Patient Satisfaction With a Comprehensive Remote Care Program for Chronic Condition Management for Adults Under Medical Care: Observational Study
Bibliographic record
Abstract
Background: More than half of adults in the United States have at least one chronic medical condition. Remote care strategies, including telemedicine, remote monitoring, and connected health devices, are increasingly used to support chronic condition management and adherence to provider-recommended care plans. Evaluating participant satisfaction and perceived usefulness is essential to understanding program value and potential for sustained engagement. Objective: This study aims to evaluate participant satisfaction, perceived usefulness, and self-reported health outcomes associated with a clinically deployed Remote Care program for chronic condition management that included nurse and coach follow-up, health monitoring devices, and digital education tools. Methods: A survey was emailed to 1411 active participants in the Brook Remote Care program between September 23 and December 8, 2023. The survey assessed satisfaction with program features, perceived usefulness, and self-reported health changes. Descriptive statistics were used to summarize the data, and chi-square tests were used to examine differences by age, gender, program duration, and health conditions. Results: A total of 360 participants completed the survey. Most participants rated the program as useful (320/359, 89%), and 66% (234/357) indicated they were likely to recommend it to others with similar health concerns. Between 68% (216/316) and 84% (277/332) rated specific program features as "good" to "excellent," with nurse monitoring, health monitoring devices, and program cost receiving the most favorable ratings. Nearly half of participants reported improvements in physical health (155/314, 49%), reduced health-related stress (148/326, 45%), and increased knowledge of their condition (172/360, 48%). Additionally, approximately one-third reported improvements in lifestyle behaviors. Longer program duration was associated with higher satisfaction and greater self-reported health improvements. Conclusions: Participants reported high satisfaction with a remote care program designed to support chronic condition self-management. These findings support the value of integrated remote care models that combine device monitoring, personalized follow-up, and patient education to enhance patient experience and promote engagement in self-care.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".