Large Surgical Databases with Direct Data Abstraction: VASQIP and ACS-NSQIP

Direct data abstraction from a patient's chart by experienced medical professional data abstractors has been the historical gold standard for quality and accuracy in clinical medical research. The limiting challenge to population-wide studies for quality and public health purposes is the high personnel costs associated with very large-scale efforts of this type. Two historically related programs that are at least partially able to successfully circumvent this problem and provide high-quality data relating to surgical procedures and the early postoperative period are reviewed in this article. Both utilize similar data abstraction efforts by specially trained and qualified medical abstractors of a sample subset of the total procedures performed at participating hospitals.The Veterans Affairs Surgical Quality Improvement Program (VASQIP), detailed by Nicholas J. Giori, MD, PhD, in the first section of this article, makes use of trained abstractors and has undergone recent additions and updates, including the development of an associated total hip registry for the VA system. The data elements and data integrity provided by both of these programs establish important benchmarks for other "big data" efforts, which often attempt to use alternative less-expensive methods of data collection in order to achieve more widespread or even nationwide data collection.In the second section, Elizabeth B. Habermann, PhD, MPH, provides a detailed review of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP), the data elements collected, and examples of the range of quality improvement and outcomes studies in orthopaedic surgery that it has made possible, along with information on data that have not been collected and the resulting limitations. The ACS NSQIP was actually modeled after the very similar earlier effort started by the United States Department of Veterans Affairs (VA).