Mailed Letter Versus Phone Call to Increase Diabetic-Related Retinopathy Screening Engagement by Patients in a Team-Based Primary Care Practice: Prospective, Single-Masked, Randomized Trial
Bibliographic record
Abstract
BACKGROUND: Vision loss from diabetic-related retinopathy (DR) is preventable through regular screening. OBJECTIVE: The purpose of this study was to test different patient engagement approaches to expand a teleophthalmology program at a 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 older than 18 years with type 1 or type 2 diabetes were randomized to one of the following 4 engagement strategies: phone call, mail, mail plus phone call, or usual care. Outreach was conducted by administrative staff within the clinic. The primary outcome was booking an appointment for DR screening. RESULTS: A total of 23 patients in the phone, 28 in the mail, 32 in the mail plus phone call, and 27 in the control (usual care) group were included in the analysis. After the intervention and after excluding patients who said they were screened, 88% (15/17) of patients in the phone, 11% (2/18) in the mail, and 100% (21/21) in the mail and phone group booked an appointment with the teleophthalmology program compared to 0% (0/12) in the control group. Phoning patients positively predicted patients booking a teleophthalmology appointment (P<.001), whereas mailing a letter had no effect. CONCLUSIONS: Patient engagement to book DR screening via teleophthalmology in an urban, academic, team-based primary care practice using telephone calls was much more effective than patient engagement using letters or usual care. Practices that have access to a local DR screening program and have resources for such engagement strategies should consider using them as a means to improve their DR screening rates. TRIAL REGISTRATION: ClinicalTrials.gov NCT03927859; https://clinicaltrials.gov/ct2/show/NCT03927859.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".