Lessons From the Field From a Volunteer Telehealth Ambassador Program to Enhance Video Visits Among Low-Income Patients: Qualitative Improvement Study
Bibliographic record
Abstract
BACKGROUND: The prevalence of telehealth video use across the United States is uneven, with low uptake in safety-net health care delivery systems, which care for patient populations who face barriers to using digital technologies. OBJECTIVE: This study aimed to increase video visit use in an urban safety-net delivery system. We piloted a telehealth ambassador program, in which volunteers offered technical support to patients with access to digital technologies to convert primary care visits already scheduled as telehealth audio-only visits to telehealth video visits. METHODS: We used a descriptive approach to assess the feasibility, efficacy, and acceptability of the pilot telehealth ambassador program. Feasibility was quantified by the percentage of eligible patients who answered calls from telehealth ambassadors. Program efficacy was measured in two ways: (1) the percentage of patients with access to digital technology who interacted with the navigators and were successfully prepared for a telehealth video visit, and (2) the percentage of prepared patients who completed their scheduled video visits. Program acceptability was ascertained by a structured telephone survey. RESULTS: Telehealth ambassadors attempted to contact 776 eligible patients; 43.6% (338/776) were reached by phone, among whom 44.4% (150/338) were provided digital support between March and May 2021. The mean call duration was 8.8 (range 0-35) minutes. Overall, 67.3% (101/150) of patients who received support successfully completed a telehealth video visit with their provider. Among the 188 patients who were contacted but declined video visit digital support, 61% (114/188) provided a reason for their decline; 42% (48/114) did not see added value beyond a telehealth audio-only visit, 20% (23/114) had insufficient internet access, and 27% (31/114) declined learning about a new technology. The acceptability of the telehealth ambassador program was generally favorable, although some patients preferred having in-real-time technology support on the day of their telehealth video visit. CONCLUSIONS: This high-touch program reached approximately one-half of eligible patients and helped two-thirds of interested patients with basic video visit capability successfully complete a video visit. Increasing the program's reach will require outreach solutions that do not rely solely on phone calls. Routinely highlighting the benefits of video visits, partnering with community-based organizations to overcome structural barriers to telehealth use, and offering in-real-time technology support will help increase the program's efficacy.
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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 | 0.025 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".