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Diabetic Retinopathy

Diabetic Retinopathy

DefinitionDiabetic retinopathy is a microvascular complication of diabetes affecting the retinal blood vessels.Risk FactorsDiabetic retinopathy is present in almost all individuals with type 1 diabetes and more than 60% of those with type 2 diabetes after two decades of disease.The risk increases with poor glycemic control, hypertension, dyslipidemia, smoking, pregnancy, and puberty.Although cataracts and glaucoma are also more frequent in people with diabetes, retinopathy remains the leading...

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Target Product Profile for a Machine Learning-Automated Retinal Imaging Analysis Software for Use in English Diabetic

Trystan Macdonald^1,2,3, Jacqueline Dinnes³, Gregory Maniatopoulos⁴

¹Ophthalmology Department, Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham National Health Service Foundation Trust, Birmingham, United Kingdom.

JMIR Research Protocols

|March 27, 2024

Summary

This summary is machine-generated.

This study develops a Target Product Profile (TPP) for machine learning-automated retinal imaging analysis software (ML-ARIAS) to improve diabetic eye screening (DES) in England. The TPP ensures ML tools meet patient and healthcare needs.

Keywords:

DM England artificial intelligence design developers diabetes mellitus diabetic diabetic eye screening diabetic retinopathy eye screening imaging analysis software implementation machine learning retinal imaging study protocol target product profile

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Area of Science:

Medical technology
Artificial intelligence in healthcare
Ophthalmology

Background:

Diabetic eye screening (DES) offers opportunities for machine learning (ML) to enhance clinical and service outcomes.
Successful ML integration into DES necessitates meticulous product development, evaluation, and implementation.
Target Product Profiles (TPPs) are crucial for guiding ML product development and evaluation by summarizing implementation requirements.

Purpose of the Study:

To create a TPP for an ML-automated retinal imaging analysis software (ML-ARIAS) system.
The ML-ARIAS system is intended for use in diabetic eye screening (DES) programs in England.

Main Methods:

A three-phase approach was employed, starting with characteristic identification from systematic reviews and standards.
Stakeholder input (patients, healthcare professionals, managers, regulators) refined characteristics and developed specifications through interviews.
A Delphi consensus study with stakeholders and developers ensured feasibility and finalized the TPP through iterative feedback and voting.

Main Results:

Phase 1, establishing TPP characteristics, was completed in November 2023.
Phase 2, drafting specifications, is ongoing and expected to conclude in March 2024.
Phase 3, the Delphi consensus, is scheduled for completion in July 2024.

Conclusions:

Multistakeholder TPP development for ML-ARIAS in DES will yield tools aligned with patient and provider needs.
The TPP development process offers a transferable methodology and template for other disease areas.