Temporal costs of access to formal health care among adult users in Peru: a national analysis of inequalities in travel and waiting times, 2016–2024
Vera-Ponce V.J.; Ballena-Caicedo J.; Portal-Valqui L.M.; Yoplac-Oyarce A.M.; Cusma-Regalado K.; Cervera Vasquez N.J.; Zuzunaga-Montoya F.E. · Frontiers in Health Services (2026) · DOI: 10.3389/frhs.2026.1864862
Resumen
Introduction – The time spent accessing health care, both in travel and in waiting, represents a poorly monitored dimension of inequity in health systems. This study estimated territorial and socioeconomic inequalities in travel and waiting times in Peru from 2016 to 2024 among adults who attended formal health care facilities. Methods – We analyzed nine rounds of the Peruvian National Household Survey (ENAHO) using a repeated cross-sectional design. The main sample included adults who attended formal facilities and had valid simultaneous information on travel time and waiting time. The outcomes were travel time?>60 min, waiting time?>60 min, and poor access, defined as both travel and waiting times?>60 min. Weighted prevalences and adjusted prevalence ratios (aPRs) were estimated. Results – The prevalence of travel time >60 min was 4.0% in Metropolitan Lima, 4.2% in other urban areas, and 11.3% in rural areas (rural vs. Lima aPR: 3.32; 95% CI: 2.92–3.79). The pattern was reversed for waiting time >60 min: 22.2% in Metropolitan Lima, 21.8% in other urban areas, and 9.2% in rural areas (rural aPR: 0.40; 95% CI: 0.37–0.43). Poor access was uncommon but showed a consistent territorial gradient. Acceptable waiting time and optimal access improved through 2022 and then declined in 2023–2024. Discussion – Among adult users who successfully accessed formal facilities, temporal inequities in Peru operate in opposite directions: rural disadvantage is concentrated in travel time, whereas urban disadvantage is concentrated in waiting time. Equity policies should distinguish geographic from organizational barriers and incorporate time-based indicators into routine health-system monitoring.
Instituciones: Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas