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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

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Lessons From One FQHC's Experience With Artificial Intelligence.

Grace Wang1, Sydney Kennedy, Meredith Johnson

  • 1Author Affiliations: Weitzman Institute, Moses-Weitzman Health System, Middletown, Connecticut (Dr Wang); and Community Health Center, Inc., Moses-Weitzman Health System, Middletown, Connecticut (Mr Kennedy, Ms Johnson, and Ms Avellino).

The Journal of Ambulatory Care Management
|December 1, 2025
PubMed
Summary
This summary is machine-generated.

Federally Qualified Health Centers (FQHCs) can build effective artificial intelligence (AI) programs by establishing dedicated workgroups and clear policies. This approach balances innovation with ethical considerations for AI implementation in healthcare.

Keywords:
artificial intelligencecommunity health centersorganization and administrationprimary health care

Related Experiment Videos

Last Updated: Jan 9, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

752

Area of Science:

  • Health Informatics
  • Artificial Intelligence in Healthcare
  • Health Systems Management

Background:

  • The rapid advancement of artificial intelligence (AI) presents both opportunities and challenges for healthcare systems.
  • Safety-net providers, such as Federally Qualified Health Centers (FQHCs), require structured approaches to assess and implement AI applications.
  • Moses-Weitzman Health System (MWHS) initiated steps to develop an AI program for intentional and informed AI use.

Purpose of the Study:

  • To describe the initial steps taken by MWHS in establishing an AI program.
  • To outline a framework for assessing and implementing AI tools within a safety-net health system.
  • To provide a model for other FQHCs embarking on AI integration.

Main Methods:

  • Established two AI-focused workgroups: a senior leadership group and a cross-departmental group.
  • Developed a comprehensive AI policy emphasizing transparency, privacy, security, and regulatory compliance.
  • Focused initial AI projects on automating routine tasks and exploring evidence frameworks for AI adoption.

Main Results:

  • Effective AI program implementation necessitates tech-savvy leadership and cross-departmental collaboration.
  • Differentiating between general automation and generative AI is crucial for cautious implementation.
  • Key challenges include agile budgeting, vendor vetting, and establishing safe testing environments.

Conclusions:

  • MWHS's AI program demonstrates a proactive yet cautious approach to AI adoption in healthcare.
  • Balancing innovation with operational and ethical considerations is paramount.
  • The MWHS model offers valuable insights for other safety-net systems developing their AI strategies.