The Economic Impact of Community Paramedics Within Emergency Medical Services: A Systematic Review

Abstract

Background and objective: Globally, emergency medical services (EMSs) report that their demand is dominated by non-emergency (such as urgent and primary care) requests. Appropriately managing these is a major challenge for EMSs, with one mechanism employed being specialist community paramedics. This review guides policy by evaluating the economic impact of specialist community paramedic models from a healthcare system perspective.

Methods: A multidisciplinary team (health economics, emergency care, paramedicine, nursing) was formed, and a protocol registered on PROSPERO (CRD42023397840) and published open access. Eligible studies included experimental and analytical observational study designs of economic evaluation outcomes of patients requesting EMSs via an emergency telephone line ('000', '111', '999', '911' or equivalent) responded to by specialist community paramedics, compared to patients attended by usual care (i.e. standard paramedics). A three-stage systematic search was performed, including Peer Review of Electronic Search Strategies (PRESS) and Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). Two independent reviewers extracted and verified 51 unique characteristics from 11 studies, costs were inflated and converted, and outcomes were synthesised with comparisons by model, population, education and reliability of findings.

Results: Eleven studies (n = 7136 intervention group) met the criteria. These included one cost-utility analysis (measuring both costs and consequences), four costing studies (measuring cost only) and six cohort studies (measuring consequences only). Quality was measured using Joanna Briggs Institute tools, and was moderate for ten studies, and low for one. Models included autonomous paramedics (six studies, n = 4132 intervention), physician oversight (three studies, n = 932 intervention) and/or special populations (five studies, n = 3004 intervention). Twenty-one outcomes were reported. Models unanimously reduced emergency department (ED) transportation by 14-78% (higher quality studies reduced emergency department transportation by 50-54%, n = 2639 intervention, p < 0.001), and costs were reduced by AU$338-1227 per attendance in four studies (n = 2962). One study performed an economic evaluation (n = 1549), finding both that the costs were reduced by AU$454 per attendance (although not statistically significant), and consequently that the intervention dominated with a > 95% chance of the model being cost effective at the UK incremental cost-effectiveness ratio threshold.

Conclusions: Community paramedic roles within EMSs reduced ED transportation by approximately half. However, the rate was highly variable owing to structural (such as local policies) and stochastic (such as the patient's medical condition) factors. As models unanimously reduced ED transportation-a major contributor to costs-they in turn lead to net healthcare system savings, provided there is sufficient demand to outweigh model costs and generate net savings. However, all models shift costs from EDs to EMSs, and therefore appropriate redistribution of benefits may be necessary to incentivise EMS investment. Policymakers for EMSs could consider negotiating with their health department, local ED or insurers to introduce a rebate for successful community paramedic non-ED-transportations. Following this, geographical areas with suitable non-emergency demand could be identified, and community paramedic models introduced and tested with a prospective economic evaluation or, where this is not feasible, with sufficient data collection to enable a post hoc analysis.

Fig. 1

An illustration of how community paramedic interventions compare to other paramedic roles’ interventions. IM intramuscular, IN intranasal, IO intraosseous, IV intravenous, MDI metered-dose inhaler, PEG percutaneous endoscopic gastrostomy, PO oral, PR per rectal, SC subcutaneous, SL  sublingual

Fig. 2

Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) diagram of the search results

Fig. 3

Relative risk of emergency department (ED) transportation by community paramedics compared to standard paramedics. CIs confidence intervals