Associations between Organizational Size and Implementation Behavior in Children's Mental Health Care

Background and Purpose:

Scaling evidence-based interventions (EBIs) across public health service systems is a national priority. System-wide initiatives to implement EBIs have succeeded when stakeholder groups collaborate to bridge the research-practice gap. However, it is not clear what factors facilitate implementation when a diverse population of organizations are licensed to deliver care with different characteristics and patients that are not easily amenable to change. Organizational size along with financial health, dependency, and infrastructure have been identified as structural characteristics related to innovation. Larger organizations may have more capacity and infrastructure to support translational efforts while smaller organizations may be more agile to change. In the context of a large-scale implementation effort, this study examined the relationship between the size of community mental health organizations and their adoption and implementation behavior.

Methods:

This study analyzed publicly available data from the Patient Characteristics Survey and IRS 990 forms from the Guidestar database for organizations (N=100) who were being recruited to participate in a hybrid 2 effectiveness implementation trial of an EBI for families with a child with a disruptive behavior disorder. Organizations were eligible for recruitment if they operated a New York State licensed outpatient mental health clinic. Variables were analyzed at the organizational level and included organizational characteristics (e.g., size, age), patient characteristics (e.g., race, language), and adoption behavior (i.e., meeting with project staff, implementing EBI). Organizational size was defined as total revenue less than 13 million (small), 13-55 million (medium), and greater than 55 million (large). Analyses of variance examined characteristics by size. Binary logistic regression analyses examined the relationships between organizational size and likelihood of meeting with the research team and EBI adoption.

Results:

68% of organizations (N=100) responded to initial outreach; 43% met with research personnel to learn more about the EBI, and 16% implemented the EBI. A smaller percentage of small-sized organizations met with research personnel (N=8; 27.59%), as compared to medium-sized organizations (N=15; 50%) or large-sized organizations (N=27; 67.50%). Once engaged, the highest percentage of organizations that implemented the EBI were medium sized (N=8; 53.33%) as compared to small (N=1; 12.5%) and large (N=6; 35.3%). Small organizations served a significantly higher percentage of non-English speaking patients (32.96%) than larger organizations (16.62%) (F=6.84, p<.01). Logistic regression analyses indicated the odds of meeting with the research personnel were 3.7 times greater for large organizations as compared to small organizations (β =1.31; SE =561; p < .05).  

Conclusions and Implications: 

Findings demonstrate support that organizational size is related to adoption behavior and mattered at different stages of adoption. Harnessing publicly available data can be useful in determining organizational population characteristics and informing knowledge of relevant determinants and strategies for successful system-wide scale-up. This presentation will discuss key implications for the development of efficient implementation strategies with potential for preventing disparities in access to quality mental health care for children and families.