A quality improvement project targeting postoperative hospital revisit rates after pediatric appendicitis
Bibliographic record
Abstract
BACKGROUND: High rates of hospital revisits after pediatric appendectomy are costly to the health care system, patients, and families. We sought to trial a bundle of interventions targeted at reducing the rate of unnecessary revisits to hospital in this population. METHODS: In February 2021, a working group of relevant stakeholders was created. In June 2021, the group developed and implemented interventions to reduce revisits in a staggered fashion. Interventions included increased education provided to patients and their families, as well as nursing staff, revised discharge pamphlets, and a post-discharge phone call from our nurse practitioner. We tracked revisit rates prospectively using run charts with comparison to historical controls. RESULTS: We tracked revisit rates from July 2018 to October 2022. A total of 793 appendectomies were performed. There was a downward trend in revisit rates, from 16.7% before interventions to 13.4% after intervention implementation, for a relative reduction of 20%. In the postintervention period, 193 appendectomies were performed, with 78.0% contacted by our nurse practitioner in the early postoperative period. Of those contacted, 74% received the discharge pamphlet and 98.7% of respondents expressed that the phone call was useful. Almost all respondents stated they would want the follow-up phone call if they were to have another child with appendicitis. CONCLUSION: Simple, low-cost interventions aimed at improving education at time of discharge after pediatric appendectomy were associated with a reduction in unnecessary hospital revisits. Ongoing efforts are required to sustain results and assess efficacy of bundle elements to determine if additional initiatives may be beneficial in further reductions of revisits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 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".