Open AccessBig data, big contributions: outcomes research in thoracic surgery
Author(s) -
Benjamin J. Resio,
Andrew P. Dhanasopon,
Justin D. Blasberg
Publication year - 2019
Publication title -
journal of thoracic disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.682
H-Index - 60
eISSN - 2077-6624
pISSN - 2072-1439
DOI - 10.21037/jtd.2019.01.04
Subject(s) - medicine , big data , cardiothoracic surgery , data science , general surgery , surgery , data mining , computer science
In recent years, analysis of registry data has defined clinically significant practice patterns and treatment strategies that optimize cancer care for thoracic surgery patients. These higher-order outcome studies rely on large patient cohorts that minimize the risk of selection bias and allow for a powered analysis that is not achievable with single- or multi-institutional data. This review uses recent study examples to highlight important contributions to our knowledge of thoracic surgery and describes how outcomes research using large data can address high impact clinical questions.