Literature DB >> 29672402

Postoperative Surgical Site Infections: Understanding the Discordance Between Surveillance Systems.

Mariam N Ali-Mucheru1,2, Maria T Seville3, Vickie Miller4, Priya Sampathkumar5, David A Etzioni1,2.   

Abstract

OBJECTIVE: To characterize agreement in the ascertainment of surgical site infections (SSIs) between the National Surgical Quality Improvement Program (NSQIP), National Healthcare Safety Network (NHSN), and administrative data.
BACKGROUND: The NSQIP, NHSN, and administrative data are the primary systems used to monitor and report SSIs for the purpose of quality control and benchmarking of hospitals and surgeons. These systems have different methods for identifying SSIs.
METHODS: We queried the NHSN, NSQIP, and administrative data systems for patients who had an operation at 1 of 4 hospitals within a single health system between January 2013 and September 2015. The detection of an SSI during a postoperative hospitalization was the outcome of analysis. Any SSI detected by one (or more) of these systems was analyzed by 2 reviewers to determine the presence of discrete elements of documentation constituting evidence of SSI. Concordance between the 3 systems (NHSN, NSQIP, and administrative data) was analyzed using Cohen's kappa.
RESULTS: After application of appropriate exclusion criteria, a cohort of 9447 inpatient operations was analyzed. In total, 130 SSIs were detected by 1 or more of the 3 systems, with reported SSI rates of 0.5% (NHSN), 0.7% (administrative data), and 1.0% (NSQIP). Of these 130 SSIs, only 17 SSIs were reported by all 3 systems. The concordance between these 3 systems was moderate (kappa values NSQIP-NHSN = 0.50 [0.40-0.60], administrative-NHSN = 0.36 [0.24-0.47], and administrative-NSQIP = 0.47 [0.38-0.57]). Chart review found that reasons for discordance were related to issues of different criteria as well as inaccuracies.
CONCLUSION: There is significant discordance in the determination of SSIs reported by the NHSN, NSQIP, and administrative data. The differences and limitations of each of these systems have to be recognized, especially when using these data for quality reports and pay for performance.

Entities:  

Mesh:

Year:  2020        PMID: 29672402     DOI: 10.1097/SLA.0000000000002780

Source DB:  PubMed          Journal:  Ann Surg        ISSN: 0003-4932            Impact factor:   12.969


  3 in total

1.  Surgical site infection metrics: Dissecting the differences between the National Health and Safety Network and the National Surgical Quality Improvement Program.

Authors:  Alaia M M Christensen; Karen Dowler; Shira Doron
Journal:  Antimicrob Steward Healthc Epidemiol       Date:  2021-07-26

2.  Novel Method to Flag Cardiac Implantable Device Infections by Integrating Text Mining With Structured Data in the Veterans Health Administration's Electronic Medical Record.

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

3.  Rates and causative pathogens of surgical site infections attributed to liver transplant procedures and other hepatic, biliary, or pancreatic procedures, 2015-2018.

Authors:  Nora Chea; Mathew R P Sapiano; Liang Zhou; Lauren Epstein; Alice Guh; Jonathan R Edwards; Katherine Allen-Bridson; Victoria Russo; Jennifer Watkins; Stephanie M Pouch; Shelley S Magill
Journal:  Transpl Infect Dis       Date:  2021-03-23
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.