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.

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)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(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.

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 impacts on health, social, and utilization outcomes in impoverished and non-poor depressed, and poor subgroups. Methods An analysis of clients above (N=268) and below (N=750) the federal-poverty level (FPL), and, among the poor, three non-overlapping subgroups: justice-involved (N=158), homeless 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). Outcomes are poor mental-health-quality-of-life and PHQ9 scores (primary) and community-prioritized and utilization outcomes (secondary). Effects were scrutinized using false-discovery-rate-adjusted p-values to account for multiple comparisons. Results For the impoverished, CEP and RS clients did not differ in primary outcomes but, CEP over RS improved mental wellness for depressed poor (unadjusted p=0.004) while providing suggestive evidence for other secondary outcomes. Within poor subgroups, evidence favoring CEP was only suggestive, but strongest among justice-involved clients. Conclusions A coalition approach to improve outcomes for low-income, particularly justice-involved clients, with depression may offer additional benefits over standard technical assistance programs.