T Pindyck1, K Gupta2, J Strymish3, K M Itani2, M E Carter4, Y Suo4, M T Bessesen5, J Topkoff6, A S Steele7, A E Barón8, A V Gundlapalli4, W Branch-Elliman3. 1. Department of Family Medicine Preventive Medicine Residency Program, University of Colorado Anschutz Medical Campus, Aurora, CO. Electronic address: talia.pindyck@ucdenver.edu. 2. VA Boston Healthcare System, Boston, MA; Boston University School of Medicine, Boston, MA. 3. VA Boston Healthcare System, Boston, MA; Harvard Medical School, Boston, MA. 4. VA Salt Lake City Healthcare System, Salt Lake City, UT; IDEAS Center 2.0, Salt Lake City, UT; University of Utah School of Medicine, Salt Lake City, UT. 5. Eastern Colorado VA Healthcare System, Denver, CO; Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO. 6. Eastern Colorado VA Healthcare System, Denver, CO. 7. U.S. Department of Veteran Affairs, VA St. Louis Healthcare System, St. Louis, MO. 8. Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO.
Abstract
BACKGROUND: Surveillance is an effective strategy for reducing surgical site infections (SSIs); however, current identification methods are resource-intensive. Therefore, we sought to validate an electronic SSI triaging tool for detection of probable infections and identify operational barriers and challenges. METHODS: A retrospective cohort study was conducted among all Veterans Affairs Surgical Quality Improvement Program (VASQIP)-reviewed surgeries at 2 Veterans Affairs medical centers from October 1, 2011-September 30, 2014. During the postoperative period, clinical and administrative variables associated with SSI (relevant microbiology order, antibiotic order, radiology order, and administrative codes) were extracted from the electronic medical record and used to score the probability (high, intermediate, and low) that an SSI occurred. VASQIP manual chart review was used as the gold standard of comparison. RESULTS: VASQIP manual review identified 118 SSIs out of 3,700 surgeries (3.2%). There were 2,041, 1,428, and 231 surgeries that met criteria for low, intermediate, and high probability for SSI. The tool's area under the curve was 0.86 (95% confidence interval, 0.82-0.89). The sensitivity among low-probability surgeries was 92.4%, and the specificity among high-probability surgeries was 95.1%. CONCLUSIONS: The electronic SSI tool has the potential to be used for triaging VASQIP surveillance toward the high-probability surgeries and to avoid manual review of surgeries with low probability of SSI.
BACKGROUND: Surveillance is an effective strategy for reducing surgical site infections (SSIs); however, current identification methods are resource-intensive. Therefore, we sought to validate an electronic SSI triaging tool for detection of probable infections and identify operational barriers and challenges. METHODS: A retrospective cohort study was conducted among all Veterans Affairs Surgical Quality Improvement Program (VASQIP)-reviewed surgeries at 2 Veterans Affairs medical centers from October 1, 2011-September 30, 2014. During the postoperative period, clinical and administrative variables associated with SSI (relevant microbiology order, antibiotic order, radiology order, and administrative codes) were extracted from the electronic medical record and used to score the probability (high, intermediate, and low) that an SSI occurred. VASQIP manual chart review was used as the gold standard of comparison. RESULTS: VASQIP manual review identified 118 SSIs out of 3,700 surgeries (3.2%). There were 2,041, 1,428, and 231 surgeries that met criteria for low, intermediate, and high probability for SSI. The tool's area under the curve was 0.86 (95% confidence interval, 0.82-0.89). The sensitivity among low-probability surgeries was 92.4%, and the specificity among high-probability surgeries was 95.1%. CONCLUSIONS: The electronic SSI tool has the potential to be used for triaging VASQIP surveillance toward the high-probability surgeries and to avoid manual review of surgeries with low probability of SSI.
Authors: Westyn Branch-Elliman; Steven D Pizer; Elise A Dasinger; Howard S Gold; Hassen Abdulkerim; Amy K Rosen; Martin P Charns; Mary T Hawn; Kamal M F Itani; Hillary J Mull Journal: Antimicrob Resist Infect Control Date: 2019-03-06 Impact factor: 4.887
Authors: Hillary J Mull; Kelly L Stolzmann; Marlena H Shin; Emily Kalver; Marin L Schweizer; Westyn Branch-Elliman Journal: JAMA Netw Open Date: 2020-09-01