Cost effects of nurse led triage at an emergency department with the advice to consult the adjacent general practice cooperative for low-risk patients, a cluster randomised trial
Abstract
BACKGROUND: During the TRIAGE trial, emergency nurses diverted 13.3% of patients with low-risk complaints from a Belgian emergency department (ED) to the adjacent general practitioner cooperative (GPC). We examined the effects of this diversion on the total cost, insurance costs and patient costs, as charged on the invoice. Changes in the cost composition and the direct impact on revenues of both locations were examined as a secondary objective.
METHODS: The differences in costs between intervention and control weekends were tested with two-sample t-tests and Kolmogorov-Smirnov (KS) tests. For the main outcomes an additional generalised linear model was created. Proportions of patients charged with certain costs were examined using Pearson's chi-square tests. Average revenues per weekend were compared using pooled t-tests.
RESULTS: During intervention weekends, total costs increased by 3% (€3.3). The costs decreased by 8% (€2.2) for patients and increased by 6% (€5.5) for insurance, mainly driven by differences in physician fees. More patients were charged a consultation fee only (25% vs. 19%, p-value<0.01). The GPC's revenues increased by 13% (p-value=0.06); no change was found for the ED's revenues.
CONCLUSION: The intervention reduced costs slightly for patients, while total costs and insurance costs slightly increased. When implementing triage systems with primary care involvement, the effects on the costs and revenues of the stakeholders should be monitored.
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.