The Economic Impact of Community-Based Allied Health on the Acute Sector: A Systematic Review of Economic Evaluations
Bibliographic record
Abstract
Community-based allied health (AH) services have previously demonstrated a potential positive impact on acute care utilization, with wide acceptance among consumers. However, little is known about their economic impact. This systematic review aimed to address this gap. The primary outcomes of interest included: (a) costs of at least one type of acute care utilization; and (b) cost-effectiveness regarding acute care. The secondary outcomes of interest included total healthcare and/or non-healthcare costs. An a priori protocol was registered with PROSPERO [CRD42023437013]. Inclusion criteria were: (a) stand-alone interventions led by practitioners/graduates from one or more target AH professions; (b) reported acute care utilization costs as a primary or secondary outcome; (c) full or partial economic evaluations; and (d) studies published in English from 2010 onward. Eligible studies were identified from relevant bibliographic databases and gray literature search (September and October 2023). Modified McMaster Critical Appraisal Tool for quantitative studies, McGill Mixed Methods Appraisal Tool, and Consensus on Health Economic Criteria List were used to assess methodological quality. Narrative synthesis and cost-effectiveness planes were used for synthesizing and presenting the findings. Twelve studies, comprising eight cost analyses and four full economic evaluations, were included. Both single disciplinary (led by physiotherapists, dietitians, social workers, or exercise physiologists) and multidisciplinary (involved two to five AH professions) services were identified. Collectively, ten studies showed cost savings in acute care, while seven indicated varying degrees of cost-effectiveness and cost savings in total healthcare and non-healthcare, from pre-post and between-group comparisons. The findings demonstrated trends towards economic benefits of AH, highlighting their potential to alleviate the pressures on the acute sector and even the wider health system. However, the evidence is limited and of lower quality, emphasizing cautious interpretation. This review underscores the value of AH services and highlights key areas requiring action to strengthen the evidence base.
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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 | 0.031 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 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".