Big Data in Colorectal Surgery

Stefan D. Holubar, MD, MS, FACS, FASCRS

Early in the 21st century, “big data” which refers to large databases (millions of records) has become ubiquitous in both modern life and in medicine and surgery. This convergence is typified by the concept of the “internet of things,” where medical equipment such as wireless bedside monitors can record and upload a tremendous amount of data, and “the quantified self” with health trackers which add an ever increasing number of variables, such as activity, weight, pulse, blood glucose, sleep time, also uploaded for offline analysis. This converging phenomenon will ultimately result in implantable wireless chips. Having so much data will require new types of computing power, such as Big Blue by IBM Inc. and artificial intelligence, and a cadre of specialized data analysts and human monitors. Only then will we be able to have real-time predictive analytics and early-warning systems.

However, currently, and within our field, often it is difficult to access these large datasets and understand the nuances of one database to another. Therefore, we have chosen colon and rectal surgeons who have expertise with particular databases to present various common databases. As guest editor, my request was simple: for each group of authors to review the history and overall structure, including strengths and weaknesses, of their chosen database in the first half of their articles, and in the second half to review select articles from within the clinical colon and rectal surgery research.

I extend my gratitude to all the authors, who not only wrote excellent articles but also took the time to include excellent tables and figures to help readers understand a somewhat academic and technical topic. I am indebted for all their hard work on the readers' behalf.

Our issue begins with a preface by Dr. David Etzoni; his preface gives the following articles secular context to allow readers to understand how these databases fit in to the global structure of medical policy in the Unites States. This issue is divided into four sections. Section 1 focuses on locoregional databases and registries, and Drs. Amy Lightner and Robert Cima from Mayo Clinic Rochester reviews the Rochester Epidemiology Project (REP), which is the world's largest population-based epidemiologic passive records linkage system of its kind. Next, the Michigan State Quality Collaborative (MSQC) is reviewed by Drs. Vahagn Nikolian and Scott Regenbogen from the University of Michigan. The MSQC is a state-based collaborative model, and relatively unique in that it is funded by Blue Cross/Blue Shield as they recognize the value of quality improvement. Next is an introduction to Surgical Care and Outcomes Assessment Program (SCOAP), which also is a model of state-based registry, by Drs. Vlad Simianu and Anjali S. Kumar. We appreciate their unique idea to include interviews with the leadership of SCOAP.

Section 2 focuses on national databases, and the first article by Drs. Katherine Kelly and Liana Tsikitis introduces to the National Inpatient Sample (NIS), an immense administrative database which is likely the de facto gold standard for studying a variety of benign and malignant, common and rare, as well as medical and surgical conditions over time, including costs. The next big national database, but one that focuses solely on surgery, reviewed by Dr. Samuel Eisenstein et al, is the National Surgical Quality Improvement Project (NSQIP). NSQIP is a large clinical database and quality improvement platform. Finally, occupying a niche in the large national administrative database space, Truven Health MarketScan databases, as shown in the review by Dr. Audrey S. Kulaylat et al, are obtained from insurance databases and are particularly useful for examining pharmaceutical topics and their costs.

Section 3 reviews cancer-specific databases. Drs. Meghan C. Daly and Ian Paquette provide a concise review on the use of the Surveillance, Epidemiology, and End Results (SEER) and SEER-Medicare. This large administrative database collects data on 30% of Americans with cancer, making a wonderful, relatively easily accessible resource.

We are also grateful to Drs. Katherine Kelly and Liana Tsikitis for their second contribution to this issue on Big Data, in which they review the National Cancer Database (NCBD). This is another American College of Surgeons Commission on Cancer's (CoC) large database, but one that has myriad surgical oncology, including colorectal, cancer-specific variables.

Finally, the last section highlights two relatively new, innovative databases. Drs. Andrew Currie and Mattias Soop from the United Kingdom present us the ERAS Society's database (which Dr. Soop designed in Stockholm Sweden) as well as their web-based ERAS interactive audit system (EIAS). We are grateful to the ERAS Society for sharing screenshots of their system. Finally, regardless of current politics, it is obvious that the Electronic Health Record (EHR) is here to stay, and Drs. Jacob Carlson and Jonathan Laryea provide a concise review of a complicated topic—how to get data out of EHR's, especially in the form of registries.

This topic of “Big Data in Colorectal Surgery” has been on my mind for several years; thus, I am especially thankful to Dr. Beck and Dr. Scott Steele for giving me the opportunity to guest edit this special issue of Clinics in Colon and Rectal Surgery.