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Invited Commentary
Nov/Dec 2017

Harnessing the Power of Data in Facial Plastic and Reconstructive Surgery—From Refuse to Riches

Author Affiliations
  • 1Department of Otolaryngology–Head & Neck Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland
  • 2Associate Editor, JAMA Facial Plastic Surgery
  • 3Department of Otolaryngology and Communication Sciences, Medical College of Wisconsin Clinic at Froedtert West, Milwaukee
  • 4Editor, JAMA Facial Plastic Surgery
JAMA Facial Plast Surg. 2017;19(6):532-533. doi:10.1001/jamafacial.2017.1484

The widespread use of electronic health records (EHRs) has created unprecedented opportunities to apply meaningful clinical data for quality improvement. Through machine learning, large data sets of patient clinical information gathered through routine clinical encounters can be analyzed for risk prediction and treatment algorithms. Although randomized clinical trials remain the criterion standard study type to show causality, the use of big data is showing promise as an alternative for discovery.1 This alternative is of particular significance in surgery, where randomized clinical trials are not feasible or likely.

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