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A Systematic Umbrella Review of the Effects of Teledentistry on Costs and Oral-Health Outcomes.

Janneke Francisca Maria ScheermanAlaa H QariBenoit VarenneHarmen BijwaardLaura SwinckelsNicolas GiraudeauBerno van MeijelRodrigo Mariño
Published in: International journal of environmental research and public health (2024)
Teledentistry offers possibilities for improving efficiency and quality of care and supporting cost-effective healthcare systems. This umbrella review aims to synthesize existing systematic reviews on teledentistry and provide a summary of evidence of its clinical- and cost-effectiveness. A comprehensive search strategy involving various teledentistry-related terms, across seven databases, was conducted. Articles published until 24 April 2023 were considered. Two researchers independently reviewed titles, abstracts and full-text articles. The quality of the included reviews was critically appraised with the AMSTAR-2 checklist. Out of 749 studies identified, 10 were included in this umbrella review. Two reviews focusing on oral-health outcomes revealed that, despite positive findings, there is not yet enough evidence for the long-term clinical effectiveness of teledentistry. Ten reviews reported on economic evaluations or costs, indicating that teledentistry is cost-saving. However, these conclusions were based on assumptions due to insufficient evidence on cost-effectiveness. The main limitation of our umbrella review was the critically low quality of the included reviews according to AMSTAR-2 criteria, with many of these reviews basing their conclusions on low-quality studies. This highlights the need for high-quality experimental studies (e.g., RCTs, factorial designs, stepped-wedge designs, SMARTs and MRTs) to assess teledentistry's clinical- and cost-effectiveness.
Keyphrases
  • meta analyses
  • healthcare
  • systematic review
  • randomized controlled trial
  • quality improvement
  • palliative care
  • case control
  • clinical trial
  • machine learning
  • single cell
  • social media
  • big data
  • pain management