Characteristics of Patients Receiving Complex Case Management in an Acute Care Hospital
Bibliographic record
Abstract
BACKGROUND: Improving transitions in care is a major focus of health care planning. In the research team's prior intervention study, the length of stay (LOS) was reduced when patients at high risk for readmission were identified early in their acute care stay and received complex management. OBJECTIVE: This study will describe the characteristics of patients receiving complex case management in an urban acute care hospital. PRIMARY PRACTICE SETTING: Acute care hospital. METHODOLOGY AND SAMPLE: This was a retrospective chart review of patients in a previous quality assurance study. A random selection of patients who previously underwent high-risk screening using the LACE (Length of stay; Acuity of the admission; Comorbidity of the patient; Emergency department use) index and received complex case management (the intervention group) were reviewed. The charts of a random selection of patients from the previous comparison group were also reviewed. Patient characteristics were collected and compared using descriptive statistics. RESULTS: In the intervention group, more patients had their family physicians (FPs) documented (93.1% [81/87] vs. 89.2% [66/74]). More patients in the intervention group (89.7% [77/87] vs. 85.1% [63/74]) lived at home prior to admission. More patients in the intervention group had a family caregiver involved (44.8% [39/87] vs. 41.9% [31/74]). At discharge, more patients in the intervention group (87.1% [74/85]) were discharged home compared with the comparison group (78.4% [58/74]). IMPLICATIONS FOR CASE MANAGEMENT PRACTICE: (1) Having an identified FP, living at home, and having family caregiver(s) characterized those with lower LOS and discharged home. (2) Case management, risk screening, and discharge planning improve patient outcomes. (3) This study identified the importance of having a FP and engaged family caregivers in improving care outcomes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".