluation, and subsequent diagnosis of depression among medical outpatients.
This was a cross-sectional study using chart-review data from the Department of Veterans Affairs (VA) 2002 External Peer Review Program merged with administrative data.
We studied a national sample of VA medical outpatients with no depression diagnosis or mental health visits in the past 6 months (n = 21,489) and used chart-review and administrative data to follow the chain of events from depression screening to diagnosis.
Overall, 84.9% of eligible patients (n = 18,245) were screened for depression in the past year. Of the 8.8% who screened positive, only 54.0% received follow-up evaluation and, of these, 23.6% (n = 204) subsequently were diagnosed with a depressive disorder (representing 1.1% of the originally screened sample). Patients who were younger, unmarried, and had more medical comorbidities were less likely to be screened; however, if screened, they were more likely to screen positive. Male gender and greater medical comorbidity were associated with decreased odds of follow-up evaluation after a positive screen. At the facility level, likelihood of depression screening was inversely associated with spending on teaching and research but positively associated with spending on mental health care.
VA's depression case-finding activities yielded relatively few positive cases, raising questions about cost-effectiveness. Targeted strategies may increase the value of case-finding among patients at greatest risk for depression and at more academically affiliated medical centers. Targeted efforts also are needed to ensure proper follow-up evaluation of suspected cases, particularly among male patients and those with increased medical comorbidity.
Available from: Jeffrey L Smith
- "Of VA patients screening positive for depression, only about half (54%) receive the recommended follow-up evaluation to confirm the diagnosis . Another recent study found that among VA patients with severe depression symptoms, 36% remained undiagnosed and untreated with antidepressants over one year . "
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ABSTRACT: Little is known about effective strategies for disseminating and implementing complex clinical innovations across large healthcare systems. This paper describes processes undertaken and tools developed by the U.S. Department of Veterans Affairs (VA) Mental Health Quality Enhancement Research Initiative (MH-QUERI) to guide its efforts to partner with clinical leaders to prepare for national dissemination and implementation of collaborative care for depression.
An evidence-based quality improvement (EBQI) process was used to develop an initial set of goals to prepare the VA for national dissemination and implementation of collaborative care. The resulting product of the EBQI process is referred to herein as a "National Dissemination Plan" (NDP). EBQI participants included: a) researchers with expertise on the collaborative care model for depression, clinical quality improvement, and implementation science, and b) VA clinical and administrative leaders with experience and expertise on how to adapt research evidence to organizational needs, resources and capacity. Based on EBQI participant feedback, drafts of the NDP were revised and refined over multiple iterations before a final version was approved by MH-QUERI leadership. 'Action Teams' were created to address each goal. A formative evaluation framework and related tools were developed to document processes, monitor progress, and identify and act upon barriers and facilitators in addressing NDP goals.
The National Dissemination Plan suggests that effectively disseminating collaborative care for depression in the VA will likely require attention to: Guidelines and Quality Indicators (4 goals), Training in Clinical Processes and Evidence-based Quality Improvement (6 goals), Marketing (7 goals), and Informatics Support (1 goal). Action Teams are using the NDP as a blueprint for developing infrastructure to support system-wide adoption and sustained implementation of collaborative care for depression. To date, accomplishments include but are not limited to: conduct of a systematic review of the literature to update VA depression treatment guidelines to include the latest evidence on collaborative care for depression; training for clinical staff on TIDES (Translating Initiatives for Depression into Effective Solutions project) care; spread of TIDES care to new VA facilities; and integration of TIDES depression assessment tools into a planned update of software used in delivery of VA mental health services. Thus far, common barriers encountered by Action Teams in addressing NDP goals include: a) limited time to address goals due to competing tasks/priorities, b) frequent turnover of key organizational leaders/stakeholders, c) limited skills and training among team members for addressing NDP goals, and d) difficulty coordinating activities across Action Teams on related goals.
MH-QUERI has partnered with VA organizational leaders to develop a focused yet flexible plan to address key factors to prepare for national dissemination and implementation of collaborative care for depression. Early indications suggest that the plan is laying an important foundation that will enhance the likelihood of successful implementation and spread across the VA healthcare system.
Implementation Science 01/2009; 3(1):59. DOI:10.1186/1748-5908-3-59 · 4.12 Impact Factor
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ABSTRACT: A new method for characterizing surface topography using a 2-dimensional discrete wavelet transform (2-D DWT) has been developed. The wavelet transform (WT) is the basis for a wide range of techniques applied in image processing and pattern recognition. Its main advantages over other feature extraction methods are the space-frequency localization, and the multi-resolution view of the frequency components of a signal. In this paper, an automatic grinding modes classification technique using a 2-D DWT is introduced, and comparisons of automatic grinding modes classification and human eye inspection are also examined
Emerging Technologies and Factory Automation, 1996. EFTA '96. Proceedings., 1996 IEEE Conference on; 12/1996
Available from: Joseph Goulet
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ABSTRACT: Electronic medical records systems (EMR) contain many directly analyzable data fields that may reduce the need for extensive chart review, thus allowing for performance measures to be assessed on a larger proportion of patients in care.
This study sought to determine the extent to which selected chart review-based clinical performance measures could be accurately replicated using readily available and directly analyzable EMR data.
A cross-sectional study using full chart review results from the Veterans Health Administration's External Peer Review Program (EPRP) was merged to EMR data.
Over 80% of the data on these selected measures found in chart review was available in a directly analyzable form in the EMR. The extent of missing EMR data varied by site of care (P<0.01). Among patients on whom both sources of data were available, we found a high degree of correlation between the 2 sources in the measures assessed (correlations of 0.89-0.98) and in the concordance between the measures using performance cut points (kappa: 0.86-0.99). Furthermore, there was little evidence of bias; the differences in values were not clinically meaningful (difference of 0.9 mg/dL for low-density lipoprotein cholesterol, 1.2 mm Hg for systolic blood pressure, 0.3 mm Hg for diastolic, and no difference for HgbA1c).
Directly analyzable data fields in the EMR can accurately reproduce selected EPRP measures on most patients. We found no evidence of systematic differences in performance values among these with and without directly analyzable data in the EMR.
Medical Care 01/2007; 45(1):73-9. DOI:10.1097/01.mlr.0000244510.09001.e5 · 3.23 Impact Factor
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