Scaling Beyond Early Adopters: a Content Analysis of Literature and Key Informant Perspectives.

BACKGROUND: Innovations and improvements in care delivery are often not spread across all settings that would benefit from their uptake. Scale-up and spread efforts are deliberate efforts to increase the impact of innovations successfully tested in pilot projects so as to benefit more people. The final stages of scale-up and spread initiatives must contend with reaching hard-to-engage sites. OBJECTIVE: To describe the process of scale-up and spread initiatives, with a focus on hard-to-engage sites and strategies to approach them. DESIGN: Qualitative content analysis of systematically identified literature and key informant interviews. PARTICIPANTS: Leads from large magnitude scale-up and spread projects. APPROACH: We conducted a systematic literature search on large magnitude scale-up and spread and interviews with eight project leads, who shared their perspectives on strategies to scale-up and spread clinical and administrative practices across healthcare systems, focusing on hard-to-engage sites. We synthesized these data using content analysis. KEY RESULTS: Searches identified 1919 titles, of which 52 articles were included. Thirty-four discussed general scale-up and spread strategies, 11 described hard-to-engage sites, and 7 discussed strategies for hard-to-engage sites. These included publications were combined with interview findings to describe a fourth phase of the national scale-up and spread process, common challenges for spreading to hard-to-engage sites, and potential benefits of working with hard-to-engage sites, as well as useful strategies for working with hard-to-engage sites. CONCLUSIONS: We identified scant published evidence that describes strategies for reaching hard-to-engage sites. The sparse data we identified aligned with key informant accounts. Future work could focus on better documentation of the later stages of spread efforts, including specific tailoring of approaches and strategies used with hard-to-engage sites. Spread efforts should include a "flexible, tailored approach" for this highly variable group, especially as implementation science is looking to expand its impact in routine care settings.

Differences in Depression Care for Men and Women among Veterans with and without Psychiatric Comorbidities.

BACKGROUND: Depression is common among primary care patients, affecting more women than men. Women veterans are an extreme but growing minority among patients seeking care from the Department of Veterans Affairs (VA), an organization historically designed to serve men. Little is known about gender differences in depression care quality within the VA primary care population. PURPOSE: This works assesses the gender differences in depression care among veterans using longitudinal electronic measures. METHODS: We undertook a cross-sectional study of all veteran VA primary care users with a new episode of depression from federal fiscal year 2010, covering nine geographically diverse regions. We assessed the quality of depression care based on receipt of minimally appropriate depression treatment within 1 year of a new episode of depression and on receipt of depression-related follow-up visits within 180 days. Minimally appropriate treatment and follow-up were operationalized as meeting or exceeding a minimally appropriate threshold for care, based on national quality measures and expert panel consensus. Regression models were used to produce predicted probabilities for each process outcome accounting for the presence or absence of other psychiatric comorbidities. All models were adjusted for model covariates and clinic clusters (404 sites). MAIN FINDINGS: In 2010, 110,603 veterans with a primary care visit had a new episode of depression; 10,094 (9%) were women. In multivariate analyses, women had modest yet significantly higher rates of minimally appropriate depression treatment than men, whether patients had depression only (79% of women vs. 76% of men; p < .001) or depression along with other psychiatric comorbidities (92% of women vs. 91% or men; p < .001). There were no significant gender differences for rate of receipt of follow-up for depression at 180 days. Interactions between gender and other psychiatric comorbidities were not significant. CONCLUSIONS: Our findings suggest that the VA is achieving comparable depression care between genders at minimally appropriate thresholds.

The Impact of Community Engagement on Health, Social, and Utilization Outcomes in Depressed, Impoverished Populations: Secondary Findings from a Randomized Trial.

BACKGROUND: Disparities in depression care exist among the poor. Community Partners in Care (CPIC) compared a community coalition model with technical assistance to improve depression services in under-resourced communities. We examine effects on health, social, and utilization outcomes among the poor and, non-poor depressed, and poor subgroups. METHODS: This study analyzed clients living above (n = 268) and below (n = 750) the federal-poverty level and, among the poor, 3 nonoverlapping subgroups: justice-involved (n = 158), homeless and not justice-involved (n = 298), and other poor (n = 294). Matched programs (n = 93) from health and community sectors were randomly assigned to community engagement and planning (CEP) or resources for services (RS). Primary outcomes were poor mental health-related quality of life and 8-item Patient Health Questionnaire scores, whereas community-prioritized and utilization outcomes were secondary. Effects were scrutinized using false discovery rate-adjusted P values to account for multiple comparisons. RESULTS: In the impoverished group, CEP and RS clients of participating study programs did not differ in primary outcomes, but CEP more than RS improved mental wellness among the depressed poor (unadjusted P = .004) while providing suggestive evidence for other secondary outcomes. Within the poor subgroups, evidence favoring CEP was only suggestive but was strongest among justice-involved clients. CONCLUSIONS: A coalition approach to improving outcomes for low-income clients with depression, particularly those involved in the justice system, may offer additional benefits over standard technical assistance programs.

Depression Quality of Care: Measuring Quality over Time Using VA Electronic Medical Record Data.

BACKGROUND: The Veterans Health Administration (VA) has invested substantially in evidence-based mental health care. Yet no electronic performance measures for assessing the level at which the population of Veterans with depression receive appropriate care have proven robust enough to support rigorous evaluation of the VA's depression initiatives. OBJECTIVE: Our objectives were to develop prototype longitudinal electronic population-based measures of depression care quality, validate the measures using expert panel judgment by VA and non-VA experts, and examine detection, follow-up and treatment rates over a decade (2000-2010). We describe our development methodology and the challenges to creating measures that capture the longitudinal course of clinical care from detection to treatment. DESIGN AND PARTICIPANTS: Data come from the National Patient Care Database and Pharmacy Benefits Management Database for primary care patients from 1999 to 2011, from nine Veteran Integrated Service Networks. MEASURES: We developed four population-based quality metrics for depression care that incorporate a 6-month look back and 1-year follow-up: detection of a new episode of depression, 84 and 180 day follow-up, and minimum appropriate treatment 1-year post detection. Expert panel techniques were used to evaluate the measure development methodology and results. Key challenges to creating valid longitudinal measures are discussed. KEY RESULTS: Over the decade, the rates for detection of new episodes of depression remained stable at 7-8 %. Follow-up at 84 and 180 days were 37 % and 45 % in 2000 and increased to 56 % and 63 % by 2010. Minimum appropriate treatment remained relatively stable over the decade (82-84 %). CONCLUSIONS: The development of valid longitudinal, population-based quality measures for depression care is a complex process with numerous challenges. If the full spectrum of care from detection to follow-up and treatment is not captured, performance measures could actually mask the clinical areas in need of quality improvement efforts.