Multilevel Intervention to Increase Patient Portal Use in Adults With Type 2 Diabetes Who Access Health Care at Community Health Centers: Single Arm, Pre-Post Pilot Study
Bibliographic record
Abstract
BACKGROUND: Diabetes self-management education and support (DSMS) delivered via patient portals significantly improves glycemic control. Yet, disparities in patient portal use persist. Community health centers (CHCs) deliver care to anyone who needs it, regardless of income or insurance status. OBJECTIVE: This study aimed to evaluate the feasibility, acceptability, and preliminary efficacy of a multilevel intervention to increase access and use of portals (MAP) among people with type 2 diabetes (T2D) receiving health care at CHCs. METHODS: A within-subjects, pre-post design was used. Adults with T2D who were portal naive were recruited from 2 CHCs. After informed consent, participants met with a community health worker for referrals for social determinants of health, provision of a tablet with cell service, and individualized training on use of the tablet and portal. Next, a nurse met individually with participants to develop a DSMS plan and then communicated with patients via the portal at least twice weekly during the first 3 months and weekly for the latter 3 months. Data were collected at baseline, 3 months and 6 months. The primary outcome was patient activation and engagement with the portal. Secondary outcomes included technology attitudes, digital health literacy, health-related outcomes and psychosocial function. RESULTS: level was 8.31%. Portal activation was high; 100% (22/22) of participants created a portal account and logged in within the first month. Mean participant logins per week over the first 3 months was 3.16 (SD 1.55) and 1.45 (SD 0.93) over the final 3 months; mean logins per month over the first 3 months was 12.65 (SD 6.21) and 5.79 (SD 3.74) over last 3 months. Engagement was high; 96% (20/21) logged in at least twice per month in the first 3 months and 76% (16/21) between 3 and 6 months. At 6 months, improvements were seen in technology confidence, digital health literacy, diabetes self-efficacy, and diabetes distress. Participant satisfaction with MAP was high as was intention to continue portal use. Barriers to clinical integration and recommendations for portal development were identified. CONCLUSIONS: MAP shows promise for improving health equity in portal use for T2D. Larger, controlled studies are needed to determine how best to implement MAP in complex clinical settings and to evaluate efficacy over time. TRIAL REGISTRATION: ClinicalTrials.gov NCT05180721; https://clinicaltrials.gov/study/NCT05180721.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".