Impact of a multidisciplinary interstitial lung disease clinic on healthcare utilization
Bibliographic record
Abstract
RATIONALEA minimal amount is known of the impact that a multidisciplinary interstitial lung disease (ILD) clinic with dedicated nursing support may have on healthcare utilization.OBJECTIVES The objective of this study is to determine if there is a reduction in healthcare utilization including emergency room (ER) visits, hospitalizations, and hospitalization costs in the year after a patient is assessed in the ILD clinic.METHODS This retrospective study evaluated the number of ER visits and hospitalizations 1 year before and after being seen in an ILD clinic. For those with hospitalizations, length of stay (LOS) and cost of each stay were collected. Pre- and post-ILD clinic outcomes were compared using Mann-Whitney and Wilcoxon rank sum test.MEASUREMENTS AND MAIN RESULTSA total of 202 patients were screened and 140 included in the analysis. Mean age was 66 years (±12), and 47% were female. Mean forced vital capacity percentage predicted was 77% (±22). There was no significant difference in the pre- and post-ILD clinic mean number of ER visits per patient (p = 0.33) nor hospitalizations (p = 0.91). LOS was shorter in the post-ILD clinic period (10.8 ± 10.5 days) versus pre-ILD clinic visit (18.8 ± 25.4 days), although not statistically significant (p = 0.30). Pre-ILD clinic visit mean hospitalization cost was $24,881.89 (±35,817.48) and post-ILD clinic visit was $16,751.68 (±16,549.74) although not statistically different (p = 0.66).CONCLUSIONS We found no statistically significant difference in ER visits, hospitalizations or hospitalization costs post-ILD multidisciplinary clinic assessment in our ILD cohort. However, there was a trend toward lower overall healthcare utilization and cost in the year post-ILD clinic.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".