Assessing innovative care models for musculoskeletal disorders’ management in the emergency department using Time-Driven Activity-Based Costing
Bibliographic record
Abstract
Abstract Objectives Compare the average cost of an emergency department (ED) visit between three ED care models, namely management by an emergency physician (EP) alone (usual care), management by a primary contact physiotherapist (PT) and an EP (intervention), and management by a PT alone (sensitivity analysis). Methods Cost study (Canadian Public Payer perspective) based on data collected during a pragmatic randomized clinical trial (2018-2019) conducted in an urban Canadian academic ED (CHUL, Quebec City, Canada; n=78, 18-80 years old). Costs incurred for the management of persons presenting to the ED for a minor musculoskeletal disorder (MSKD) were calculated using Time-Driven Activity-Based Costing, in which time invested with a patient determines care costs. The main outcome measure was the average cost of an ED visit. Generalized linear models with Gamma distributions and log links were used to assess whether there were significant differences in average costs between the care models. Results Mean ED visit cost was $267.08 (2019 $CAD, 95%CI: $212.75, $346.40) for PT and EP management, compared with $245.14 for EP management ($169.46, $336.72), resulting in a non- significant absolute difference of 21.94 CAD/patient ($-87.33, $132.63) between models (p=.60). Sensitivity analyses showed that the average cost of ED management by a PT was $194.38 ($161.50, $234.34), representing a non-significant average saving of 50.76 CAD/patient ($- 156.91, $37.54) compared to EP management. Conclusion This study is a first step towards a better understanding of the costs incurred by the Canadian Public Payer for the management of persons presenting with MSKDs in the ED. Primary contact physiotherapists have the potential to complement care of MSKD ED patients without increasing healthcare costs.
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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 | 0.040 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.011 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".