ARTIFICIAL INTELLIGENCE–AUGMENTED CLINICAL DECISION SUPPORT IN NURSING AND ALLIED HEALTH CARE: EXAMINING TECHNOLOGICAL POTENTIAL, PRACTICAL LIMITATIONS, AND ETHICAL RESPONSIBILITIES WITHIN THE PAKISTANI HEALTHCARE FRAMEWORK

Abstract

The integration of Artificial Intelligence–augmented Clinical Decision Support Systems (AI-CDSS) into nursing and allied health care offers considerable potential to bolster health systems in low- and middle-income countries, yet remains critically under examined in contexts such as Pakistan. Drawing on a cross-sectional quantitative study of 342 frontline health professionals across six tertiary hospitals, and corroborated by objective clinical data from a 12-month pre–post implementation period, this research demonstrates that AI-CDSS significantly improved diagnostic accuracy for high-acuity conditions (from 78.3% to 91.2%, p < 0.001) and enhanced both workflow efficiency (β = 0.52) and professional autonomy (β = 0.38). Nevertheless, these gains were consistently constrained by infrastructural fragilities, particularly unreliable connectivity and non-interoperable systems, and profound ethical uncertainties surrounding data privacy and algorithmic accountability. The findings affirm that effective AI adoption in Pakistan hinges not on technical prowess alone, but on context-sensitive design, foundational digital investment, workforce preparedness, and a robust national ethics framework. This study advances an integrated socio-technical-ethical model to guide equitable, sustainable AI deployment in LMIC frontline care, an imperative for global health equity