Building trust through collaboration: a mixed-methods evaluation of San Francisco’s Pregnancy Village model of cross-sector care delivery
Osamuedeme J. Odiase, April J. Bell, Alison M. El Ayadi, Catherine Ravikumar, Kattia Suarez Vargas, KaSelah Crockett, Malini A. Nijagal, Patience A. Afulani

TL;DR
This study evaluates how San Francisco's Pregnancy Village model builds trust in healthcare through collaboration with community organizations, especially in marginalized communities.
Contribution
The study introduces a mixed-methods evaluation of a cross-sector care model aimed at building institutional trust in historically marginalized communities.
Findings
Participants showed high trust in the Pregnancy Village model, with mean trust score of 85.9/100.
Trust was lower among Latine participants, those with prior preterm birth, and those with food insecurity.
Qualitative data showed that trust in CBOs was due to holistic care and responsiveness, while distrust in the health system stemmed from racism and neglect.
Abstract
Historical injustices, systemic racism, unequal healthcare access, and provider bias have fostered mistrust in healthcare institutions. Cross-sector collaborations between healthcare institutions and community-based organizations (CBOs), such as San Francisco’s Pregnancy Village (PV) model, could potentially build institutional trust within minoritized communities. This study primarily aimed to examine trust in PV, with secondary aims exploring participant perceptions of trust in the health system and CBOs, including their views on the health system’s involvement in PV. Between July 2021 and June 2022, we conducted a convergent, mixed-methods study involving 116 survey participants (57 pregnant/postpartum individuals and 59 family members) and 18 semi-structured interviews (13 pregnant/postpartum people and five family members). Trust was assessed quantitatively using a seven-item…
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Taxonomy
TopicsGlobal Maternal and Child Health · Migration, Health and Trauma · Reproductive Health and Contraception
