MEASURING ELECTIVE SURGERY WAITING LISTS IN BRAZIL’S UNIFIED HEALTH SYSTEM: ANALYTICAL LIMITS

Abstract

The measurement of elective surgery waiting lists within Brazil’s Unified Health System (SUS) remains, in 2025, a technical, methodological, and institutional challenge widely recognized in the literature and in official documents of the Ministry of Health. Despite the implementation of federal programs aimed at reducing unmet surgical demand, such as the National Waiting List Reduction Program (PNRF) and the More Access to Specialists Program (PMAE), the SUS still lacks an integrated data infrastructure capable of systematically capturing, consolidating, and analyzing information on surgical requests, waiting times, and procedures performed. This article demonstrates that the main information systems currently used to manage elective surgery waiting lists—SISREG, SIH/SUS, e-SUS APS, and DRAC/DATASUS dashboards—suffer from structural fragmentation, inconsistent data entry, and low interoperability, which prevent the construction of reliable and auditable national time series. The absence of unique surgical request identifiers, heterogeneous municipal data reporting practices, and the lack of applied data science and artificial intelligence tools constitute critical bottlenecks in surgical regulation governance. Based on contemporary health data governance frameworks and international experiences, the study proposes a set of structural actions focused on national standardization, systemic integration, the use of machine learning, and data openness through public APIs. It concludes that, without profound reforms in the SUS information architecture, Brazil will remain unable to accurately measure unmet elective surgical demand, undermining evidence-based surgical planning and capacity management.