Interventions to increase adherence to cervical cancer early detection and treatment recommendations in Mexico City clinics

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Project summary/Abstract Despite being highly preventable, stark cervical cancer (CC) disparities exist globally. CC is the second leading cause of cancer mortality among Mexican women, where CC detection, diagnosis, and treatment delays result from suboptimal implementation of and adherence to longstanding Mexican early detection, diagnosis, and treatment guidelines, which have been in existence since 1974. In contrast, CC is the 12th leading cause of cancer mortality among women in the US, where evidence about patient, provider, and health care organizational factors associated with adherence to CC early detection and diagnosis recommendations likely associated with the success of CC control programs has accrued. In Mexico, screening rates are suboptimal (50-67%), in contrast to 80% in the US, and follow-up colposcopy among Mexican women with abnormal screens is 43%, in contrast to around 66%-71% in the US. In response to NOT-CA-20-025 Notice of Special Interest (NOSI): Dissemination and Implementation Science for Cancer Prevention and Control in Low Resource Environments, we propose to identify barriers to and facilitators of adherence to the Mexican guidelines for follow-up from an abnormal screen onward down the CC care cascade (MGMACS, Mexican Guidelines for Managing Abnormal Cervical Cancer Screening Tests), and to develop strategies to increase adherence to these guidelines in clinics in Tlalpan, a Southern district of Mexico City. Following an Implementation Mapping approach, guided by the Consolidated Framework for Implementation Research (CFIR), the Health Belief Model, and the Implementation Outcomes Framework (IOF), we will evaluate the determinants of implementation and outcomes of the current MGMACS implementation and develop a logic model describing the process for improving adherence to the MGMACS from abnormal screens onwards down the cascade, among patients, providers, and clinics (Aim 1). Next, we will select and adapt implementation strategies that address the barriers identified to improve adherence to MGMACS (Aim 2). In both aims, we will use qualitative and quantitative methods for data collection and synthesis of findings, embedding them together in a multistage integrated convergent mixed methods design and analysis approach. Our study team has extensive research expertise in biostatistics, implementation science methods and practice, and CC prevention and control in Mexico and elsewhere. We aim to gather data to inform a future external application for a large-scale implementation study on improving adherence to MGMACS. This project will provide a model for an implementation science-based approach to improving CC early detection, diagnosis, and treatment programs in similar under-resourced contexts in Latin America and beyond, contributing to the reduction and ultimate elimination of CC.