Retrospective Analysis of Hospitalization Patterns in Peru: Insights on Inpatient Resource Utilization

Abstract

This study addresses the inequality in hospital resource distribution in Peru using Data Mining techniques. Analyzing hospitalization data from 2018 to 2022, we employed K-means, Linear Discriminant Analysis (LDA), and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to identify patterns in hospital resource availability and inpatient service demand across different regions. Our findings reveal significant disparities, with resources concentrated in high-population urban areas, particularly Lima, and a predominance of public sector healthcare provision in inpatient settings. We identified potential saturation issues in departments like Lima and Arequipa, and substantial geographical discrepancies between inpatient care demand and hospital resource availability. Based on these insights, we propose targeted interventions to improve equity in hospital resource distribution, including resource redistribution and strengthening private sector capacity in underserved areas. This research provides valuable information for hospital policy planning and contributes to the broader goal of achieving equitable access to inpatient care in Peru.