Surgery
Volume 145, Issue 5 , Pages 527-535, May 2009

Prevention of retained surgical sponges: A decision-analytic model predicting relative cost-effectiveness

  • Scott E. Regenbogen, MD, MPH

      Affiliations

    • Department of Health Policy and Management, Harvard School of Public Health, Boston, MA
    • Department of Surgery, Massachusetts General Hospital, Boston, MA
    • Corresponding Author InformationReprint requests: Scott E. Regenbogen, MD, MPH, Massachusetts General Hospital, 55 Fruit Street, GRB-425, Boston, MA 02114.
  • ,
  • Caprice C. Greenberg, MD, MPH

      Affiliations

    • Center for Surgery and Public Health, Brigham and Women's Hospital, Boston, MA
  • ,
  • Stephen C. Resch, PhD, MPH

      Affiliations

    • Abt Associates, Cambridge, MA
  • ,
  • Anantha Kollengode, PhD, MBA

      Affiliations

    • Office of Quality Management, Mayo Clinic, Rochester, MN
  • ,
  • Robert R. Cima, MD, MA, FACS

      Affiliations

    • Department of Surgery, Mayo Clinic, Rochester, MN
  • ,
  • Michael J. Zinner, MD, FACS

      Affiliations

    • Center for Surgery and Public Health, Brigham and Women's Hospital, Boston, MA
  • ,
  • Atul A. Gawande, MD, MPH, FACS

      Affiliations

    • Department of Health Policy and Management, Harvard School of Public Health, Boston, MA
    • Center for Surgery and Public Health, Brigham and Women's Hospital, Boston, MA

Accepted 28 January 2009. published online 23 March 2009.

Background

New technologies are available to reduce or prevent retained surgical sponges (RSS), but their relative cost effectiveness are unknown. We developed an empirically calibrated decision-analytic model comparing standard counting against alternative strategies: universal or selective x-ray, bar-coded sponges (BCS), and radiofrequency-tagged (RF) sponges.

Methods

Key model parameters were obtained from field observations during a randomized-controlled BCS trial (n = 298), an observational study of RSS (n = 191,168), and clinical experience with BCS (n ∼ 60,000). Because no comparable data exist for RF, we modeled its performance under 2 alternative assumptions. Only incremental sponge-tracking costs, excluding those common to all strategies, were considered. Main outcomes were RSS incidence and cost-effectiveness ratios for each strategy, from the institutional decision maker's perspective.

Results

Standard counting detects 82% of RSS. Bar coding prevents ≥97.5% for an additional $95,000 per RSS averted. If RF were as effective as bar coding, it would cost $720,000 per additional RSS averted (versus standard counting). Universal and selective x-rays for high-risk operations are more costly, but less effective than BCS—$1.1 to 1.4 million per RSS event prevented. In sensitivity analyses, results were robust over the plausible range of effectiveness assumptions, but sensitive to cost.

Conclusion

Using currently available data, this analysis provides a useful model for comparing the relative cost effectiveness of existing sponge-tracking strategies. Selecting the best method for an institution depends on its priorities: ease of use, cost reduction, or ensuring RSS are truly “never events.” Given medical and liability costs of >$200,000 per incident, novel technologies can substantially reduce the incidence of RSS at an acceptable cost.

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 S.E.R. was supported by Kirschstein National Research Service Award T32-HS000020 from the Agency for Healthcare Research and Quality. Drs Greenberg and Gawande have received research grant support from SurgiCount Medical, Temecula, CA. The funding agencies were not involved in the conduct, analysis, or composition of this study, and were not given the opportunity to approve or edit the manuscript before submission.

PII: S0039-6060(09)00073-7

doi:10.1016/j.surg.2009.01.011

Surgery
Volume 145, Issue 5 , Pages 527-535, May 2009