Bio

Dr. Mieso is a pediatrics-trained fellow in the Stanford University Clinical Informatics Fellowship Program, where she focuses on advancing child health equity and physician wellness. Her career has been marked by a commitment to addressing health disparities and advocating for systemic improvements in patient care and medical workforce conditions. She has held various leadership roles and played a crucial part in promoting diversity, equity, and inclusion (DEI) initiatives.

In her current fellowship, Dr. Mieso is leveraging her DEI expertise in clinical informatics, aiming to develop digital tools that enhance patient outcomes and experience. Her goal is to merge her informatics skills and advocacy experience to drive innovations that improve healthcare delivery, promote a more equitable and efficient system, and streamline electronic health record (EHR) systems to reduce provider burnout. Dr. Mieso holds a BS in Biology from San Jose State University, an MD from Case Western Reserve University School of Medicine, and completed her pediatrics residency at Stanford.

Clinical Focus

  • Fellow
  • Clinical Informatics
  • General Pediatrics

Boards, Advisory Committees, Professional Organizations

  • Member, American Medical Informatics Association (2023 - Present)
  • Member, American Academy of Pediatrics (2021 - Present)

Professional Education

  • Fellowship, Stanford University, Clinical Informatics
  • Residency, Stanford University, Lucile Packard Children's Hospital (2024)
  • MD, Case Western Reserve University School of Medicine (2021)
  • Bachelor of Science, San Jose State University, Biology (2014)

Links

All Publications

  • Decoding the Reference Letter: Strategies to Reduce Unintentional Gender Bias in Letters of Recommendation. MedEdPORTAL : the journal of teaching and learning resources Mieso, B. R., Barnett, J. F., Otero, T. M., Berquist, S. W., Perez, F. D., Han, P., Bhargava, S., Atasuntseva, A., Yemane, L. 2024; 20: 11419

    Abstract

    There is a growing body of literature on gender bias in letters of recommendation (LORs) in academic medicine and the negative effect of bias on promotion and career advancement. Thus, increasing knowledge about gender bias and developing skills to mitigate it is important for advancing gender equity in medicine. This workshop aims to provide participants with knowledge about linguistic bias (focused on gender), how to recognize it, and strategies to apply to mitigate it when writing LORs.We developed an interactive 60-minute workshop for faculty and graduate medical education program directors consisting of didactics, reflection exercises, and group activities. We used a postworkshop survey to evaluate the effectiveness of the workshop. Descriptive statistics were used to analyze Likert-scale questions and a thematic content analysis for open-ended prompts.We presented the workshop four times (two local and two national conferences) with one in-person and one virtual format for each. There were 50 participants who completed a postworkshop survey out of 74 total participants (68% response rate). Ninety-nine percent of participants felt the workshop met its educational objectives, and 100% felt it was a valuable use of their time. Major themes described for intended behavior change included utilization of the gender bias calculator, mindful use and balance of agentic versus communal traits, closer attention to letter length, and dissemination of this knowledge to colleagues.This workshop was an effective method for helping participants recognize gender bias when writing LORs and learn strategies to mitigate it.

    View details for DOI 10.15766/mep_2374-8265.11419

    View details for PubMedID 38974126

    View details for PubMedCentralID PMC11224141

  • Mobile Phone Applications to Support Breastfeeding Among African-American Women: a Scoping Review. Journal of racial and ethnic health disparities Mieso, B., Neudecker, M., Furman, L. 2022; 9 (1): 32-51

    Abstract

    Racial disparities persist with respect to breastfeeding. The use of health e-technology is increasing, with promise for a role in improving breastfeeding outcomes.We undertook a scoping review of both individual breastfeeding apps and the literature on breastfeeding apps to map the available evidence on app-based breastfeeding support for African-American mothers.A systematic search of online databases identified 241 English language papers published on or before June 2020 that included e-technology in support of breastfeeding. We included those that (1) described individual human subjects research studies utilizing any research design, (2) described app-based breastfeeding support, and (3) could be pertinent for African-American mothers, and assessed for inclusion and relevance for this population. We also searched app stores for breastfeeding apps, and evaluated features with a rubric. Our aim was to identify if gaps exist relative to breastfeeding support for African-Americans.Of the 15 publications meeting inclusion criteria, 9 focused on app development, 4 examined user experience, and 3 examined breastfeeding outcomes with use of an app (one study overlapped categories). The percentage of African-American participants ranged from 100% (2 studies) to none (7 studies); 3 studies (20%) focused on African-American mothers' breastfeeding experience. Of 77 apps that met inclusion criteria, just one was both breastfeeding-focused by content and targeted for African-Americans by picture predominance.The quality of studies was generally high and many included African-American participants, but research focused on breastfeeding apps specifically for African-American mothers/parents is limited, creating a meaningful gap in the literature.

    View details for DOI 10.1007/s40615-020-00927-z

    View details for PubMedID 33219430

    View details for PubMedCentralID 6715261

  • Beyond Statistics: Uncovering the Roots of Racial Disparities in Breastfeeding. Pediatrics Mieso, B. R., Burrow, H., Lam, S. K. 2021; 147 (5)

    View details for DOI 10.1542/peds.2020-037887

    View details for PubMedID 33833073