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Accepted for/Published in: JMIR Formative Research

Date Submitted: Jul 30, 2025
Date Accepted: Nov 3, 2025

The final, peer-reviewed published version of this preprint can be found here:

Evaluating a Clinical Decision Support Tool for Cancer Risk Assessment in Primary Care: Simulation Study of Unintended Weight Loss

Martinez-Gutierrez J, Chima S, De Mendonca L, Lee A, Hunter B, Manski-Nankervis JA, Daly D, Fishman G, Huckvale K, Lim FS, Wang B, Nelson C, Nicholson B, Emery J

Evaluating a Clinical Decision Support Tool for Cancer Risk Assessment in Primary Care: Simulation Study of Unintended Weight Loss

JMIR Form Res 2025;9:e79208

DOI: 10.2196/79208

PMID: 41370791

PMCID: 12694943

Evaluating a Clinical Decision Support Tool for Cancer Risk Assessment in Primary Care: A Simulation Study of Unintended Weight Loss

  • Javiera Martinez-Gutierrez; 
  • Sophie Chima; 
  • Lucas De Mendonca; 
  • Alex Lee; 
  • Barbara Hunter; 
  • Jo-Anne Manski-Nankervis; 
  • Deborah Daly; 
  • George Fishman; 
  • Kit Huckvale; 
  • Fong Seng Lim; 
  • Benny Wang; 
  • Craig Nelson; 
  • Brian Nicholson; 
  • Jon Emery

ABSTRACT

Background:

Early cancer detection is crucial, but recognising the significance of associated symptoms such as unintended weight loss in primary care remains challenging. Clinical Decision Support Systems (CDSS) can aid cancer detection, but face implementation barriers and low uptake in real-world settings. To address these issues, simulation environments offer a controlled setting to study CDSS usage and improve their design for better adoption in clinical practice.

Objective:

To evaluate a CDSS integrated within general practice electronic health records aimed at identifying patients at risk of undiagnosed cancer.

Methods:

The evaluation of CDSS to identify patients with unintended weight loss was conducted in a simulated primary care environment where GPs interacted with the CDSS in simulated clinical consultations. There were four possible clinical scenarios based on patient gender and risk of cancer. Data collection included interviews with GPs, cancer survivors (lived-experience community advocates), and patient actors, as well as video analysis of GP-CDSS interactions. Two theoretical frameworks were employed for thematic interpretation of the data.

Results:

We recruited 10 GPs and 6 community advocates, conducting 20 simulated consultations with two patient actors (two consultations per GP, one high-risk and one low-risk). All participants found the CDSS acceptable and unobtrusive. GPs utilised CDSS recommendations in three distinct ways: as a communication aid when discussing follow up with the patient, as a reminder for differential diagnoses and recommended investigations, and as an aid to diagnostic decision-making without sharing with patients. The CDSS's impact on patient-doctor communication varied, both facilitating and hindering interactions depending on the GP's communication style.

Conclusions:

We developed and evaluated a CDSS for identifying cancer risk in patients with unintended weight loss in a simulated environment, revealing its potential to aid clinical decision-making and communication, while highlighting implementation challenges and the need for context-sensitive application. Clinical Trial: NA


 Citation

Please cite as:

Martinez-Gutierrez J, Chima S, De Mendonca L, Lee A, Hunter B, Manski-Nankervis JA, Daly D, Fishman G, Huckvale K, Lim FS, Wang B, Nelson C, Nicholson B, Emery J

Evaluating a Clinical Decision Support Tool for Cancer Risk Assessment in Primary Care: Simulation Study of Unintended Weight Loss

JMIR Form Res 2025;9:e79208

DOI: 10.2196/79208

PMID: 41370791

PMCID: 12694943

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