Study protocol for a hospital-to-home transitional care intervention for older adults with multiple chronic conditions and depressive symptoms: a pragmatic effectiveness-implementation trial
Bibliographic record
Abstract
BACKGROUND: Older adults (> 65 years) with multiple chronic conditions (MCC) and depressive symptoms experience frequent transitions between hospital and home. Care transitions for this population are often poorly coordinated and fragmented, resulting in increased readmission rates, adverse medical events, decreased patient satisfaction and safety, and increased caregiver burden. There is a dearth of evidence on best practices in the provision of transitional care for older adults with MCC and depressive symptoms transitioning from hospital-to-home. This paper presents a protocol for a two-armed, multi-site pragmatic effectiveness-implementation trial of Community Assets Supporting Transitions (CAST), an evidence-informed nurse-led six-month intervention that supports older adults with MCC and depressive symptoms transitioning from hospital-to-home. The Collaborative Intervention Planning Framework is being used to engage patients and other key stakeholders in the implementation and evaluation of the intervention and planning for intervention scale-up to other communities. METHODS: Participants will be considered eligible if they are > 65 years, planned for discharged from hospital to the community in three Ontario locations, self-report at least two chronic conditions, and screen positive for depressive symptoms. A total of 216 eligible and consenting participants will be randomly assigned to the control (usual care) or intervention (CAST) arm. The intervention consists of tailored care delivery comprising in-home visits, telephone follow-up and system navigation support. The primary measure of effectiveness is mental health functioning of the older adult participant. Secondary outcomes include changes in physical functioning, depressive symptoms, anxiety, perceived social support, patient experience, and health and social service use and cost, from baseline to 6- and 12-months. Caregivers will be assessed for caregiver strain, depressive symptoms, anxiety, health-related quality of life, and health and social service use and costs. Descriptive and qualitative data from older adult and caregiver participants, and the nurse interventionists will be used to examine implementation of the intervention, how the intervention is adapted within each study region, and its potential for sustainability and scalability to other jurisdictions. DISCUSSION: A nurse-led transitional care strategy may provide a feasible and effective means for improving health outcomes and patient/caregiver experience and reduce service use and costs in this vulnerable population. TRIAL REGISTRATION: # NCT03157999 . Registration Date: April 4, 2017.
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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) | 0.000 | 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 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".