Bibliographic record
Abstract
Introduction and Objective: given the increasing demand for health services and resource limitations, effective management is required to prevent the loss of hospital resources and facilities and optimize their activities by using various management methods.Re-hospitalization of patients accounts for significant part of preventable costs in the health care system.Methodology: This descriptive-analytical research was conducted in the form of a retrospective cohort study on patients admitted to Imam Khomeini Hospital since fall 2011 to fall 2012, who were re-hospitalized one month after discharge.Results: out of all patients admitted during the one-year period, 5.6% (1560 patients), were re-hospitalized during 30 days.Among the hospitalized factors, incomplete treatment, treatment failure, hospital infection and complications of surgery had the greatest impact on the re-hospitalization of patients, and among the clinical factors, recurrence of disease, being affected by new disease, severe disease, mental disease, concomitant disease, the use of high-risk drugs, addiction to psychotropic drugs and opiates had the greatest impact on the rehospitalization of patients, and among the factors related to the patient, the factor of age had the greatest impact on the re-hospitalization of patients.Conclusion: based on the research results, proper management of hospital resources, observing therapeutic protocols and safety standards in the hospital, paying special attention to vulnerable groups, using modern therapeutic methods and providing the necessary training to the medical staff and patients at the time of discharge can reduce the re-hospitalization of patients and lead to proper use of resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.996 | 0.997 |
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; both teacher heads agree on what is shown here.
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".