Healthcare resource utilization, treatment patterns, and cost of care among patients with thermal burns and inpatient autografting in two large privately insured populations in the United States
Bibliographic record
Abstract
The current standard of care for severe burns includes autografting; however, there is scarce knowledge regarding the long-term economic burden associated with thermal burns and inpatient autografting. The objective of this study was to characterize healthcare resource utilization, treatment patterns, and cost of care for thermal burn patients in two large privately insured populations in the United States who underwent inpatient autografting between 01/01/2011 and 06/30/2016. Patient demographics, clinical characteristics, healthcare resource utilization, and total cost were examined during baseline (one year before the initial hospitalization with autografting) and two-year evaluation period. There was a substantial economic burden on thermal burn patients who received inpatient autografts (HIRD® database [HIRD]: N=371, mean age=39.6 years, male=67.1%; MarketScan® database [MarketScan]: N=698, mean age=38.2 years, male=63.3%) in the year 1 evaluation period (HIRD: mean=$184,805; MarketScan: mean=$155,272), which was mainly driven by the initial hospitalization with autografting (HIRD: mean=$157,384 and MarketScan: mean=$131,470). The percentage of patients with burn-related healthcare resource utilization and average burn-related costs were considerably reduced in the year 2 evaluation period (HIRD: mean=$3020; MarketScan: mean=$1990). Consistent with previous studies, mean length of hospital stay (days) and mean total medical costs generally increased as the percentage of total body surface area burned increased.
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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 | 0.000 | 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) | 0.000 | 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".