Implementation Science and Health Disparities: The Quality Gap Is Still Here
by Ana Baumann, PhD, Research Assistant Professor, Brown School
Racial and ethnic minorities in the United States continue to face serious mental health care disparities, receiving lower quality care and completing treatment less often than their non-Hispanic white counterparts. (1,2)
Mental health care disparities are complex, in large part because factors that contribute to disparities occur at a variety of levels and include individuals, families, providers, organizations, communities, and economic and political factors.
The implementation science field was developed with the goal of diminishing the quality gap between the best available interventions that could be implemented and the treatment/interventions/care people actually receive.
The field has been extremely active, supporting the movement of evidence-based interventions into routine use by developing and testing implementation strategies, measures, and theoretical frameworks. We have a journal, an annual conference, a couple of training institutes, and numerous interest groups that reach national and international audiences.
Yet, we have not done enough to decrease the quality gap, particularly related to racial and ethnic minorities. So what is missing in this picture? Why are not decreasing the disparities in care?
There is not a single answer, but we can brainstorm about a couple of factors:
There are two silent assumptions in the field that can be dangerous for racial and ethnic minority communities:
- There is an assumption that if an intervention has been proven to be efficacious and effective, its implementation in any setting would decrease the quality gap. What is not openly discussed in the field is the fact that an intervention developed for one population, in one particular setting may not be appropriate for another population in either the same setting or on a different one. The danger of this assumption relies on the “blaming” aspect: if the implementation of an intervention fails, it is easy to “blame” on the population (e.g., we could not recruit; it was hard to retain our sample; our sample did not like this component of the intervention) rather than on the intervention or on the implementation process. Considering that meta-analysis have shown that adapting interventions make a difference in recruitment, retention and on client outcomes, we need to think more deeply on what are we implementing, how and to whom we are implementing the evidence-based interventions.
- Partly because we are not attending to the cultural context of our implementation process, another silent assumption in our field is that “adaptations happen” when an intervention is transposed from one setting to another. Adaptations to the intervention or to the implementation process are usually not documented and, consequently, not tested. The problem with the lack of documentation? Replicating interventions and the implementation process ends up being extremely challenging because no one setting is exactly the same as another and no one knows what works best to whom.
Implementation outcomes are crucial in the implementation process because they have a direct impact on clinical outcomes: for an intervention to be effective, it needs to be implemented well. The field is growing and we have a couple of national initiatives categorizing D&I outcome measures, such as SIRC and GEM. Our ICTS DIRC Core has also compiled measures and provides consultation around measurement and designs for D&I.
Silent in the measurement discussion, however, is the external validity of these measures: how are they being used for different populations and in different contexts? How and by whom are they being adapted? We know that a measure developed and tested for one population may not hold the same psychometric properties when used for another population. More discussion around cultural context may be needed when developing databases of implementation outcome measures.
Recruitment of minority participants
While we are doing better in recruiting American Indians/Native Americans, the numbers of minorities in the funded studies is a far reach from the current minority population (13% for Hispanics, 17% for African American/Black, and 1% for American Indian/Native American), despite NIH’s guiding principle to decrease disparities in the US. (3)
Table 1 below shows a summary of minority participants recruited in studies from NIMH, NIDA, and NIAAA. With such numbers, it is hard to generalize our findings to minority populations when they are not present in our studies. Add this context to the fairly few D&I studies funded by each institute and we certainly have a problem of generalizability.
In summary, if our goal is to decrease the quality gap, we need to do a better job attending to the context of our research. Solutions to the problem are complex and varied:
- The implementation science field could benefit from the lessons learned and frameworks developed to adapt interventions from the cultural adaptation field. (5) Frameworks will give us guidance on pre-planning and on-the-spot adaptation, helping us document and test the adaptation process;
- We could use more community-based participatory research (CBPR), allowing for clear input from racial and ethnic communities in our studies;
- Use methodologies that allow for rapid usability testing, so researchers can test the fit of the intervention in different settings in short periods of time. (6)
This is only a conversation-starter for the D&I community. The stakes of implementation science is high and we need to attend more to the contextual aspects of the implementation process. (7)
Much more needs to be discussed and addressed to be able to decrease the current racial and ethnic disparities gap. But that is the beauty of the (implementation and dissemination) science: we grow, one step at a time, to make this world a better place to be.
This post is part of the April 2016 “Dissemination & Implementation” series of the Institute for Public Health’s blog. Subscribe to email updates or follow us on Twitter and Facebook to receive notifications about our latest blog posts.
1. US Department of Health and Human Services. Mental Health: Culture, Race, and Ethnicity—A Supplement to Mental Health: A Report of the Surgeon General. (Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, 2001).
2. Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. (2003).
3. Census, US. State and county QuickFacts: data derived from population estimates. (Census of Population and Housing, 2014).
4. National Research Council and Institute of Medicine. Preventing Mental, Emotional, and Behavioral Disorders Among Young People: Progress and Possibilities. (The National Academies Press, 2009).
5. Cabassa, L. J. & Baumann, A. A. A two-way street: Bridging implementation science and cultural adaptations of mental health treatments. Implement. Sci. 8, 90 (2013).
6. Lyon, A. R. & Koerner, K. User-Centered design for psychosocial intervention development and implementation. Clin. Psychol. Sci. Pract. (in press).
7. Sampson, U. K. et al. Implementation Research: The Fourth Movement of the Unfinished Translation Research Symphony. Glob. Heart 11, 153–158 (2016).Tags: dandi, health disparities, implementation science, racial disparities