<p>Search strategy for Ovid MEDLINE.</p>

Two independent reviewers will screen titles, abstracts, and full texts. Eligible studies include empirical research describing, evaluating, implementing, or developing AI and ML applications at the meso-level (organizational, e.g., care scheduling, population stratification) and macro-level (system-wide, e.g., workforce planning, funding allocation) of PHC. Studies on micro-level clinical applications, non-empirical research, and secondary literature will be excluded.

Applications will be classified using a two-layer taxonomy (AI technique family and core algorithm) and mapped to PHC building blocks adapted from WHO operational frameworks. Synthesis will examine technique-building block intersections, application purposes, data sources, implementation maturity, and evidence gaps. The protocol is registered in Open Science Framework (osf.io/wzj5x).</p> <p>Conclusions</p><p>This review will provide a timely synthesis of AI and ML applications at organizational and system levels of PHC, identifying which building blocks have been addressed, which remain underexplored, and where the field stands in terms of implementation readiness.

The findings will inform a targeted research agenda and provide actionable evidence for decision-makers seeking to leverage AI and ML for PHC strengthening.</p></div>