Intensive Case Management to Reduce Hospital Readmissions
Bibliographic record
Abstract
PURPOSE OF STUDY: Hospital readmissions burden the U.S. health care system, and they have negative effects on patients and their families. The primary aim of this study was to pilot an intensive case management (ICM) intervention to reduce 30-day hospital readmissions. A secondary aim was to obtain patient- and caregiver-reported reasons for readmission. PRIMARY PRACTICE SETTING: The setting was a vertically integrated health care system located in Northern California. METHODOLOGY AND SAMPLE: This pilot quality improvement project occurred over a 4-month period. The intervention was delivered by master's degree students in nurse case management through an academic-clinical partnership. Patients hospitalized with a 30-day readmission were offered the ICM intervention. A total of 36 patients were identified and 20 accepted. Patient and/or caregiver was interviewed to identify reasons for their readmission. Data were collected about pre-/post-health care utilization including subsequent 30-day readmission. Mixed methods were used to analyze the findings. RESULTS: Thirteen of 20 enrolled patients received the weekly ICM intervention for at least 30 days. Seven declined further contact before 30 days. Patient-reported reasons for readmission included being discharged too soon, poor communication among providers and with patients/families, lack of understanding about disease management and/or treatment options, and inadequate support. Several patients believed that their readmission was unavoidable due to the complexity of their illnesses. We compared 30-day readmissions for those who participated in and those who declined the ICM intervention, finding that those who received the ICM intervention had a lower readmission rate than those who did not receive the intervention (35% vs. 37.5%).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".