Digitally Based Blood Pressure Self-Monitoring Program That Promotes Hypertension Self-Management and Health Education Among Patients With Low-Income: Usability Study
Bibliographic record
Abstract
BACKGROUND: According to evidence-based clinical guidelines, adults with hypertension are advised to self-monitor their blood pressure (BP) twice daily. Self-measured BP monitoring is a recommended strategy for improving hypertension management. OBJECTIVE: We aimed to determine the feasibility and acceptability of a digitally based BP self-monitoring program that promotes hypertension self-management and health education among low-income patients. We hypothesized that the program would be highly feasible and acceptable and that at least 50% of the patients would use the monitor at the rate required for the reimbursement of the device's cost (16 days of measurements in any 30-day period). METHODS: Withings BPM Connect was deployed to patients at Family Health Centers of San Diego. Program elements included training, SMS text message reminders, and physician communication. Compliance, use, mean BP, and BP control status were calculated. A Kaplan-Meier time-to-event analysis was conducted to compare time to compliance between a strict definition (≥16 days in any rolling 30-day window) and a lenient definition (≥1 day per week for 4 consecutive weeks). A log-rank test was performed to determine whether the difference in time to compliance between the definitions was statistically significant. Mean systolic BP (SBP) and diastolic BP (DBP) before the intervention and after the intervention and mean change in SBP and DBP across patients were calculated. Paired sample t tests (2-tailed) were performed to assess the changes in SBP and DBP from before to after the intervention. RESULTS: A total of 179 patients received the monitors. The mean changes in SBP and DBP from before to after the intervention were +2.62 (SE 1.26) mm Hg and +3.31 (SE 0.71) mm Hg, respectively. There was a statistically significant increase in both SBP and DBP after the intervention compared with before the intervention (P=.04 and P<.001). At the first and last measurements, 37.5% (63/168) and 48.8% (82/168) of the patients had controlled BP, respectively. During the observation period, 83.3% (140/168) of the patients had at least 1 controlled BP measurement. Use decreased over time, with 53.6% (90/168) of the patients using their monitor at week 2 and only 25% (42/168) at week 11. Although only 25.6% (43/168) achieved the strict definition of compliance, 42.3% (71/168) achieved the lenient definition of compliance. The median time to compliance was 130 days for the strict definition and 95 days for the lenient definition. The log-rank test showed a statistically significant difference in time to compliance between the compliance definitions (P<.001). Only 26.8% (45/168) complied with the measurement rate that would result in device cost reimbursement. CONCLUSIONS: Few patients used the monitors at a rate that would result in reimbursement, raising financial feasibility concerns. Plans for sustaining costs among low-income patients need to be further evaluated.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".