Measuring continuity of care for cardiac patients: development of a patient self-report questionnaire.
Bibliographic record
Abstract
BACKGROUND: Continuity of care can be a challenge for cardiac patients, many of whom require chronic and complex management from a variety of health care personnel in multiple settings. For health services research, measures are needed that encompass the multifaceted nature of continuity of care for cardiac patients. OBJECTIVE: To assess continuity of care from the patient's perspective, a comprehensive self-report instrument of continuity of care for patients with congestive heart failure and atrial fibrillation was developed and validated. METHODS: Based on published work, patient interviews and provider input, the Heart Continuity of Care Questionnaire (HCCQ) was developed to assess various aspects of care in the transition from hospital to home. The HCCQ covered a variety of content areas relevant to cardiac care. The HCCQ and either the Continuity of Care Index (CCI) or the Minnesota Living with Heart Failure Questionnaire (MLHFQ) were completed by 83 patients who had been discharged for at least six months. RESULTS: Most items had good response rates. The subscales, defined a priori, had good reliability (subscales alpha ranged from 0.80 to 0.93). The HCCQ and its subscales had strong correlations with the CCI but not the MLHFQ. The HCCQ subscales demonstrated better known group validity than the CCI. CONCLUSIONS: In this preliminary study, the HCCQ appears to be a comprehensive, reliable and valid measure of continuity of care from the patient perspective. Further studies of the validity, generalizability and use are needed.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".