Franklin Dexter1, Johannes Ledolter2, Richard H Epstein3, Randy W Loftus4. 1. Department of Anesthesia, Division of Management Consulting, University of Iowa, Iowa City, IA. Electronic address: Franklin-Dexter@UIowa.edu. 2. Department of Management Sciences, University of Iowa, Iowa City, IA. 3. Department of Anesthesiology, Perioperative Medicine, & Pain Management, University of Miami, Miami, FL. 4. Department of Anesthesia, Division of Management Consulting, University of Iowa, Iowa City, IA.
Abstract
BACKGROUND: We review the impact of the consequences of operating room (OR) management decision making on power analyses for observational studies of surgical site infections (SSIs) among patients receiving care in ORs with interventions versus without interventions involving physical changes to ORs. Examples include ventilation systems, bactericidal lighting, and physical alterations to ORs. METHODS: We performed a narrative review of operating room management and surgical site infection articles. We used 10-years of operating room data to estimate parameters for use in statistical power analyses. RESULTS: Creating pivot tables or monthly control charts of SSI per case by OR and comparing among ORs with or without intervention is not recommended. This approach has low power to detect a difference in SSI rates among the ORs with or without the intervention. The reason is that appropriate OR case scheduling decision making causes risk factors for SSI to differ among ORs, even when stratifying by surgical specialty. Such risk factors include case duration, urgency, and American Society of Anesthesiologists' Physical Status. Instead, analyze SSI controlling for the OR, where the patient had surgery, and matching patients using these variables is preferable. With α = 0.05, 600 cases per OR, 5 intervention ORs, and 5 or 1 control patients for each intervention patient, reasonable power (≅94% or 78%, respectively) can be achieved to detect reductions (3.6% to 2.4%) in the incidence of SSI between ORs with or without the intervention. CONCLUSIONS: By using this matched cohort design, the effect of the purchase and installation of capital equipment in ORs on SSI can be evaluated meaningfully.
BACKGROUND: We review the impact of the consequences of operating room (OR) management decision making on power analyses for observational studies of surgical site infections (SSIs) among patients receiving care in ORs with interventions versus without interventions involving physical changes to ORs. Examples include ventilation systems, bactericidal lighting, and physical alterations to ORs. METHODS: We performed a narrative review of operating room management and surgical site infection articles. We used 10-years of operating room data to estimate parameters for use in statistical power analyses. RESULTS: Creating pivot tables or monthly control charts of SSI per case by OR and comparing among ORs with or without intervention is not recommended. This approach has low power to detect a difference in SSI rates among the ORs with or without the intervention. The reason is that appropriate OR case scheduling decision making causes risk factors for SSI to differ among ORs, even when stratifying by surgical specialty. Such risk factors include case duration, urgency, and American Society of Anesthesiologists' Physical Status. Instead, analyze SSI controlling for the OR, where the patient had surgery, and matching patients using these variables is preferable. With α = 0.05, 600 cases per OR, 5 intervention ORs, and 5 or 1 control patients for each intervention patient, reasonable power (≅94% or 78%, respectively) can be achieved to detect reductions (3.6% to 2.4%) in the incidence of SSI between ORs with or without the intervention. CONCLUSIONS: By using this matched cohort design, the effect of the purchase and installation of capital equipment in ORs on SSI can be evaluated meaningfully.