2017 Journal of oral rehabilitation

Computer-assisted technologies used in oral rehabilitation and the clinical documentation of alleged advantages - a systematic review.

Journal of oral rehabilitation Vol. 44 (4) : 261-290 • Apr 2017

The objective of this systematic review is to identify current computer-assisted technologies used for managing patients with a need to re-establish craniofacial appearance, subjective discomfort and stomatognathic function, and the extent of their clinical documentation. Electronic search strategies were used for locating clinical studies in MEDLINE through PubMed and in the Cochrane library, and in the grey literature through searches on Google Scholar. The searches for commercial digital products for use in oral rehabilitation resulted in identifying 225 products per November 2016, used for patient diagnostics, communication and therapy purposes, and for other computer-assisted applications in context with oral rehabilitation. About one-third of these products were described in about 350 papers reporting from clinical human studies. The great majority of digital products for use in oral rehabilitation has no clinical documentation at all, while the products from a distinct minority of manufacturers have frequently appeared in more or less scientific reports. Moore's law apply also to digital dentistry, which predicts that the capacity of microprocessors will continue to become faster and with lower cost per performance unit, and innovative software programs will harness these improvements in performance. The net effect is the noticeable short product life cycle of digital products developed for use in oral rehabilitation and often lack of supportive clinical documentation. Nonetheless, clinicians must request clinically meaningful information about new digital products to assess net benefits for the patients or the dental professionals and not accept only technological verbiage as a basis for product purchases.

No clinical trial protocols linked to this paper

Clinical trials are automatically linked when NCT numbers are found in the paper's title or abstract.
PICO Elements

No PICO elements extracted yet. Click "Extract PICO" to analyze this paper.

Paper Details
MeSH Terms
Associated Data

No associated datasets or code repositories found for this paper.

Related Papers

Related paper suggestions will be available in future updates.