Over 15 million surgical procedures are performed in ambulatory surgical centers (ASCs) in the U.S. annually. ASC procedures account for more than 40% of all same-day surgeries in the U.S.;however, virtually no surveillance is currently performed to identify infections associated with ASC procedures. There are very little data on the incidence of surgical site infection (SSI) and infection with antibiotic resistant organisms, such as Clostridium difficile, after ASC procedures at the national level or from individual facilities. In a recent CDC survey deficiencies in recommended practices were found in 85% of surveyed ASCs, most of which involved infection control. There is a need for research on infections associated with ASCs. Infection surveillance after ambulatory surgeries requires integration of information across healthcare providers and facilities. With the proliferation of ASCs it is essential to develop reproducible methods to accurately identify infections following surgical procedures commonly performed in ASCs to determine the clinical and economic impact of infection, and to develop models to predict the risk of infection in individual patients. To accomplish these goals we propose to use geographically diverse longitudinal medical and pharmacy claims data from the largest commercially insured population in the U.S. to: 1) determine the incidence of C. difficile infection and SSIs, including infections caused by methicillin-resistant Staphylococcus aureus, after breast conserving surgery, hernia repair, and cholecystectomy, three common procedures performed in ASCs, 2) identify facility- and patient-level factors associated with increased risk of SSI and C. difficile infection, 3) develop and validate risk prediction models using the patient-level risk factors, taking into account the specific types of surgical procedures, 4) determine clinical outcomes and attributable costs of SSI and C. difficile infection. The methods we develop to identify infections can be used as the basis for national surveillance of ASC-associated infections. This study will provide significant new information to enhance patient safety and improve outcomes for patients undergoing common surgical procedures in ambulatory settings.
We propose to determine rates and risk factors of surgical site and Clostridium difficile infections after surgical procedures performed in ambulatory settings. We will develop an algorithm to predict infections that can be used by providers prior to surgery to determine individual patients'risk of infection. This study will provide important new information that can be used to improve outcomes after common surgical procedures.
|Jafarzadeh, S Reza; Warren, David K; Nickel, Katelin B et al. (2016) Bayesian estimation of the accuracy of ICD-9-CM- and CPT-4-based algorithms to identify cholecystectomy procedures in administrative data without a reference standard. Pharmacoepidemiol Drug Saf 25:263-8|
|Olsen, Margaret A; Nickel, Katelin B; Margenthaler, Julie A et al. (2015) Increased Risk of Surgical Site Infection Among Breast-Conserving Surgery Re-excisions. Ann Surg Oncol 22:2003-9|
|Olsen, Margaret A; Nickel, Katelin B; Wallace, Anna E et al. (2015) Stratification of surgical site infection by operative factors and comparison of infection rates after hernia repair. Infect Control Hosp Epidemiol 36:329-35|
|Warren, David K; Nickel, Katelin B; Wallace, Anna E et al. (2014) Can additional information be obtained from claims data to support surgical site infection diagnosis codes? Infect Control Hosp Epidemiol 35 Suppl 3:S124-32|