CompletedPublic Health & HealthcareNIHR-supported project
Understanding Biomedical Burden in Perioperative Care: Validation and Refinement of Early Digital Screening and Biomedical Burden Ontology using Primary and Secondary Care Linkage
Recipient organisationNIHR Southampton Biomedical Research Centre
NIHR supportRecorded as supported by this research centre
PeriodMar 2025 — Mar 2026
In plain English
AI plain-English summary
Every year, thousands of patients in the UK undergo surgery carrying hidden health burdens—such as frailty, multiple long-term conditions, or undiagnosed organ stress—that conventional risk checks miss. This project will validate a new digital tool, the Biomedical Burden Ontology (BBO), by linking GP records with hospital data from University Hospital Southampton. The researchers will also test a simple patient questionnaire called MyMR, comparing its accuracy against standard pre-surgery assessments. If successful, the BBO could give surgeons and anaesthetists a far more complete picture of a patient’s true health before they go under the knife. That would mean fewer unexpected complications, shorter hospital stays, and better-informed decisions about whether surgery is safe. The pilot will also create a blueprint for linking GP and hospital data regionally and nationally, making this kind of integrated risk screening scalable across the NHS. In the longer term, the enriched dataset could train machine learning and large language models to predict surgical outcomes more reliably—though those applications remain at the design stage and would require follow-on funding to develop.
View original technical description
In this study we aim to utilise linked primary and secondary care records to better understand biomedical burden in patients undergoing surgery. We will clinically validate and refine the BBO to support perioperative risk decisions. We will validate the MyMR screening questionnaire and compare conventional approaches to perioperative risk assessment with the BBO. This will be achieved by establishing a semantically enriched linked dataset between primary (GPs referring to UHS) and secondary care (UHSFT Fit4Surgery). The integration of these linked datasets will facilitate a more comprehensive understanding of biomedical burden and its implications on patient outcomes in perioperative care. The pilot will act as a blueprint for scaling primary care linkages regionally and nationally. The key objectives include: 1. To enhance the robustness and clinical relevance of the BBO by validating its structure and conceptual integrity against real-world patient data. Outcome: knowledge base integrating biomedical burden ontology into perioperative risk assessment and clinical decision support. 2. Develop and clinically evaluate semantic enrichment of patient datasets, ensuring that the ontology-driven augmentation aligns with clinical reasoning and decision-making needs. Outcome: evaluation of the knowledge base by clinical domain experts 3. Assess the value of BBO-enriched patient data in improving advanced analytics such as ML and LLMs within perioperative settings: Outcome: exemplar design patterns/pipelines for advanced analytics (ML, KGs, LLMs) to be used for follow-on funding proposals
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