An effort to improve the accuracy of documented surgical wound classifications

Am J Surg. 2018 Mar;215(3):515-517. doi: 10.1016/j.amjsurg.2017.11.029. Epub 2017 Dec 2.

Abstract

Background: Discordance between circulating nurse- and surgeon diagnosis-based wound classifications may lead to erroneous risk-adjusted rates of surgical site infections with effects on inter-hospital rating, reimbursement, and public perceptions regarding quality of care.

Methods: After an initial two-month audit, we placed a wound class reference algorithm in each operating room and educated staff. An audit was repeated for a two-month period after this intervention. Statistical analysis of the whole and subgroup was performed.

Results: Pre-intervention, the wound classifications for 70 of 300 cases were discordant. In the post-intervention group, 79 of 483 cases were discordant (p = 0.016). Subgroup analysis of colectomy and appendectomy cases demonstrated dramatically improved concordance. For colectomies, discordance dropped from 84.6% to 15% post-intervention (p = <0.001). Appendectomy discordance went from 80% of cases to 30.4% post-intervention (p = 0.001). Wound class discordance increased for the cholecystectomy subgroup (20.4%-37%) but this was not statistically significant (p = 0.066).

Conclusions: As we trend towards a pay-for-performance model, health care systems should review their internal controls on documenting surgical wound classes.

Keywords: Documentation; Quality improvement; Surgical site infection; Surgical wound classification; Wound classification.

MeSH terms

  • Algorithms*
  • Appendectomy
  • Cholecystectomy
  • Colectomy
  • Documentation / standards*
  • Documentation / statistics & numerical data
  • Humans
  • Medical Audit
  • Michigan
  • Quality Improvement / statistics & numerical data*
  • Risk Adjustment
  • Surgical Wound / classification*
  • Surgical Wound / diagnosis
  • Surgical Wound Infection / diagnosis
  • Surgical Wound Infection / epidemiology