De-medicalizing medication abortion: Understanding provider perspectives
Awarded 2019
Complex Family Planning Fellowship Research
Jennifer Karlin, MD, PHD, MA
University of California, San Francisco

This qualitative study will explore abortion providers’ perspectives about self-managed medication abortion (SMMA) in the United States (US).

Background: Recent studies have documented that 4-11% of ever-pregnant women in the US have attempted to end their pregnancy without formal medical assistance. Further, an unpublished national survey indicates that 23% of women are interested in some form of SMMA for themselves (advanced provision, over-the-counter or online provision of medications) and 45% would like these options to be available for other women (personal communication, Dan Grossman; please do not disseminate information). Across the world, there has been success with out-of-clinic models (using both phone hotline and online models) that employ community workers—rather than licensed clinicians—to support women through a SMMA. SMMA has the potential to increase access to abortion in the context of ongoing restrictions to clinic abortion due to the political climate on both the state and federal level in the US. This potential can only be realized if we recognize the history of medicalization of abortion in the 20th Century in which the medical profession consolidated its expertise by excluding other providers from practice and by alluding to dangerous non-clinic based abortions. Given the recent evidence that medication abortion has similar rates of completed abortion with few adverse events with and without clinical supervision, some providers are changing their assumptions about de-medicalizing medication abortion and a few randomized trials are underway to evaluate different models for supporting women with SMMA. However, besides this small group of providers and family planning advocates leading these efforts, we do not understand what abortion providers know about supporting women with SMMA, and we do not understand how this aligns with their values and norms around providing abortion care. As provider support will be critical to the success of efforts to disseminate models of SMMA, to provide thorough options counseling and to care for women after SMMA, understanding these providers’ perspectives can inform work to overcome barriers to this support.

Methods: This study will use qualitative interviews with a minimum of 30-35 (and until saturation of themes is reached) abortion providers. Providers will be chosen to ensure sampling is from the following: academic and non-academic practice location, border and non-border states, hostile and non-hostile states, and across multiple generations of providers. Interviews will explore providers’ concerns about SMMA (and its various models) as well as identify their perceived benefits to these models. Interviews will invite providers to reflect on their values and motivations for abortion provision and will assess how aspects of SMMA compare with their values. Interviews will inquire about the frameworks upon which providers draw when they think about supporting SMMA including those of harm-reduction, patient-centered care, de-medicalization, racial justice, menstrual regulation, self-empowerment, or other frameworks generated through the interviews. Finally, interviews will query what providers think we should do about decreasing access and abortion restriction in the US and how we can improve provider support for SMMA.

Aims: Analysis of interviews will aim to delineate potential areas of concerns/benefits that have not yet been recognized about SMMA from the provider perspective. We will gain an understanding of the norms and biases that abortion providers hold in addition to learning about their values and ways that they frame the de-medicalizing of medication abortion. Through integrating this information with what is known about changing provider values, norms and behavior, this research can contribute to work to promote provider support for efforts to advance evidence-based models of SMMA.