Measuring Processes of Integrated Care for Hospital to Home Transitions
Bibliographic record
Abstract
BACKGROUND: Integrated care is a promising approach to improve transitions from hospital for older adults. Measures of integrated care tend to be survey-based or outcomes focused. This study determined the feasibility of using hospital chart data to measure integrated processes of care. METHODS: This paper reports on two objectives: 1) the development of an integrated care transition framework and associated features of care; 2) a pilot study to test if the features could be applied to 214 hospital patient charts. RESULTS: Twenty-four features were tested, and fifteen features could be reliably measured using chart review. Of these, the percent of patients classified as receiving integrated care varied widely across the items, from 0.05% to 84.1%. DISCUSSION: The framework presented in this paper can guide measurement of system and clinical delivery of integrated care transitions. In combination with other tools, chart review can provide perspective on day-to-day care delivery not otherwise accessible, and highlight areas requiring practice change. CONCLUSION: Multiple measurement perspectives are needed to improve our understanding of how integrated care is being implemented. While chart review cannot address the full breadth of integrated care, it can help understand how processes of care are being implemented in routine daily care.
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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 | 0.022 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".