scholarly journals Automated diabetic retinopathy screening for primary care settings using deep learning

2021 ◽  
pp. 100045
Author(s):  
Alauddin Bhuiyan ◽  
Arun Govindaiah ◽  
Avnish Deobhakta ◽  
Mohd Hossain ◽  
Richard Rosen ◽  
...  
Keyword(s):  
Primary Care ◽  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Diabetic Retinopathy Screening ◽  
Primary Care Settings ◽  
Retinopathy Screening

Mailed letter versus phone call to increase diabetic retinopathy screening engagement by patients in a team-based primary care practice: a prospective, single-masked, randomized trial.

2021 ◽  
Author(s):  
Vess Stamenova ◽  
Megan Nguyen ◽  
Nike Onabajo ◽  
Rebecca Merritt ◽  
Olivera Sutakovic ◽  
...  
Keyword(s):  
Primary Care ◽  
Diabetic Retinopathy ◽  
Usual Care ◽  
Patient Engagement ◽  
Primary Care Practice ◽  
Phone Call ◽  
Care Practice ◽  
Diabetic Retinopathy Screening ◽  
Engagement Strategies ◽  
Retinopathy Screening

Abstract Background: Diabetic retinopathy is the leading cause of blindness among adults, but vision loss is preventable through regular screening. Urban areas in Canada have large numbers of unscreened individuals and teleophthalmology programs have been used to improve access and uptake of screening. The purpose of this study was to test different patient engagement approaches to expand teleophthalmology program to team-based primary care clinic in the city of Toronto, Canada.Methods: A teleophthalmology program was set up in a large urban academic team-based primary care practice. Patients over 18 years of age, with type 1 or type 2 diabetes were randomized to one of four engagement strategies: a phone call, a letter, a letter plus phone call, or usual care. Outreach was conducted by administrative staff within the clinic. The primary outcome was booking an appointment for diabetic retinopathy screening through a teleophthalmology program at the time of the call or within one week for the mail intervention. Results: A total of 23 patients in the phone, 28 in the mail, 32 in the mail and phone, and 27 in the control (usual care) were included in the analysis. After the intervention, 88% of patients in the phone intervention, 11% of patients in the mail group, and 100% in the mail and phone group booked an appointment with the teleophthalmology program compared to 0% in the control group. Phoning patients positively predicted patients booking a teleophthalmology appointment (p< .0001), while sending a letter had no effect. Conclusions: Patient engagement to book diabetic retinopathy screening via teleophthalmology in an urban academic team-based primary care practice using telephone calls was much more effective than letters or usual care. Practices that have access to a local DR screening programs and have the required resources to undertake such engagement strategies should consider using them as a means in improving their DR screening rates.

scholarly journals Essentials of a Robust Deep Learning System for Diabetic Retinopathy Screening: A Systematic Literature Review

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Aan Chu ◽  
David Squirrell ◽  
Andelka M. Phillips ◽  
Ehsan Vaghefi
Keyword(s):  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Learning Algorithm ◽  
Learning Algorithms ◽  
Validation Dataset ◽  
Cochrane Library ◽  
Clinical Implementation ◽  
Diabetic Retinopathy Screening ◽  
Deep Learning Algorithm ◽  
Retinopathy Screening

This systematic review was performed to identify the specifics of an optimal diabetic retinopathy deep learning algorithm, by identifying the best exemplar research studies of the field, whilst highlighting potential barriers to clinical implementation of such an algorithm. Searching five electronic databases (Embase, MEDLINE, Scopus, PubMed, and the Cochrane Library) returned 747 unique records on 20 December 2019. Predetermined inclusion and exclusion criteria were applied to the search results, resulting in 15 highest-quality publications. A manual search through the reference lists of relevant review articles found from the database search was conducted, yielding no additional records. A validation dataset of the trained deep learning algorithms was used for creating a set of optimal properties for an ideal diabetic retinopathy classification algorithm. Potential limitations to the clinical implementation of such systems were identified as lack of generalizability, limited screening scope, and data sovereignty issues. It is concluded that deep learning algorithms in the context of diabetic retinopathy screening have reported impressive results. Despite this, the potential sources of limitations in such systems must be evaluated carefully. An ideal deep learning algorithm should be clinic-, clinician-, and camera-agnostic; complying with the local regulation for data sovereignty, storage, privacy, and reporting; whilst requiring minimum human input.

scholarly journals Correction to: Diabetic retinopathy screening in urban primary care setting with a handheld smartphone-based retinal camera

2020 ◽  
Author(s):  
Márcia Silva Queiroz ◽  
Jacira Xavier de Carvalho ◽  
Silvia Ferreira Bortoto ◽  
Mozania Reis de Matos ◽  
Cristiane das Graças Dias Cavalcante ◽  
...  
Keyword(s):  
Primary Care ◽  
Diabetic Retinopathy ◽  
Care Setting ◽  
Primary Care Setting ◽  
Diabetic Retinopathy Screening ◽  
Retinopathy Screening

scholarly journals Feasibility of a multifaceted implementation intervention to improve attendance at diabetic retinopathy screening in primary care in Ireland: a cluster randomised pilot trial

BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e051951
Author(s):  
Fiona Riordan ◽  
Aileen Murphy ◽  
Christina Dillon ◽  
John Browne ◽  
Patricia M Kearney ◽  
...  
Keyword(s):  
Primary Care ◽  
General Practice ◽  
Diabetic Retinopathy ◽  
Process Evaluation ◽  
Pilot Trial ◽  
Delivery Cost ◽  
Definitive Trial ◽  
Diabetic Retinopathy Screening ◽  
Cluster Randomised ◽  
Retinopathy Screening

ObjectivesDiabetic retinopathy screening (DRS) uptake is suboptimal in many countries with limited evidence available on interventions to enhance DRS uptake in primary care. We investigated the feasibility and preliminary effects of an intervention to improve uptake of Ireland’s national DRS programme, Diabetic RetinaScreen, among patients with type 1 or type 2 diabetes.Design/settingWe conducted a cluster randomised pilot trial, embedded process evaluation and cost analysis in general practice, July 2019 to January 2020.ParticipantsEight practices participated in the trial. For the process evaluation, surveys were conducted with 25 staff at intervention practices. Interviews were conducted with nine staff at intervention practices, and 10 patients who received the intervention.InterventionsThe intervention comprised practice reimbursement, an audit of attendance, electronic prompts targeting professionals, General Practice-endorsed patient reminders and a patient information leaflet. Practices were randomly allocated to intervention (n=4) or wait-list control (n=4) (usual care).OutcomesStaff and patient interviews explored their perspectives on the intervention. Patient registration and attendance, including intention to attend, were measured at baseline and 6 months. Microcosting was used to estimate intervention delivery cost.ResultsThe process evaluation identified that enablers of feasibility included practice culture and capacity to protect time, systems to organise care, and staff skills, and workarounds to improve intervention ‘fit’. At 6 months, 22/71 (31%) of baseline non-attenders in intervention practices subsequently attended screening compared with 15/87 (17%) in control practices. The total delivery cost across intervention practices (patients=363) was €2509, averaging €627 per practice and €6.91 per audited patient. Continuation criteria supported proceeding to a definitive trial.ConclusionsThe Improving Diabetes Eye screening Attendance intervention is feasible in primary care; however, consideration should be given to how best to facilitate local tailoring. A definitive trial of clinical and cost-effectiveness is required with preliminary results suggesting a positive effect on uptake.Trial registration numberNCT03901898.

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