J. S. Farrelly1, C. Clemons2, S. Witkins2, W. Hall2, E. Christison-Lagay1,2, D. Ozgediz1,2, R. Cowles1,2, D. Stitelman1,2, M. G. Caty1,2 1Yale University School Of Medicine,Department Of Surgery,New Haven, CT, USA 2Yale New Haven Hospital,New Haven, CT, USA
Introduction:
Healthcare spending in the US remains excessively high. Aside from complicated, large-scale efforts at healthcare cost reduction, there are still relatively simple ways in which individual hospitals can cut unnecessary costs from everyday operations. Inspired by recent publications, our group sought to decrease costs associated with surgical instrument processing at a large, multi-hospital academic center.
Methods:
This was a single-site observational study conducted at a large academic medical center. At the study start, all attending surgeons within the section of Pediatric Surgery agreed to standardize the Pediatric Surgery trays and to eliminate instruments that were deemed unnecessary from each tray. A multi-disciplinary start-up meeting was held, and this meeting included stakeholders from central sterile processing, operating room nursing, scrub technicians, and materials management along with all 5 pediatric surgeons. Each tray was addressed individually. Instruments were eliminated from trays only if there was unanimous agreement among all the surgeons in the group. If no instruments in a given surgical tray were deemed necessary, the entire tray was eliminated from sterile processing rotation. Feedback questionnaires were drafted by the multi-disciplinary team that participated in the start-up meeting. Surgeons were allowed to request for certain instruments to be placed back into the trays at any time, and the questionnaires also allowed for free-hand comments.
Surgical kit preparation time was obtained from the institutional barcode scanning system. The cost per second of sterile processing labor was calculated using regional median salary for sterile processing technicians in the state of Connecticut. Using the Pediatric Surgery section as the model unit, this method was then applied to Pediatric Urology, Neurosurgery, Spine surgery, and Orthopedics.
Results:
The Pediatric Surgery section eliminated an average of 31.5% of instruments from each tray resulting in an overall reduction of 1826 (39.5%) instruments from rotation, 45,856 fewer instruments processed per year, and 9 trays eliminated completely from regular rotation. Processing time for 6 commonly used trays was reduced by an average of 28.7%. The Urology section eliminated 18 trays from regular rotation and 179 (10.1%) instruments in total. Pediatric Orthopedics, Neurosurgery, and Spine sections eliminated 708 (17.1%), 560 (92.7%), and 31 (32.2%) instruments, respectively, resulting in approximately 18804 fewer instruments processed per year. Among all 5 surgical sections, instrument cost avoidance after tray optimization was estimated at $531,929 per year. Negative feedback and requests for instrument replacement were both minimal on feedback questionnaires.
Conclusion:
Surgical tray optimization represents a relatively simple microsystem improvement that could result in significant hospital cost reduction. Though difficult to quantify, other gains from surgical kit optimization include decreased weight per tray, decreased materials cost, and decreased labor required to count, decontaminate, and pack surgical trays.