Strengthening Essential Health Services Recovery Policy after the COVID-19 Pandemic. Evidence from the Mexican Institute of Social Security

Aim. To evaluate the progress of the Mexican Institute of Social Security Recovery Policy (IMSS-RP) in addressing the decline in essential health services caused by the COVID-19 pandemic. Methods. We analyzed eleven indicators of essential health services from 35 IMSS state delegations. The assessment included ambulatory and hospital care indicators such as breast and cervical cancer screening, family medicine, dental and specialty visits, diabetes and hypertension visits and health outcomes, deliveries, and elective surgeries. We analyzed the period before (January 2018-March 2021) and during (April 2021- June 2023) the implementation of the IMSS-RP. Statistical analysis to determine the association of the policy with service indicators and the change in their trends included an interrupted time series analysis and Poisson Generalized Estimating Equation models. Results. The volume of services showed substantial declines during the first year of the COVID-19 pandemic, reaching between 11 and 81% of pre -pandemic levels. All services increased significantly during the first 27 months of the IMSS-RP implementation; specialty visits, cervical and breast cancer screening, and diabetes control exceeded pre -pandemic levels (103%,112%,103%, and 138%, respectively). However, only deliveries and the percentage of patients with controlled diabetes and hypertension showed a stable increase following the IMSS-RP implementation, whereas the remaining services showed an initial increase but began to decrease over time. Conclusions. After 27 months of implementation, IMSS-RP achieved progress in increasing the volume of essential health services and improving chronic disease control. However, declining trends in several services signal the need to focalize the policy. (c) 2024 Instituto Mexicano del Seguro Social (IMSS). Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.