Two Ways of Knowing: Big Data and Evidence-Based Medicine

Ideas and Opinions19 April 2016Two Ways of Knowing: Big Data and Evidence-Based MedicineIda Sim, MD, PhDIda Sim, MD, PhDFrom University of California, San Francisco, San Francisco, California. Author, Article, and Disclosure Informationhttps: //doi. org/10. 7326/M15-2970 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Evidence-based medicine (EBM) is more than 20 years old (1). Although EBM's painstaking path of careful clinical studies, critical appraisal of published evidence, and methodologically rigorous systematic reviews has been the template for knowing what works in medicine, new "big data" approaches seem to offer a powerful and tempting alternative. Big data are a distinct "cultural, technological, and scholarly phenomenon" (2) centered on the application of machine learning algorithms to diverse, large-scale data. As clinics and hospitals generate huge amounts of electronic health record (EHR) data and systems like IBM's Watson system combine genomic data, published literature, and EHR data. . . References1. Evidence-Based Medicine Working Group. Evidence-based medicine. A new approach to teaching the practice of medicine. JAMA. 1992;268: 2420-5. PMID: 1404801 CrossrefMedlineGoogle Scholar2. Boyd D, Crawford K. Critical questions for big data. Information, Communication 15: 662-79. CrossrefGoogle Scholar3. IBM Watson for Oncology. Accessed at www. ibm. com/smarterplanet/us/en/ibmwatson/watson-oncology. html on 9 December 2015. Google Scholar4. Savov V. Google signs deal to put sensors directly on your eye. The Verge. 15 July 2014. Accessed at www. theverge. com/2014/7/15/5900871/google-and-novartis-smart-contact-lens-partnership on 9 December 2015. Google Scholar5. Press G. 6 Predictions for the 125 Billion Big Data Analytics Market in 2015. Forbes. 11 December 2014. Accessed at www. forbes. com/sites/gilpress/2014/12/11/6-predictions-for-the-125-billion-big-data-analytics-market-in-2015 on 9 December 2015. Google Scholar6. Centre for Evidence-Based Medicine. Study Designs. Accessed at www. cebm. net/study-designs on 8 January 2016. Google Scholar7. Zhao FH, Tiggelaar SM, Hu SY, Zhao N, Hong Y, Niyazi M, et al. A multi-center survey of HPV knowledge and attitudes toward HPV vaccination among women, government officials, and medical personnel in China. Asian Pac J Cancer Prev. 2012;13: 2369-78. PMID: 22901224 CrossrefMedlineGoogle Scholar8. Corley CD, Mihalcea R, Mikler AR, Sanfilippo AP. Chapter 18: Predicting individual affect of health interventions to reduce HPV prevalence. . In: Arabnia HR, Tran QN, eds. Software Tools and Algorithms for Biological Systems. New York: Springer Science+Business Media; 2011: 181. Google Scholar9. De Choudhury M, Gamon M, Counts S, Horvitz E. Predicting Depression via Social Media. Proceedings of the Seventh International Association for the Advancement of Artificial Intelligence Conference on Weblogs and Social Media, Boston, MA, 8–10 July 2013. Palo Alto, CA: Association for the Advancement of Artificial Intelligence Pr; 2013. Google Scholar Author, Article, and Disclosure InformationAffiliations: From University of California, San Francisco, San Francisco, California. Presented in part at the 3rd Annual Cochrane Lecture, Vienna, Austria, 4 October 2015 (available at www. youtube. com/watch? v=RgOgcs95fRk). Disclosures: Disclosures can be viewed at www. acponline. org/authors/icmje/ConflictOfInterestForms. do? msNum=M15-2970. Corresponding Author: Ida Sim, MD, PhD, Division of General Internal Medicine, University of California, San Francisco, 1545 Divisadero Street, Suite 308, San Francisco, CA 94143-0320; e-mail, ida. email protectededu. Author Contributions: Conception and design: I. Sim. Drafting of the article: I. Sim. Critical revision of the article for important intellectual content: I. Sim. Final approval of the article: I. Sim. Administrative, technical, or logistic support: I. Sim. This article was published at www. annals. org on 26 January 2016. 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