Integrating Artificial Intelligence with General Practitioners to Improve Equity in Basic Public Health Services in Medically Underserved Areas
1
Peking University Shenzhen Hospital, Shenzhen, China
2
Shenzhen Young Physicians Club, Shenzhen, China
3
The University of Hong Kong Shenzhen Hospital, Shenzhen, China
4
Shenzhen Health Capacity Building and Continuing Education Center, Shenzhen, China
Popul. Med. 2026;8(Supplement Supplement 1):A968
ABSTRACT
INTRODUCTION:
Medically underserved areas face dual challenges: a shortage of general practitioners and deepening health inequities. While artificial intelligence holds transformative potential, it also risks exacerbating inequities through algorithmic bias and the digital divide.
METHODS:
We conducted a systematic evidence synthesis using literature retrieved from PubMed (2016–2026) on AI and equity in GP-led public health. Studies were included if they focused on resource-limited settings and GP-driven interventions. Thematic analysis was performed across three dimensions: technical feasibility (e.g., lightweight tools), ethical risks (e.g., algorithmic bias), and implementation pathways (e.g., community co-governance). Evidence was appraised using WHO equity frameworks.
RESULTS:
Key findings include: 1. Technical adaptation: Mobile AI tools improve service accessibility, but hardware dependence limits rural coverage. 2. Ethical mitigation: GP-led data governance models reduce the risk of algorithmic bias. 3. Core paradox: Digital literacy gaps constrain benefits for vulnerable groups, necessitating complementary non-technical supports.
CONCLUSIONS:
General practitioners are pivotal for equitable AI integration. We propose a four-pillar framework: needs-driven tool design, training AI on culturally diverse datasets, integrating offline-accessible technologies, and legislative empowerment of patients. This framework provides an evidence-informed basis for global health policy formulation.
Medically underserved areas face dual challenges: a shortage of general practitioners and deepening health inequities. While artificial intelligence holds transformative potential, it also risks exacerbating inequities through algorithmic bias and the digital divide.
METHODS:
We conducted a systematic evidence synthesis using literature retrieved from PubMed (2016–2026) on AI and equity in GP-led public health. Studies were included if they focused on resource-limited settings and GP-driven interventions. Thematic analysis was performed across three dimensions: technical feasibility (e.g., lightweight tools), ethical risks (e.g., algorithmic bias), and implementation pathways (e.g., community co-governance). Evidence was appraised using WHO equity frameworks.
RESULTS:
Key findings include: 1. Technical adaptation: Mobile AI tools improve service accessibility, but hardware dependence limits rural coverage. 2. Ethical mitigation: GP-led data governance models reduce the risk of algorithmic bias. 3. Core paradox: Digital literacy gaps constrain benefits for vulnerable groups, necessitating complementary non-technical supports.
CONCLUSIONS:
General practitioners are pivotal for equitable AI integration. We propose a four-pillar framework: needs-driven tool design, training AI on culturally diverse datasets, integrating offline-accessible technologies, and legislative empowerment of patients. This framework provides an evidence-informed basis for global health policy formulation.
| eISSN: | 2654-1459 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
