A cross-sectional evaluation of the idiopathic pulmonary fibrosis patient satisfaction and quality of life with a care coordinator
Bibliographic record
Abstract
BACKGROUND: Canadian and international guidelines recommend specialized, multidisciplinary teams for the treatment of patients with idiopathic pulmonary fibrosis (IPF). The objective of this cross-sectional clinical study was to investigate the effect of a care coordinator on IPF patient satisfaction and quality of life. METHODS: Forty IPF patients were enrolled from the practices of two physicians (n=20/physician), with either low (LCU) or high-coordinator use (HCU). Patient satisfaction was measured with modified FAMCARE and IPF Care UK Patient Support Program (UK-CARE) surveys. Health related quality of life (HRQoL) was assessed with the living with IPF impacts (L-IPFi) survey. An economic model assessed the impact of the coordinator; staff surveys informed patient management requirements, and costs were derived from published literature. RESULTS: Patient satisfaction was similar between the clinics; a trend (P=0.1) towards increased satisfaction among HCU patients was observed. Patients in the HCU clinic reported increased satisfaction (P<0.05) with their current care compared with care prior to joining the tertiary-care clinic, while LCU patients did not. IPF patient HRQoL did not differ between clinics. The coordinator was estimated to alleviate approximately 30% of a physician's IPF-related work load, and to facilitate the care of more patients per physician. Modelled estimates suggest the coordinator lead to annual cost-savings of $137,212. CONCLUSIONS: Reliance upon a coordinator during routine management of IPF patients may improve patient satisfaction, spare physician time and lead to annual cost-savings. Future studies should examine the impact of a coordinator on healthcare resource utilization.
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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 | 0.005 | 0.009 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".