William C Rupp

Mayo Foundation for Medical Education and Research, Rochester, MI, United States

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Publications (2)12.4 Total impact

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    ABSTRACT: Variability in flow of patients through operating rooms has a dramatic impact on a hospital's performance and finances. Natural variation (uncontrollable) and artificial variation (controllable) differ and require different resources and management. The aim of this study was to use variability methodology for a hospital's surgical services to improve operational performance. Over a 3-month period, all operations at a referral center were classified as either scheduled (artificial variation) or unscheduled (natural variation). Data regarding patient flow were collected for all cases. From these data, mathematical models determined explicit resources to be allocated for scheduled and unscheduled cases, with isolation of the 2 flow streams. Services were allocated block time based on 80% prime time use, and scheduled cases were capped at 5:00 PM. Guidelines for operating room access were implemented to smooth the daily schedule and minimize artificial variation on the day of surgery. After implementation of this redesign, 12 months of data were compared with the previous 12-month period. Metrics analyzed included prime time use, overtime minutes, access for urgent or emergent cases, the number of room changes to the elective schedule on the day of surgery, and variation of daily schedules. Surgical volume and surgical minutes increased by 4% and 5%, respectively. Prime time use increased by 5%. Overtime staffing decreased by 27%. Day-to-day variability decreased by 20%. The number of elective schedule same day changes decreased by 70%. Staff turnover rate decreased by 41%. Net operating income and margin improved by 38% and 28%, respectively. Variability management results in improvement in operating room operational and financial performance. This optimization may have a significant impact on a hospital's ability to adapt to health care reform.
    Journal of the American College of Surgeons 04/2013; 216(4):559-68. · 4.50 Impact Factor
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    ABSTRACT: It is estimated that healthcare associated infections (HAI) account for 1.7 million infections and 99,000 associated deaths each year, with annual direct medical costs of up to $45 billion. Surgical Site Infections (SSI) account for 17% of HAIs, an estimated annual cost of $3.5 to 10 billion for our country alone. This project was designed to pursue elimination of SSIs and document results. Starting in 2009 a program to eliminate SSIs was undertaken at a nationally recognized academic health center. Interventions already outlined by CMS and IHI were utilized, along with additional interventions based on literature showing relationships with SSI reduction and best practices. Rapid deployment of multiple interventions (SSI Bundle) was undertaken. Tactics included standardized order sets, a centralized preoperative evaluation (POE) clinic, high compliance with intraoperative interventions, and widespread monthly reporting of compliance and results. Data from 2008 to 2010 were collected and analyzed. Between May 1, 2008 and June 30, 2010, all patients with Class I and Class II wounds were tracked for SSIs. Baseline data (May-June 2008) was obtained showing a Class I surgical site infection rate of 1.78%, Class II of 2.82% (total surgical volume: 4160 cases). As of the second quarter 2010, those rates have dropped to 0.51% and 1.44%, respectively (P < 0.001 and P = 0.013; total surgical cases: 2826). This represents a 57% decrease in the SSI rate with an estimated institution specific cost savings of nearly $1 million during the study period. Committed leadership, aggressive assurance of high compliance with multiple known interventions (SSI Bundle), transparency to achieve high levels of staff engagement, and centralization of critical surgical activities result in significant declines in SSIs with resulting substantial cost savings.
    Annals of surgery 09/2011; 254(3):430-6; discussion 436-7. · 7.90 Impact Factor