Bringing together clinical and community partners for better patient care: Bootheel Perinatal Network
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A clinical–community integration framework recognizes six critical stakeholder groups: clinicians, community members and organizations, spanning personnel and infrastructure, national and/ or state leadership, local leaders, and funders. The Maternal and Child Health Bureau’s Rural Maternity and Obstetrics Management Strategies (RMOMS) program, piloted in 2019 by the Health Resources and Services Administration’s (HRSA) Federal Office of Rural Health Policy, was designed to address the need to strengthen access to services and to improve maternal outcomes in rural areas. The initial Notice of Funding Opportunity (NOFO) required four partners, including a minimum of two rural or critical access hospitals, one federally qualified health center (FQHC) or FQHC lookalike, the state-funded home visiting agency or the Healthy Start program if available, and the state Medicaid agency.6 These four required partners align with, and signal application of, a community–clinical integration framework. The Bootheel Perinatal Network (BPN), one of the first three funded RMOMS programs, is built on the clinical–community integration framework. This chapter highlights the BPN program as a case example of clinical–community integration. The discussion offers insights and considerations for other organizations interested in advancing critical work in maternal health with clinical and community partners.
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New York City's Local Law 144 of 2021 mandates bias audits for automated tools that make employment decisions in hiring and promotion.
“Most notably, New York City (NYC) enacted the Local Law 144 of 2021 ('NYC bias audit law' hereafter) in which bias audits-defined as independently conducted impartial evaluations-are required for automated employment decision tools used in hiring and promotion [75].”
From A Framework for Assurance Audits of Algorithmic Systems (2024) · cites this paper as [75]
Many laws, regulations, standardized frameworks, and industry guidelines have proposed auditing as a way to identify and mitigate AI harms and to build public trust and accountability.
“Auditing has been proposed in a variety of laws and regulations [17,22,23,25,42,52,75], 1 standardized frameworks [47,62], and guidelines for industry best practices [5,77] as a mechanism to identify and mitigate risks of harm in artificial intelligence (AI) 2and to build public trust and promote accountability for AI system developers and deployers.”
From A Framework for Assurance Audits of Algorithmic Systems (2024) · cites this paper as [75]
There is growing consensus that conflicts of interest between auditor and auditee in internal audits may undermine their purpose of providing assurance of trustworthiness or compliance to outside parties.
“There is a growing consensus that, with internal audits, conflicts of interest between the auditor and the auditee may undermine their purpose of providing the assurance of trustworthiness or compliance to outside parties [2,23,28,57,66,75].”
From A Framework for Assurance Audits of Algorithmic Systems (2024) · cites this paper as [75]
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Seznec, Y. (2024) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3677045.3685496 · Cited by 2 · see citing works
- Authors
- Lanford, D., Minyard, K., Alderman, L., Hemming, J., Parker, C., & Adimu, T.
- Venue
- Counseling And Psychological Services Dissertations (Georgia State University)
- Publisher
- Georgia State University
- Published
- 2024-01-01
- DOI
- 10.1093/oso
- OpenAlex
- W6922094438
- Cited by
- 138
- References
- 0
- Citations by year
- 2025: 6 · 2024: 84 · 2023: 32 · 2022: 5 · 2021: 9 · 2019: 2
- FWCI
- 52.86
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-nd
- Locations
- Counseling And Psychological Services Dissertations (Georgia State University) (submittedVersion, cc-by-nc-nd)
- Topics
- Health Sciences › Health Professions › General Health Professions › Community Health and Development
- Health Sciences › Health Professions › General Health Professions › Maternal and Neonatal Healthcare
- Health Sciences › Health Professions › General Health Professions › Interprofessional Education and Collaboration
- Keywords
- rural maternity care, maternal health, perinatal care, rural health, community health centers, home visiting, Medicaid, stakeholder collaboration, health care access, maternal outcomes
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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