Economic evaluation of advanced practice physiotherapy models of care: a systematic review with meta-analyses
Bibliographic record
Abstract
BACKGROUND: The objective of this systematic review is to appraise evidence on the economic evaluations of advanced practice physiotherapy (APP) care compared to usual medical care. METHODS: Systematic searches were conducted up to September 2021 in selected electronic bibliographical databases. Economic evaluation studies on an APP model of care were included. Economic data such as health care costs, patient costs, productivity losses were extracted. Methodological quality of included studies was assessed with the Effective Public Health Practice Project tool and the Critical Appraisal Skills Programme checklist. Meta-analyses were performed and mean differences (MD) in costs per patient were calculated using random-effect inverse variance models. Certainty of the evidence was assessed with the GRADE Approach. RESULTS: Twelve studies (n = 14,649 participants) including four randomized controlled trials, seven analytical cohort studies and one economic modeling study were included. The clinical settings of APP models of care included primary, emergency and specialized secondary care such as orthopaedics, paediatrics and gynaecology. The majority of the included participants were adults with musculoskeletal disorders (n = 12,915). Based on low quality evidence, health system costs including salaries, diagnostic tests, medications, and follow-up visits were significantly lower with APP care than with usual medical care, at 2 to 12-month follow-up (MD: - 145.02 €/patient; 95%CI: - 251.89 to - 38.14; n = 7648). Based on low quality evidence, patient costs including travel and paid medication prescriptions, or treatments were significantly higher with APP care compared to usual medical care, at 2 to 6-month follow-up (MD: 22.18 €/patient; 95%CI: 0.40 to 43.96; n = 1485). Based on very low quality evidence, no significant differences in productivity losses per patient were reported between both types of care (MD: 450 €/patient; 95%CI: - 80 to 970; n = 819). CONCLUSIONS: This is the first systematic review and meta-analysis on the economic evaluation of APP models of care. Low quality evidence suggests that APP care might result in lower health care costs, but higher patient costs compared to usual medical care. Costs differences may vary depending on various factors such as the cost methodology used and on the clinical setting. More evidence is needed to evaluate cost benefits of APP models of care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".