Impact on quality of life of two emergency department care models for people presenting with a musculoskeletal disorder
Bibliographic record
Abstract
Context The addition of physiotherapists (PTs) to the emergency department (ED) is an emerging initiative aimed at optimizing patient flow through the ED. A number of studies have demonstrated that this care model has several benefits, such as increasing patient satisfaction towards care received and reducing healthcare resource utilization during and after the ED visit. However, no study has looked at its impact on patients’ health-related quality of life. Objective Compare the three-month change in health-related quality of life of people presenting to the ED with a minor musculoskeletal disorder (MSKD) and managed through two different care models. Study Design Evaluation of health-related quality-of-life data captured alongside a prospective randomized clinical trial (NCT04009369). Setting ED of the CHU de Québec–Université Laval (Quebec, Canada). Population Studied People aged 18 to 80 presenting to the ED with a minor MSKD (n=56). Intervention Management by a PT and an emergency physician (EP), or management by an EP according to standard practice. Outcome Measures. Qualityadjusted life-years (QALY). Participants’ health-related quality of life was measured at the initial ED visit and at one- and three-month follow-ups using the EQ-5D-5L. Responses to the questionnaires were transformed into utility scores using the Canadian conversion algorithm for an adult population. Each participant’s utility score was then transformed into QALYs. As recommended in economic guidelines, differences between scores were compared using the EQ-5D-5L minimal important difference (MID). Results The utility scores of the two groups were almost identical at baseline ([Group: Mean, 95%CI] EP: 0.536, 0.421-0.651 vs PT and EP: 0.537, 0.427-0.646). At three months, utility scores were higher in the group managed by the PT and EP, but the difference was not clinically significant (MID: 0.074, [Group: Mean, 95%CI] EP : 0.784, 0.624-0.943 vs PT and EP: 0.852, 0.686-1.017). Participants managed by the PT and EP showed a gain of 0.069 QALYs after three months, compared with 0.062 for those treated in the usual way (mean difference: 0.017). Expected Outcomes. Management by a PT and an EP in the ED achieves a level of health-related quality of life that is at least as high as that of the usual care by an EP. However, further studies with a larger sample size are needed to confirm the results observed.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 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) | 0.004 | 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".