Research Brief: Introducing The Screen-Diagnose-Manage-Monitor Framework

By Yogarabindranath Swarna Nantha and Sentil Gopal

Recommended Citation—Swarna Nantha Y, Gopal S. Screen–Diagnose–Manage–Monitor: a real-world, co-designed framework for clinical reasoning [premise] [Internet]. Insight Circle. 2026 Jul 25. Available from: https://www.theinsightcircle.org/post/screen-diagnose-manage-monitor-a-real-world-co-designed-framework-for-clinical-reasoning

Background

Primary care clinicians work in complex environments that are influenced by time pressure, diagnostic uncertainty, and increasing reliance on unsupervised artificial intelligence. Current evolution in healthcare has outstripped the capacity of traditional educational pathways, which remain constrained by slower processes of validation and governance. The Screen–Diagnose–Manage–Monitor (SDMM) framework (from the international textbook Screen-Diagnose-Manage and Monitor: A GP Primer to Common Clinical Conditions), seeks to address this gaps as a human oversight layer to any AI decision-making process.

Approach

Co-designed by academic faculty, general practitioners, and students as active collaborators—with origins traced to an algorithmically structured clinical textbook—SDMM provides a structured, iterative scaffold for decision-making across four stages: screening, diagnosis, management, and monitoring. The framework was progressively integrated into undergraduate medical education through problem-based learning, clinical skills teaching, case-based discussions and clinical reasoning workshops.

Evaluation

Early implementation across teaching and clinical settings suggests a shift from knowledge-centric to decision-centric care while maintaining human oversight. Student evaluations demonstrated consistently high satisfaction with teaching sessions incorporating SDMM principles, while independent peer review highlighted strengths in learning design, learner engagement, authenticity and application of clinical reasoning. Learners reported improved clarity in structuring clinical decisions and greater confidence in applying knowledge to clinical contexts.

Implication

SDMM supports improved clarity in clinical reasoning, strengthened longitudinal thinking, and consistent application across acute, chronic, and preventive care. SDMM reflects a generalizable pattern of naturalistic decision-making and human-centred care, with potential for integration into modern decision-support systems. This higher order human governance layer has the potential create oversight platform to any AI decision-making in medicine.

Availability of Full Research—The complete research details is currently maintained as an internal research dossier by Full Circle Nexus and Insight Circle, therefore not publicly available at this stage. Researchers, healthcare professionals, policymakers, and organizations with a legitimate interest in this work are welcome to contact Insight Circle to discuss access or potential collaboration.