Development and evaluation of AI-based clinical decision support system for streamlining breast multidisciplinary team meetings - abstract, methods, results and conclusions

Sep 23, 2026

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Multidisciplinary team (MDT) meetings are central to cancer care, yet rising caseload and constrained resources reduce their effectiveness and sustainability. This quality improvement project assessed an artificial intelligence-based clinical decision support (CDS) system to develop and validate a standard of care (SoC) for streamlining breast MDT meetings in a tertiary cancer centre. International MDT guidelines informed SoC development, and Deontics CDS evaluated application for benign and malignant breast disease while excluding metastatic and recurrent cancer.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages9

Reading Time23 min

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Abstract

Objectives

Methods

Results

Discussion

Conclusions

Introduction

What is already known on this topic

What this study adds

How this study might affect research, practice or policy

Open access Original research Development and evaluation of AI-based clinical decision support system for streamlining breast multidisciplinary team meetings Hannah Jeffery ,1,2 Aaditya Prakash Sinha ,3,4 Belul Shifa ,5 Georgina Bitsakou,5 Mark Harries ,5 Elinor Sawyer ,1,5 Sarah Pinder ,1,5 Wen Ng,5 Ali Sever ,5 Sultana Hasso,5 Maria Javed ,5 Priya Devadas ,5 Qurratulain Chougle ,5 Neyaf Almajali ,5 Mohamed Attia ,5,6 Mariam Malik ,5 Mangesh A Thorat ,5 Vivekanand Patkar ,7 Arnie Purushotham 1,5 To cite: Jeffery H, Sinha AP, Shifa B, et al. Development and evaluation of AI-based clinical decision support system for streamlining breast multidisciplinary team meetings. BMJ Health Care Inform 2026;33:e102045 . doi:10 . 1136/ bmjhci-2026-102045 ► Additional supplemental material is published online only. To view, please visit the journal online ([https://doi.org/10.1136/](https://doi.org/10.1136/)[ ](https://doi.org/10.1136/)[bmjhci-2026-102045](bmjhci-2026-102045)) . HJ and APS contributed equally. Received 08 January 2026 Accepted 08 July 2026 © Author(s) (or their employer(s)) 2026. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ Group. For numbered affiliations see end of article. Correspondence to Professor Arnie Purushotham; [arnie.purushotham@kcl.ac.uk](arnie.purushotham@kcl.ac.uk) ABSTRACT Objectives Multidisciplinary team (MDT) meetings are key to delivering cancer care. Increasing caseload and limited resources make them less effective and unsustainable. The aim of this quality improvement project was to assess novel artificial intelligence-based clinical decision support (CDS) technology to develop and validate standard of care (SoC) to streamline the breast MDT meetings in a tertiary cancer centre. Methods A clinical governance group of the MDT approved international guidelines used to develop SoC. Deontics CDS was assessed for its suitability to apply the SoC pathway for benign and malignant breast disease with the exclusion of metastatic and recurrent cancer. Results Patients discussed over the preceding 16 months were added to the platform in cohorts of 50 women: two consisting of 50 women each diagnosed with benign disease (benign A and B: n=100) and three consisting of 50 women each diagnosed with malignant disease (cancer A, B and C: n=150) . Concordance between the blinded MDT decision outcomes and SoC recommendations was analysed. This stepwise approach identified knowledge gaps in SoC and refined the CDS. Concordance improved from 82% to 100% in benign and from 94% to 100% in malignant cases. Discussion A sequential process of validating the SoC with data derived from the development of evidence-based SoC protocols based on international guidelines resulted in a final 100% concordance rate between the platform and MDT recommendations for both benign and malignant disease. Conclusions CDS technology could be a milestone in using SoC to deliver a sustainable clinical decision pathway. INTRODUCTION As a result of observed variations in treatment and outcomes in patients with cancer, the Chief Medical Officers of England and Wales published the Calman-Hine report in 1995.1 WHAT IS ALREADY KNOWN ON THIS TOPIC | ⇒ Multidisciplinary team meetings are essential in cancer management. A substantial increase in caseload has overwhelmed their capacity. Therefore, there is a pressing need to prioritise complex cases of cancer using standard of care pathways.
WHAT THIS STUDY ADDS | | --- | | ⇒ Artificial intelligence-based clinical decision support systems can accurately triage cases directly without requiring full multidisciplinary team discussion, thereby prioritising time for discussion of more complex cases.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY | ⇒ This study shows that technology can improve efficiency in decision-making without compromising quality of care and enable teams to

FAQs

What problem does the project address in MDT meetings for breast cancer care?

Increasing caseloads and limited resources make MDT meetings less effective and unsustainable, reducing time for complex cases and potentially affecting decision quality.

How was the standard of care (SoC) developed and evaluated?

An MDT clinical governance group used international guidelines to develop SoC, then Deontics CDS assessed suitability for benign and malignant breast disease, excluding metastatic and recurrent cancer.

What were the key results of CDS concordance with MDT decisions?

Concordance improved from 82% to 100% for benign cases and from 94% to 100% for malignant cases after the stepwise CDS refinement.

Sep 23, 2026

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