Use of the National Surgical Quality Initiative Program in Vascular Surgery Research Journal Articles uri icon

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abstract

  • BACKGROUND: The National Surgical Quality Improvement Program (NSQIP) is a prospectively collected database that collects 30-day patient outcome data, and analyzes these data for risk adjusted comparisons. The purpose of this review is to determine how this database is used in vascular surgery literature. METHODS: With the assistance of a librarian, a comprehensive search string was developed to survey the NSQIP vascular surgery literature in PubMed, EMBASE, MEDLINE, and CINAHL. Two reviewers independently reviewed the articles. To be included in the study articles had to relate to one of the domains of vascular surgery and utilize the NSQIP database. RESULTS: One hundred fifty-six articles were included in this review. All studies were retrospective and the most common study type was retrospective cohort studies (65.4%). Although 2016 was the year with the most published articles (22.4%), 2014 and 2015 stand out as going against the upward trend of number of published articles in respect to year. The most prominent aims of the studies were to find preoperative predictors of adverse outcomes (50.6%). There were a minority of studies investigating quality improvement following implementation of the NSQIP (5.1%) or validation and examination of risk predicting tools (3.8%). Of the surgical domains investigated by studies, the use of aneurysm repair data was most common (33.3%) followed by lower extremity revascularization or amputation (28.2%). Within these surgical domains, majority of studies were interested specifically in open cases (51.9%). Although there was some range in outcomes investigated, mortality and morbidity were one of the primary outcomes in majority of the studies (mortality 65.0%, morbidity 57.3%). CONCLUSIONS: Since its inception, the NSQIP has grown in both hospital implementation and vascular surgery literature. Although a variety of literature exists that uses said NSQIP data to predict and compare adverse events, not much literature exists surrounding the translation of implementing these findings into the hospital setting. Additionally, despite the size of the database, many existing studies investigate similar aims and outcomes to each other.

authors

  • Wong, Cynthia
  • Augustine, Haley
  • Saleh, Asem
  • Naji, Faysal
  • Hu, Jiayi
  • Rapanos, Theodore

publication date

  • November 2019