This study examines the impact of data-driven policy interventions on healthcare accessibility and infant mortality rates in Southern Ghana. Data-driven models were employed to analyse health service utilization patterns and identify disparities. A mixed-method approach combining quantitative survey data with qualitative interviews was used to validate findings. Analysis revealed that targeted interventions in maternal healthcare services led to a statistically significant reduction of infant mortality rates by 20% within the study period, with a 95% confidence interval indicating robust stability of results. The data-driven policy interventions demonstrated substantial success in enhancing health accessibility and reducing infant mortality. Further research is recommended to explore scalability and long-term sustainability. Policy makers are encouraged to implement continuous monitoring mechanisms and integrate community engagement strategies to sustain the positive impacts observed. Data-Driven Policy Interventions, Healthcare Accessibility, Infant Mortality Reduction, Southern Ghana Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.