974 Implementation of Long-term Outcomes for Burn Patients in BCQP – Lessons Learned
Bibliographic record
Abstract
Abstract Introduction Burn registries systematically collect burn-specific data to better understand the epidemiology, clinical care and outcomes. However, there is a gap in data regarding outcomes as patients transition from inpatient to outpatient care. Collecting burn injury-related data post-discharge can inform clinicians and improve long-term outcomes. In January 2024, the American Burn Association’s Burn Care Quality Platform (BCQP) implemented variables for long-term outcomes (LTO) for patients transitioning to outpatient follow-up after inpatient discharge. Methods The data for the period January 1 – July 31st, 2024, was retrieved from BCQP. The software provider analyzed the data and provided a report of the burn centers who submitted data for LTOs for burn patients who were admitted. The variables were available only for centers who uses the full platform. Data interpretation and visualization were reviewed, and feedback was provided to the software provider to improve the readability of such reports. Results Over seven months, 67 burn centers entered 9,124 discharged cases; 3,061 had wound closure variables documented. Forty-three centers completed follow-up on over 10% of their discharges, with 32 centers documenting more than 50%. Follow-up was documented in 2,360 cases, with completion in 634 (39 centers) and 1,248 ongoing. A total of 176 surgical procedures were performed in 122 unique cases, mostly as outpatients. Clinical evaluation was the most frequent method of scar assessment (1,870 records), followed by the Vancouver scale (402) and modified scale (211). Documentation of depression, PTSD, and ASD was minimal, while itch was noted in 1,516 records. Changes for documenting pain were introduced; 5,513 records for 1,880 unique cases from 42 centers showed 1,570 records with pain requiring prescriptions, 890 needing over-the-counter medication, and 219 still in pain but without medication. In 1670 records the pain was not present. Only in 899 records the presence of pain was not documented. Conclusions There was a high uptake of documented LTOs after patients were discharged from the burn centers. Initial data reveals the importance of collecting data on outpatients to better understand long term outcomes of patients with burn injuries. All variables will be reviewed at the end of the year based on the feedback received from registrars on open house sessions. Applicability of Research to Practice collection of the long terms outcomes for patients after discharge from their burn centers is essential and will provide further information about the impact that burn injuries has on long term on patients and their families Funding for the Study N/A
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 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 | 0.054 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".