A241 PRICE: PREVENTING READMISSIONS IN IBD CENTRES OF EXCELLENCE
Bibliographic record
Abstract
Abstract Background Hospital readmission rates are high in the IBD population, with 20% of patients readmitted within the same calendar year. Hospital discharge processes are not routinely standardized and deficiencies in the transition of care after discharge puts patients at increased risk of illness, hospital utilization and healthcare cost. In addition to increased healthcare expenditure, hospitalizations for IBD patients are associated with nosocomial complications such as venous thromboembolism and infection. Aims We hypothesize that implementing standardized follow-up by an IBD practice nurse and electronic health outcome monitoring through NoviSurvey can reduce the risk of hospital readmission compared to current approaches of hospital discharge alone. Methods This parallel randomized control trial is powered for N=400 and will include patients admitted for an IBD flare without requiring surgical intervention from the gastroenterology service or consulted from general internal medicine. Patients randomized to the control arm are discharged with usual standard of care. Patients in the intervention group will be eligible for usual post-discharge care in addition to organized telephone follow-up by an IBD practice nurse at 1, 7 and 30 days post-discharge. In addition, these patients will receive bi-weekly correspondence from NoviSurvey to complete a short questionnaire on clinical disease severity and medication adherence. Based on telephone interaction and survey scores, the IBD nurse may arrange readmission or expedited ambulatory visit for high-risk patients. Results 15 patients are currently enrolled into our study, with 7 randomized to the intervention and 8 to the control group. In the control group, 25% of patients were readmitted to hospital within 30 days of discharge and 13% failed to follow their steroid taper. There were no patients in the intervention group who were readmitted to hospital within 30 days and none who failed their steroid taper. In both the control or intervention group, there were no occurrences of deep vein thrombosis within 30 days post-discharge. Conclusions The preliminary findings in our small sample study indicate that a nurse led post-discharge intervention may translate to benefits including decreased readmission rates to hospital, better patient satisfaction and better medication adherence. Funding Agencies CCC
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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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.002 |
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".