Concise Communication Impact of health insurance status on surgical site infection incidence: A prospective cohort study Brian T. Duggan BSc 1,a , Jan A. Roth MD 1,2,3,a , Marc Dangel MPH 1,2 , Manuel Battegay MD 1,2 and Andreas F. Widmer MD, MS 1,2,4 1 Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland, 2 University of Basel, Basel, Switzerland, 3 Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, Basel, Switzerland and 4 Swissnoso, National Center for Infection Prevention, Bern, Switzerland Abstract Health insurance status may affect the risk for surgical site infection (SSI). A large prospective cohort study in a Swiss tertiary-care hospital did not find evidence of a difference in SSI risk in individuals with basic versus semiprivate or private insurance in a setting with universal health insurance coverage. (Received 29 April 2019; accepted 24 June 2019) Surgical site infections (SSIs) are associated with increased morbid- ity, mortality, and healthcare costs. 1,2 Previous studies have reported associations between patient insurance status and various postsurgical complications. 3–6 However, these analyses were restricted to specific surgeries and patient populations and did not a priori focus their analysis on the insurance status–SSI relationship. Therefore, we aimed to estimate differences in SSI risk across health insurance categories (basic, semiprivate, and private) in a universal health insurance coverage setting. Methods This prospective cohort study was performed at the University Hospital Basel—a tertiary care hospital with >38,000 inpatient cases per year. As part of a national SSI surveillance, we included consecutive patients undergoing cholecystectomy, heart surgery, orthopedic surgery, or colon surgery between January 2014 and December 2018. 7 We excluded repeated surgical interventions dur- ing the same hospital stay. The local ethics committee approved this study as part of a continuing quality improvement program. Infection control practitioners prospectively collected SSI surveillance data in the framework of a national SSI surveillance program. 7 In brief, they screened patients for evidence of SSI, and a board-certified infectious diseases specialist trained in surveillance double-checked all cases. SSIs were classified accord- ing to Centers for Disease Control and Prevention definitions. 8 Standardized postdischarge surveillance was conducted by telephone interview and review of electronic medical records. The surveillance program has been validated, and it undergoes routine on-site checks of data quality. 7 We predefined SSI within 30 days after surgery as our primary outcome and insurance status of the patient at surgery as our main exposure. Basic insurance covers all medical treatments but is lim- ited in the choice of the hospital, surgeon, and comfort (often 4-bed room), whereas the semiprivately or privately insured are hospital- ized in double or single rooms, respectively, and are usually treated by senior physicians or chief physicians, respectively. Private insur- ance allows choice of desired hospital and surgeon. Observation times were analyzed from day of surgery until death, SSI, loss to follow-up, or day 30 after surgery, whichever came first. A priori sample sizes were calculated: α, 0.05; power, 0.80; minimally detectable effect size, hazard ratio (HR), 2; SSI proportion, 0.05; and private insurance proportion, 0.05. We estimated 3,631 patients and 182 SSIs. We compared patient and operation characteristics across insurance categories using the χ 2 test or the Kruskal-Wallis test, as appropriate. We investigated the insurance status–SSI relation- ship using univariable and multivariable Cox regression models with basic health insurance as the baseline category. In multivari- able analysis, we defined age at surgery, sex, and surgery type as a priori confounders. Furthermore, we considered the following variables as potential confounders, based on a causal diagram, expert opinion and previous reports 3–6 : duration of surgery (inci- sion until skin closure, in minutes), emergency surgery, adequate antimicrobial prophylaxis, preoperative American Society of Anesthesiologists score, surgical wound classification, body mass index (BMI), diabetes mellitus type 2, year of surgery and the num- ber of comorbidities according to the International Classification of Diseases, 10th Revision. Potential confounders were included in the final multivariable model if they confounded the main association. The proportional hazard assumption was upheld in all models. We chose not to model potential intracluster correlation because there was no indication of within-patient clustering. We performed all Author for correspondence: Jan A. Roth, MD, Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland. E-mail: janadam.roth@usb.ch. a Authors of equal contribution. Cite this article: Duggan BT, et al. (2019). Impact of health insurance status on surgical site infection incidence: A prospective cohort study. Infection Control & Hospital Epidemiology, https://doi.org/10.1017/ice.2019.195 © 2019 by The Society for Healthcare Epidemiology of America. All rights reserved. Infection Control & Hospital Epidemiology (2019), 1–3 doi:10.1017/ice.2019.195