Authors:
Aaron R. Lyon, Tricia Aung, Kathryn E. Bruzios, and Sean Munson
University of Washington affiliated authors are displayed in bold.
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Published: December 2024
Aaron R. Lyon, Tricia Aung, Kathryn E. Bruzios, and Sean Munson
University of Washington affiliated authors are displayed in bold.
Published: December 2024
Courtney A. Zulauf-McCurdy, Margaret Johansson, Jasmine Rose Hashimoto & Rosemary D. Meza
University of Washington affiliated authors are displayed in bold.
Published: December 2024
Patricia Mae G. Santos, Sierra Silverwood, Gita Suneja, Eric C. Ford, Nikhil G. Thaker, Jamie S. Ostroff, Bryan J. Weiner, and Erin F. Gillespie
University of Washington affiliated authors are displayed in bold.
Published: December 2024
Harriette G.C. Van Spall, Laura Desveaux, Tracy Finch, Cara C. Lewis, George A. Mensah, Yves Rosenberg, Kavita Singh, Francois Venter, Bryan J. Weiner, Faiez Zannad
University of Washington affiliated authors are displayed in bold.
Published: November 2024
Xinnian Lin, Chen Liang, Jihong Liu, Tianchu Lyu, Nadia Ghumman & Berry Campbell
University of Washington affiliated authors are displayed in bold.
Published: September 2024
Despite the emerging application of clinical decision support systems (CDSS) in pregnancy care and the proliferation of artificial intelligence (AI) over the last decade, it remains understudied regarding the role of AI in CDSS specialized for pregnancy care.
To identify and synthesize AI-augmented CDSS in pregnancy care, CDSS functionality, AI methodologies, and clinical implementation, we reported a systematic review based on empirical studies that examined AI-augmented CDSS in pregnancy care.
We retrieved studies that examined AI-augmented CDSS in pregnancy care using database queries involved with titles, abstracts, keywords, and MeSH (Medical Subject Headings) terms. Bibliographic records from their inception to 2022 were retrieved from PubMed/MEDLINE (n=206), Embase (n=101), and ACM Digital Library (n=377), followed by eligibility screening and literature review. The eligibility criteria include empirical studies that (1) developed or tested AI methods, (2) developed or tested CDSS or CDSS components, and (3) focused on pregnancy care. Data of studies used for review and appraisal include title, abstract, keywords, MeSH terms, full text, and supplements. Publications with ancillary information or overlapping outcomes were synthesized as one single study. Reviewers independently reviewed and assessed the quality of selected studies.
We identified 30 distinct studies of 684 studies from their inception to 2022. Topics of clinical applications covered AI-augmented CDSS from prenatal, early pregnancy, obstetric care, and postpartum care. Topics of CDSS functions include diagnostic support, clinical prediction, therapeutics recommendation, and knowledge base.
Our review acknowledged recent advances in CDSS studies including early diagnosis of prenatal abnormalities, cost-effective surveillance, prenatal ultrasound support, and ontology development. To recommend future directions, we also noted key gaps from existing studies, including (1) decision support in current childbirth deliveries without using observational data from consequential fetal or maternal outcomes in future pregnancies; (2) scarcity of studies in identifying several high-profile biases from CDSS, including social determinants of health highlighted by the American College of Obstetricians and Gynecologists; and (3) chasm between internally validated CDSS models, external validity, and clinical implementation.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Christopher G. Kemp (Ngāi Tahu), Abagail J. Edwards, Lauren White (Choctaw Nation of Oklahoma), Gauri Kore, Pamela Jumper Thurman (Cherokee), Tommi Gaines (Navajo, Hopi), Paula Toko King (Te Aupōuri, Te Rarawa, Ngāpuhi, Ngāti Whātua, Waikato Tainui, Ngāti Maniapoto), Marama Cole (Ngāti Kahungunu, Ngāti Porou) & E. Roberto Orellana (Maya)
University of Washington affiliated authors are displayed in bold.
Published: August 2024
We systematically reviewed implementation research conducted in Indigenous communities in the Americas and the Pacific that focused on improving delivery of HIV preventive or treatment services. We highlight strengths and opportunities in the literature and outline principles for Indigenous-led, HIV-related implementation science.
We identified 31 studies, revealing a consistent emphasis on cultural tailoring of services to Indigenous communities. Common barriers to implementation included stigma, geographic limitations, confidentiality concerns, language barriers, and mistrust. Community involvement in intervention development and delivery emerged as a key facilitator, and nearly half of the studies used community-based participatory research methods. While behavioral HIV prevention, especially among Indigenous youth, was a major focus, there was limited research on biomedical HIV prevention and treatment. No randomized implementation trials were identified.
The findings underscore the importance of community engagement, the need for interventions developed within Indigenous communities rather than merely adapted, and the value of addressing the social determinants of implementation success. Aligned to these principles, an indigenized implementation science could enhance the acceptability and reach of critical HIV preventive and treatment services in Indigenous communities while also honoring their knowledge, wisdom, and strength.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
M Carter Denny, Nicole Rosendale, Nicole R Gonzales, Thabele M Leslie-Mazwi, & Sandy Middleton
University of Washington affiliated authors are displayed in bold.
