Grant Number:	1R01CA288530-01 Interpret this number
Primary Investigator:	Haas, Jennifer
Organization:	Massachusetts General Hospital
Project Title:	Personalized Risk-Based Follow-Up of Cervical Cancer Screening in Practice (PREDICT)
Fiscal Year:	2024

Abstract Cervical cancer is highly preventable when detected early and managed appropriately; today it is most often diagnosed in under-screened individuals or after a failure to follow-up abnormal screening results. Cervical cancer screening and management (CCSM) is complex as both screening modalities and management guidelines have recently evolved. The 2018 US Preventive Services Task Force screening guidelines recommend 3 strategies to screen for cervical cancer: Pap test with option of reflex human papilloma virus (HPV) testing, Pap/ HPV co-testing, and HPV alone. The 2019 American Society for Colposcopy and Cervical Pathology (ASCCP) guidelines for managing abnormal results reflect the principle of “equal management for equal risks,” promoting highly personalized management, with synthesis of current and prior results, to maximize benefits of cancer prevention while minimizing harms of over-testing and over-treatment. Yet, the complexity of these current evidence-based clinical guidelines makes it challenging for clinicians to implement in practice. Lack of integration of the ASCCP algorithms with electronic health records (EHRs) is an important barrier to management. As a result, incomplete and incorrect follow-up represents an ongoing and growing challenge, involving complex interactions among patients, primary care practitioners and specialists. Implementing personalized risk-based cervical cancer screening requires addressing barriers at individual, both patient and practitioner, levels as well as at care team and health system levels. We propose to develop, test and disseminate a health information technology-enabled, multilevel, stepped care intervention grounded in primary care, PREDICT (Personalized Risk-based Follow-up of Cervical Cancer Screening in Practice) for the cervical cancer screening continuum. PREDICT is designed to be highly scalable, using an open source CCSM tool, integrated using national data standards endorsed by the 21st Century Cures Act Final Rule. Key PREDICT components include: system redesign to promote identification, tracking, and EHR-integration of clinical guidelines to promote both visit-based and population management; use of individual patient and practitioner reminders and tools to promote engagement; and enhance team coordination through an efficient “stepped care” approach. The effectiveness and implementation of PREDICT will be evaluated by conducting a 3-arm cluster randomized controlled trial (standard care vs. visit-based management vs. population outreach) of individuals in 4 primary care networks. The design will allow us to examine the marginal and cumulative effectiveness of the intervention components on the primary effectiveness outcome of receipt of appropriate CCSM within 120-days of becoming due for care. Guided by Implementation Evaluation (RE-AIM QuEST) and Determination (CFIR) frameworks, we will assess the reach, acceptability, adoption, implementation and maintenance/ sustainability of the intervention.





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