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The Bridge “Artificial Intelligence” Over the “Healthcare Quality” Lake

Year: 2025

Type: article

Abstract: The pandemic, aging population, and legacy healthcare delivery systems have severely impacted health care, and there is a need to deliver high-quality care by leveraging real-world data-driven insights directly into patient care. Several artificial intelligence (AI)-assisted tools have been adopted to empower clinical decision-making, optimize operations, refine medical image analysis, and monitor patients using AI-powered wearables. AI systems rely on the data they are trained on. Training data that lack representativity, inclusivity, and diversity are often biased and can generate biased AI outcomes. It is important to limit algorithm bias, ensure developmental transparency, enhance data security, and facilitate equitable access for the healthcare industry to harness AI benefits when minimizing its potential challenges. Balancing innovation with caution is critical for clinicians to ensure that the AI bridge over the healthcare quality lake is crossed successfully, without harm.

Source: QAI Journal for Healthcare Quality and Patient Safety

DOI: 10.4103/qaij.qaij_11_25

Authors: Satish Chandrasekhar Nair, Nellie Boma, Pratheesh Ravindran, Chinmay Shah, Lallu Joseph, Karthyayani Priya Satish, Ebinesh Antony

Institutions: United Arab Emirates University, Tawam Hospital, Abu Dhabi Health Services, Al Ain Hospital, Mahatma Gandhi Medical College and Research Institute, Government Medical College Bhavnagar, Christian Medical College, Vellore, Kasturba Medical College, Mangalore

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Reduced inequalities

Open Access status: hybrid

OpenAlex ID: W4411219930

FWCI:

Cites: 9

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Related to: 10