Structured Telephone Support Intervention: Improved Heart Failure Outcomes
Bibliographic record
Abstract
BACKGROUND: Presently, 6.5 million Americans are living with heart failure (HF). These patients are expected to follow a complex self-management regimen at home. Several demographic and psychosocial factors limit patients with HF in following the prescribed self-management recommendations at home. Poor self-care is associated with increased hospital re-admissions. Under the Affordable Care Act, there are financial implications related to hospital re-admissions for hospitals and programs such as the Program of All-Inclusive Care for the Elderly (PACE) in Pinellas County, Florida. Previous studies and systematic reviews demonstrated improvement in self-management and quality of life (QoL) in patients with HF with structured telephone support (STS) and short message service text messaging (SMS). OBJECTIVE: This study aimed to evaluate the effects of STS and SMS on self-care, knowledge, medication adherence, and QoL of patients with HF. METHODS: A prospective quality improvement project using a pre-post design was implemented. Data were collected at baseline, 30 days, and 3 months from 51 patients with HF who were enrolled in PACE in Pinellas County, Florida. All participants received STS and SMS for 30 days. The feasibility and sustained benefit of using STS and SMS was assessed at a 3-month follow-up. RESULTS: =0.81; P=.01). The results also demonstrated the sustained benefit with improved HF self-care maintenance, self-care management, self-care confidence, knowledge, medication adherence, and physical and mental health (SF-12) at 3 months with P<.05 for all outcomes. Living status and social support had a strong correlation with HF outcomes. Younger participants (aged less than 65 years) performed extremely well compared with older adults. CONCLUSIONS: STS and SMS were feasible to use among PACE participants with sustained benefits at 3 months. Implementing STS and SMS may serve as viable options to improve HF outcomes. Improving outcomes with HF affects hospital systems and the agencies that monitor and provide care for outpatients and those in independent or assisted-living facilities. Investigating viable options and support for implementation will improve outcomes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".