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 approximately 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 > or =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.
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 approximately 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 > or =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.
Authors: Skorn Ponrartana; Fergus V Coakley; Benjamin M Yeh; Richard S Breiman; Aliya Qayyum; Bonnie N Joe; Liina Poder; Ying Lu; Verna C Gibbs; John P Roberts Journal: Ann Surg Date: 2008-01 Impact factor: 12.969
Authors: Caprice C Greenberg; Scott E Regenbogen; Stuart R Lipsitz; Rafael Diaz-Flores; Atul A Gawande Journal: Ann Surg Date: 2008-08 Impact factor: 12.969
Authors: Caprice C Greenberg; Rafael Diaz-Flores; Stuart R Lipsitz; Scott E Regenbogen; Lynn Mulholland; Francine Mearn; Shilpa Rao; Tamara Toidze; Atul A Gawande Journal: Ann Surg Date: 2008-04 Impact factor: 12.969
Authors: Patrick S Romano; Jeffrey J Geppert; Sheryl Davies; Marlene R Miller; Anne Elixhauser; Kathryn M McDonald Journal: Health Aff (Millwood) Date: 2003 Mar-Apr Impact factor: 6.301
Authors: Natalia N Egorova; Alan Moskowitz; Annetine Gelijns; Alan Weinberg; James Curty; Barbara Rabin-Fastman; Harold Kaplan; Mary Cooper; Dennis Fowler; Jean C Emond; Giampaolo Greco Journal: Ann Surg Date: 2008-01 Impact factor: 12.969
Authors: Atul A Gawande; David M Studdert; E John Orav; Troyen A Brennan; Michael J Zinner Journal: N Engl J Med Date: 2003-01-16 Impact factor: 91.245
Authors: Francisco Chana-Rodríguez; Rubén Pérez Mañanes; José Rojo-Manaute; Luz María Moran-Blanco; Javier Vaquero-Martín Journal: Open Orthop J Date: 2015-07-31
Authors: Alexander W Carter; Rishi Mandavia; Erik Mayer; Joachim Marti; Elias Mossialos; Ara Darzi Journal: BMJ Open Date: 2017-08-18 Impact factor: 2.692