Using big data to promote precision oral health in the context of a learning healthcare system

Joseph Finkelstein, Frederick Zhang, Seth A. Levitin, David Cappelli

Research output: Contribution to journalReview articlepeer-review

17 Scopus citations

Abstract

There has been a call for evidence-based oral healthcare guidelines, to improve precision dentistry and oral healthcare delivery. The main challenges to this goal are the current lack of up-to-date evidence, the limited integrative analytical data sets, and the slow translations to routine care delivery. Overcoming these issues requires knowledge discovery pipelines based on big data and health analytics, intelligent integrative informatics approaches, and learning health systems. This article examines how this can be accomplished by utilizing big data. These data can be gathered from four major streams: patients, clinical data, biological data, and normative data sets. All these must then be uniformly combined for analysis and modelling and the meaningful findings can be implemented clinically. By executing data capture cycles and integrating the subsequent findings, practitioners are able to improve public oral health and care delivery.

Original languageEnglish
Pages (from-to)S43-S58
JournalJournal of Public Health Dentistry
Volume80
Issue numberS1
DOIs
StatePublished - 1 Mar 2020

Keywords

  • big data
  • learning health system
  • precision medicine
  • public health dentistry

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