Cervical Pre-Cancer Care Pathway Data Structuring Tool: A Standardized Data Capture Framework for Screening, Diagnosis, Treatment Referral, and Follow-Up Tracking in Low-Resource Hospital Systems

This work presents the Cervical Pre-Cancer Care Pathway Data Structuring Tool, a standardized digital data capture framework designed to improve longitudinal tracking, continuity of care, and service coordination across cervical cancer screening and pre-cancer management pathways in low-resource hospital systems. In many resource-constrained healthcare environments, cervical cancer prevention services remain fragmented, with limited integration between screening, diagnostic evaluation, treatment referral, and follow-up systems. These gaps contribute to incomplete patient tracking, delayed treatment, and high rates of loss to follow-up. The framework was developed to support structured and interoperable data capture across the full cervical pre-cancer care continuum, including screening encounters, diagnostic procedures, pathology results, treatment referrals, and post-treatment follow-up. The tool enables standardized organization of patient-level clinical data to improve visibility into care progression and strengthen continuity across service delivery points. The system integrates multiple sources of clinical and programmatic data into a unified longitudinal patient pathway model, allowing healthcare providers and program managers to monitor patient movement through screening and treatment workflows. It supports identification of missed follow-up visits, incomplete referrals, delayed treatment initiation, and gaps in continuity of care that commonly affect cervical cancer prevention programs in low-resource settings. Core functionalities include: Standardized cervical screening data capture Longitudinal patient pathway tracking Referral and treatment transition monitoring Follow-up appointment tracking Service completion and dropout detection Structured pathology and diagnostic data integration Continuity-of-care analytics AI-ready data structuring for implementation research and predictive analytics The framework is designed for deployment within teaching hospitals and public-sector healthcare facilities operating under resource limitations, including environments with heterogeneous record systems and low digital interoperability. Its modular architecture supports integration with existing electronic medical records, laboratory systems, and cervical cancer program databases. Beyond routine clinical documentation, the tool functions as a foundational digital public health infrastructure component supporting implementation science research, cervical cancer prevention program evaluation, and health systems strengthening. By enabling standardized longitudinal data capture across the cervical pre-cancer care continuum, the framework supports evidence-driven improvement of screening retention, referral coordination, and treatment completion. Overall, this work contributes to the development of scalable digital health infrastructure for cervical cancer prevention programs and provides an implementation-oriented framework for strengthening continuity of care in low-resource hospital systems.