• Gabriela Batista Rodríguez, Andrea Balla, Santiago Corradetti, Carmen Martinez, Pilar Hernández, Jesús Bollo, and Eduard M Targarona.
• General and Digestive Surgery Unit, Hospital de la Santa Creu i Sant Pau, UAB Universidad Autónoma de Barcelona, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain. batistagaby@gmail.com.
• Int J Colorectal Dis. 2018 Jun 1; 33 (6): 663-681.

Background"Big data" refers to large amount of dataset. Those large databases are useful in many areas, including healthcare. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) and the National Inpatient Sample (NIS) are big databases that were developed in the USA in order to record surgical outcomes. The aim of the present systematic review is to evaluate the type and clinical impact of the information retrieved through NISQP and NIS big database articles focused on laparoscopic colorectal surgery.MethodsA systematic review was conducted using The Meta-Analysis Of Observational Studies in Epidemiology (MOOSE) guidelines. The research was carried out on PubMed database and revealed 350 published papers. Outcomes of articles in which laparoscopic colorectal surgery was the primary aim were analyzed.ResultsFifty-five studies, published between 2007 and February 2017, were included. Articles included were categorized in groups according to the main topic as: outcomes related to surgical technique comparisons, morbidity and perioperatory results, specific disease-related outcomes, sociodemographic disparities, and academic training impact.ConclusionsNSQIP and NIS databases are just the tip of the iceberg for the potential application of Big Data technology and analysis in MIS. Information obtained through big data is useful and could be considered as external validation in those situations where a significant evidence-based medicine exists; also, those databases establish benchmarks to measure the quality of patient care. Data retrieved helps to inform decision-making and improve healthcare delivery.

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