Abstract

Abstract Purpose To compare the cost‐efficiency of digitally designed and manufactured removable complete dentures (RCDs) with conventionally fabricated RCDs through a systematic review and meta‐analysis. Methods A comprehensive electronic and manual search was performed in PubMed, Embase, Web of Science, and Scopus up to February 10, 2025. Eligible studies included clinical trials and cohort studies comparing cost‐related outcomes of digital and conventional RCD workflows. Primary outcomes were laboratory, clinical, and total costs; secondary outcomes included the number of treatment sessions. Meta‐analyses were conducted using random‐effects models. Risk of bias was evaluated using standardized tools. Results Four retrospective studies and one prospective study, including 184 patients, met the inclusion criteria. No statistically significant differences were observed between digital and conventional workflows in laboratory costs (mean difference [MD]: –239.77 (2025 USD); p = 0.1063), clinical costs (MD: 74.39 (2025 USD); p = 0.4514), total costs (MD: –357.76 (2025 USD); p = 0.2577), or treatment sessions (MD: –1.47; p = 0.3514). Operator experience significantly influenced clinical costs ( p < 0.0001) and the number of sessions ( p = 0.0001). Conclusion Within the limitations of the available evidence, digital and conventional workflows for RCD fabrication demonstrated comparable cost‐efficiency. Although digital workflows may reduce the number of sessions when performed by experienced clinicians, the current evidence is insufficient to establish a clear cost‐efficiency advantage.

Keywords

CAD‐CAMconventional denturedigital denturedigital workflowhealth economicsmeta‐analysis

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Publication Info

Year
2025
Type
review
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Elena Mühlemann‐Kazanchian, Aspasia Pachiou, Gustavo Sáenz‐Ravello et al. (2025). Cost‐efficiency of digital versus conventional workflow for removable complete dentures: A systematic review and meta‐analysis. Journal of Prosthodontics . https://doi.org/10.1111/jopr.70074

Identifiers

DOI
10.1111/jopr.70074
PMID
41368723

Data Quality

Data completeness: 81%