Published: March 2024
There are now abundant data demonstrating disparities in acute stroke management and prognosis; however, interventions to reduce these disparities remain limited. This special report aims to provide a critical review of the current landscape of disparities in acute stroke care and highlight opportunities to use implementation science to reduce disparities throughout the early care continuum. In the prehospital setting, stroke symptom recognition campaigns that have been successful in reducing prehospital delays used a multilevel approach to education, including mass media, culturally tailored community education, and professional education. The mobile stroke unit is an organizational intervention that has the potential to provide more equitable access to timely thrombolysis and thrombectomy treatments. In the hospital setting, interventions to address implicit biases among health care providers in acute stroke care decision‐making are urgently needed as part of a multifaceted approach to advance stroke equity. Implementing stroke systems of care interventions, such as evidence‐based stroke care protocols at designated stroke centers, can have a broader public health impact and may help reduce geographic, racial, and ethnic disparities in stroke care, although further research is needed. The long‐term impact of disparities in acute stroke care cannot be underestimated. The consistent trend of longer time to treatment for Black and Hispanic people experiencing stroke has direct implications on long‐term disability and independence after stroke. A learning health system model may help expedite the translation of evidence‐based interventions into clinical practice to reduce disparities in stroke care.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Jessica E. Tschida, James D. Lee, Anamiguel Pomales-Ramos, Vivien Koo
University of Washington affiliated authors are displayed in bold.
Published: February 2024
There is minimal research on the quality of community partnerships in studies of interventions for autistic children. However, building high quality community engagement in autism intervention research may improve implementation outcomes. This systematic review examined studies that report community partnership in autism intervention research. A total of 135 articles were identified and 11 of these articles were included in the final review. Community partnership data were extracted using indicators from the conceptual framework for assessing research-practice partnerships (RPP; Henrick et al., Henrick et al., Assessing research-practice partnerships: Five dimensions of effectiveness, William T. Grant Foundation, 2017) and implementation outcomes data were extracted using the taxonomy of distinct implementation outcomes (Proctor et al., Administration and Policy in Mental Health and Mental Health Services Research, 38:65–76, 2011). Quality of studies were appraised using JBIs critical appraisal tools (Munn et al., JBI Evidence Synthesis, 18:2127–2133, 2020). RPP indicators and implementation outcomes were variably reported across studies. RPP indicators and implementation outcomes more likely to be reported were related to building trust, cultivating partnership relationships, conducting rigorous research to inform action, acceptability, and feasibility. RPP indicators and implementation outcomes less likely to be reported were related to building capacity to engage in partnership work, sustainability, cost, and penetration. Together, these results may suggest the need for increased sustainability and capacity building efforts in partnerships and increased guidelines for reporting outcomes.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Sonja Klingberg, Bipin Adhikari, Catherine E Draper, Edna Bosire, Deborah Nyirenda, Priscilla Tiigah, & Ferdinand C Mukumbang
University of Washington affiliated authors are displayed in bold.
Published: February 2024
Community engagement and participatory research are widely used and considered important for ethical health research and interventions. Based on calls to unpack their complexity and observed biases in their favour, we conducted a realist review with a focus on non-communicable disease prevention. The aim was to generate an understanding of how and why engagement or participatory practices enhance or hinder the benefits of non-communicable disease research and interventions in low- and middle-income countries.
We retroductively formulated theories based on existing literature and realist interviews. After initial searches, preliminary theories and a search strategy were developed. We searched three databases and screened records with a focus on theoretical and empirical relevance. Insights about contexts, strategies, mechanisms and outcomes were extracted and synthesised into six theories. Five realist interviews were conducted to complement literature-based theorising. The final synthesis included 17 quality-appraised articles describing 15 studies.
We developed six theories explaining how community engagement or participatory research practices either enhance or hinder the benefits of non-communicable disease research or interventions. Benefit-enhancing mechanisms include community members’ agency being realised, a shared understanding of the benefits of health promotion, communities feeling empowered, and community members feeling solidarity and unity. Benefit-hindering mechanisms include community members’ agency remaining unrealised and participation being driven by financial motives or reputational expectations
Our review challenges assumptions about community engagement and participatory research being solely beneficial in the context of non-communicable disease prevention in low- and middle-income countries. We present both helpful and harmful pathways through which health and research outcomes are affected. Our practical recommendations relate to maximising benefits and minimising harm by addressing institutional inflexibility and researcher capabilities, managing expectations on research, promoting solidarity in solving public health challenges and sharing decision-making power.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Terren Green, Hayden B. Bosworth, Gloria D. Coronado, Lynn DeBar, Beverly B. Green, Susan S. Huang, Jeffrey G. Jarvik, Vincent Mor, Douglas Zatzick, Kevin P. Weinfurt & Devon K. Check
University of Washington affiliated authors are displayed in bold.
Published: January 2024