Abstract 3468: Emerging lessons from patient-reported hospital discharge experiences among hospitalized cancer patients with frequent emergency department use
Bibliographic record
Abstract
Abstract Background: While teamwork is essential to providing high-quality patient-centered care, challenges in interprofessional collaboration and decision-making in the hospital settings are common, especially for cancer patients. The purpose of this study was to identify emerging themes related to hospital discharge experiences among patients hospitalized for cancer who became frequent emergency department (ED) users following their hospital discharge. Design & Methods: A cohort of cancer patients discharged from an academic health center in Montreal (Canada) between October 2014 and November 2016 was assembled. Frequent ED (FED) users were identified as patients who had a > 4 ED visits in the year following hospital discharge using health administrative claims from the provincial universal health care program. Qualitative analysis of telephone interviews conducted with patients 30 days’ post-discharge were used for in-depth exploratory analyses to characterize hospital discharge experiences and transition process from the hospital to the community. Results: A cohort of 1253 cancer patients was formed. The mean age was 70.9 (SD=11.8) and the most frequent cancers included 488 (38.9%) respiratory and 309 (24.6%) upper digestive cancer. Overall, 14.5% (n=182) of patients became FED users. Content analyses revealed the most common emerging themes from the FED patients interviews on hospital discharge experiences. These included:1. Early hospital discharge putting patients at high risk of being re-admitted and going back to the ER shortly after that. Some patients mentioned post-discharge complications and emerging of new health issues that could have been avoided if patient was kept in the hospital for longer.2. Lack of communication between different specialists at the hospital. Some patients mentioned the help of a nurse as crucial during inpatient stays in maintaining communication between doctors. 3. Lack of communication of medications prescribed. Some patients mentioned the lack of communication of what doses was modified, what medications were stopped and which ones were newly prescribed.4. The need to schedule follow-up appointments at the time of hospital discharge. This becomes especially important for vulnerable patients who have been on pain medication during the hospital stay, affecting their cognitive abilities and making post-discharge planning more difficult. Conclusions: This study using integrated data from administrative claims and patient interviews provided insights into the challenges related to hospital discharge experiences and transition into community among hospitalized cancer patients with frequent emergency department use. Application of our findings could assist in hospital discharge preparation and improvement in healthcare delivery and health outcomes. Citation Format: Siyana Kurteva, Robyn Tamblyn. Emerging lessons from patient-reported hospital discharge experiences among hospitalized cancer patients with frequent emergency department use [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3468.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".