Service redesign interventions to reduce waiting time for paediatric rehabilitation and therapy services: A systematic review of the literature
Bibliographic record
Abstract
Despite well-documented benefits of rehabilitation and therapy services for children with disabilities, long waiting lists to access these services are common. There is a growing body of evidence, primarily from mixed or adult services, demonstrating that waiting times can be reduced through strategies that target wasteful processes and support services to keep up with demand. However, providers of rehabilitation and therapy services for children face additional complexities related to the long-term nature of many developmental conditions and the need to consider timing of interventions with developmental milestones and education transition points. This review aimed to synthesise available evidence on service redesign strategies in reducing waiting time for paediatric therapy services. We conducted a systematic review of studies conducted in outpatient paediatric rehabilitation or therapy settings, including physical and mental health services, evaluating a service redesign intervention and presenting comparative data on time to access care. Two reviewers independently applied inclusion criteria, assessed risk of bias and extracted data. Findings were analysed descriptively and the certainty of evidence was synthesised according to criteria for health service research. From 1934 studies identified, 33 met the criteria for inclusion. Interventions were categorised as rapid response strategies, process efficiency interventions or substitution strategies (using alternative providers in place of medical specialists). Reductions in waiting time were reported in 30 studies. Evidence is limited by study designs with high risk of bias, but this is mitigated by consistency of findings and large effect sizes. There is moderate-certainty evidence that service redesign strategies similar to those used in adult populations can be applied in paediatric rehabilitation and therapy settings to reduce waiting time.
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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 | 0.015 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".