Utilization and cost of a new model of care for managing acute knee injuries: the Calgary acute knee injury clinic
Bibliographic record
Abstract
BACKGROUND: Musculoskeletal disorders (MSDs) affect a large proportion of the Canadian population and present a huge problem that continues to strain primary healthcare resources. Currently, the Canadian healthcare system depicts a clinical care pathway for MSDs that is inefficient and ineffective. Therefore, a new inter-disciplinary team-based model of care for managing acute knee injuries was developed in Calgary, Alberta, Canada: the Calgary Acute Knee Injury Clinic (C-AKIC). The goal of this paper is to evaluate and report on the appropriateness, efficiency, and effectiveness of the C-AKIC through healthcare utilization and costs associated with acute knee injuries. METHODS: This quasi-experimental study measured and evaluated cost and utilization associated with specific healthcare services for patients presenting with acute knee injuries. The goal was to compare patients receiving care from two clinical care pathways: the existing pathway (i.e. comparison group) and a new model, the C-AKIC (i.e. experimental group). This was accomplished through the use of a Healthcare Access and Patient Satisfaction Questionnaire (HAPSQ). RESULTS: Data from 138 questionnaires were analyzed in the experimental group and 136 in the comparison group. A post-hoc analysis determined that both groups were statistically similar in socio-demographic characteristics. With respect to utilization, patients receiving care through the C-AKIC used significantly less resources. Overall, patients receiving care through the C-AKIC incurred 37% of the cost of patients with knee injuries in the comparison group and significantly incurred less costs when compared to the comparison group. The total aggregate average cost for the C-AKIC group was $2,549.59 compared to $6,954.33 for the comparison group (p <.001). CONCLUSIONS: The Calgary Acute Knee Injury Clinic was able to manage and treat knee injured patients for less cost than the existing state of healthcare delivery. The combined results from this study show that the C-AKIC is an appropriate, effective, and efficient model of clinical care for patients presenting with acute knee injuries.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".