The AAAPC Annual Research Conference 2023

REGISTRATIONS NOW OPEN

Prof Jon Emery – Plenary Speaker

Herman Chair of Primary Care Cancer Research

Ms Chiara Beccia

Have interventions aimed at assisting general practitioners in facilitating earlier diagnosis of type 1 diabetes in children been successful? A systematic review.

Diabetic ketoacidosis at the onset of type 1 diabetes is an acute, life-threatening emergency where the body no longer contains enough insulin for survival. It is the leading cause of death in children with type 1 diabetes. Timely diagnosis and treatment can prevent diabetic ketoacidosis from progressing, however, this is challenging as the symptoms associated with the onset of type 1 diabetes are largely non-specific.

Prior studies have identified a window of delay between clinical presentation and diagnosis. This review explores and evaluates interventions that reduce diagnostic delay of type 1 diabetes in children attending general practice. Results will be shared and discussed at the conference.

Dr Andrew Donald

Clinical indicator prioritisation: a new approach for primary care research in the electronic age.

Clinical indicators for application in primary care research need to be evidence-based and relevant to current clinical practice. The nominal group technique is an effective method for reaching consensus among healthcare experts, especially where competing prioritisation criteria are being considered. However, in the current environment where many face-to-face meetings have become virtual and the available digital tools have evolved and improved, alternative approaches are being more commonly utilised.

This study will prioritise a set of existing, validated clinical indicators proposed for inclusion in a clinical trial aiming to reduce medicine-related harm in primary care.

Dr Javiera Martinez Gutierrez

Unexpected weight loss and cancer: risk, guidelines, and recommendations for follow-up.

Due to the non-specific nature of cancer symptoms, many patients experience a delay in diagnosis. Unexpected weight loss is one symptom that can be difficult to identify in practice. Clinical decision support systems can be an efficient way of identifying relevant or overlooked information stored in electronic medical records and bringing evidence-based knowledge to practice.

This work summarises the association between unexpected weight loss and cancer risk, and identifies guidelines and recommendations that can be used in a clinical decision support system to assist primary care clinicians to recognise patients at risk of cancer.

Dr Lucas de Mendonça

Opening the “black box” of Clinical Decision Support Systems: describing development and validation of an algorithm to identify people with unexplained weight loss.

Clinical Decision Support Systems are tools that assist decision making within the clinical workflow. They are being increasingly integrated into electronic health records to flag conditions or symptoms of interest and provide guidance for action. Many health professionals remain sceptical about clinical decision support tools due to the uncertainty around how the recommendations are generated.

This study illustrates the process of algorithm creation and validation in our clinical decision support system called Future Health Today.

Dr Alex Lee

External validation of a diagnostic accuracy score for cancer based on unexpected weight loss symptoms in primary care.

Unexpected weight loss is a common symptom of patients presenting in general practice and is associated with many conditions, including cancer. This ambiguity makes it difficult to understand which patients should be referred for further investigation. Recent studies in the United Kingdom have shown that when unexpected weight loss occurs with other known cancer symptoms or an abnormal blood test result, urgent investigation is required. However, this work has not yet been validated in other populations with no similar results in Australia.

This study calculates positive predictive values of unexpected weight loss as a predictor for cancer diagnosis within six months of first presentation.