Effects of County Strategies to Scale Evidence-Informed Social Services

Background and Purpose: A persistent and seemingly intractable problem is the systemic failure to successfully scale evidence-informed social services to a level that achieves population-level improvements in well-being. Scholars are calling for governments to enter the scaling environment by executing four scaling strategies: (1) convene and support high-level leadership teams, (2) assess organizational readiness, (3) provide technical assistance, and (4) align funding. However, it is unclear whether these strategies are sufficient to achieve desired outcomes. This study, aims to provide insight into the relationship between government-led scaling strategies and scaling outcomes. It describes one county’s implementation of the four suggested scaling strategies and it examines the relative impact of these strategies on organization-level adoption of evidence-informed services.

Methods: This study uses public government records from five sources including 1,756 meeting minutes. It uses crowd-sourced and computational data-extraction methods to create measures of the four scaling strategies. And, it assesses the relative effects of these strategies on scaling progress using time-to-event analysis.

Results: Over seven years, this county increased the number of social services providers adopting evidence-informed services from 30 to 70. And, the number of unique evidence-informed services delivered by these organizations grew from 16 to 92. Through the implementation of the four scaling strategies, this county interacted with 493 local organizations. (1) The county embedded discussions of evidence-informed service in its existing governance network and exposed 233 organizations to the concept of scaling. Organizations that participated in more than one committee were more likely to adopt an evidence-informed service (HR = 6.44, SE = 0.52, p < .000). (2) The county assessed commitment to and capacity for evidence-informed services among 80 organizations. These found to internally support evidence-informed services were more likely to subsequently adopt one or more (HR = 4.92, SE = .33, p < .000). (3) The county provided capacity building assistance to 192 organizations. Surprisingly, this support has not yet effected organizational adoption of evidence-informed service, although other research suggests that technical assistance is critical. (4) The county increased the percent of contract funding awarded to organizations delivering confirmed evidence-informed services from 14% to 67%. It appears that a substantial existing contracted relationship between the county and an organization influences the likelihood that the organization will subsequently adopt evidence informed services. Organizations in the fourth quartile of prior county funding were more likely to adopt an evidence-informed service (HR = 1.45, SE = .15, p < .05).

Conclusions and Implications: This study provides initial evidence that local governments have the capacity, if they choose to use it, to successfully increase the scaling of evidence-informed services within their jurisdiction. They can convene influential committees, they can assess and promote organizational readiness, and they can gradually shift funding to organizations that are delivering evidence-informed services. Understanding and harnessing the power of government interventions as levers to promote scaling of evidence-informed services may be the best opportunity to date to achieve wide-scale implementation of evidence-informed services and their promised population-level benefits.