surgical site infection surveillance quality 1173
assessment bias (correct interpretation of the study outcome) need to be considered. Although the best means of validating a SSI surveillancemodule is still unknown, methods of calculating sensitivity, specificity, positive predictive values, and negative predictive values (with or without structured interviews for structure and process validation) have been widely acknowledged.14–18 To assess the quality of the Swissnoso SSI surveillance program, structure and process for SSI surveillance were reviewed at all participating hospitals using audits and structured interviews with all persons involved in surveillance. SSI outcome data were validated by reviewing a random sample from each hospital of 10 patient records (with or without infection) and 5 additional randomly selected records of patients with infection.
materials and methods SSI Surveillance Method
In Switzerland, the first multicenter surveillance system for SSI was developed in the mid-1990s. The system was developed according to the principles of the US National Nosocomial Infections Surveillance (NNIS) system, currently known as the National Healthcare Safety Network (NHSN)19–23 and is describedindetailinaprevious publication.8 Full documentation of the surveillance methodology is available for participating hospitals on the Swissnoso website.14 Since 2014, starting with the 2011 data, when participation in
the programbecamemandatory, the Swiss National Association for the Development of Quality in Hospitals and Clinics (ANQ) has openly publishing the surveillance results by hospital, including their names, NNIS/NHSN-adjusted SSI rates, and quality of surveillance as rated during onsite visits.24
Validation of Participating Hospitals
Since October 1, 2012, we validated the structure and process of SSI surveillance as well as SSI outcome data during dedi- cated validation visits for all hospitals required to participate in the program nationwide using a standardized data collection form. Hospitals were visited on site by 1 of 3 specifically trained investigators (2 registered nurses and 1 physician) with profound knowledge of the Swissnoso SSI surveillance methodology.
Surveillance Structure and Process Assessment
On-site structured interviews and observations of the surveillance process were performed with all persons involved in SSI surveil- lance, regardless of education, background, or the percentage of full-time equivalents ascribed for surveillance. A weighted score was attributed according to a structured that
was developed based on existing literature and expert consensus. The questionnaire covered training of persons performing the surveillance, work environment (including understaffing), potential conflicts of interest, data sources for patient selection,
completeness of inclusion, completeness of required medical information (for diagnosis of SSI, during hospitalization and after discharge), quality of postdischarge surveillance, presence and type of medical supervision, and losses to follow-up (ie, attrition bias) (Table 1 and Supplemental Tables S1, S2, and S3). When different teams performed SSI surveillance at different sites or units of a hospital (eg, pediatric surgery, abdominal surgery, or cardiac surgery), each team was assessed separately and a score was attributed to each team.
SSI Outcome Validation
Patient records of electronic case report forms (eCRFs) submitted between January 1, 2009, and October 31, 2015, were eligible for review. A random sample of 10 patient records was drawn from all cases and all types of surgeries that were submitted by each respective hospital, irrespective of the presence or absence of SSI (Dataset A). In addition, for each hospital, 5 records of patients with SSI were randomly selected from all cases and all types of surgeries with originally reported infections that were submitted by therespectivehospital(Dataset B). Patient records were reviewed by the validators with assis-
tance from on-site participants and were checked against eCRFs and paper CRFs. The outcome determination by the independent investigator was regarded as the gold standard. All cases with infection, all misclassifications (false positive and false negative), and all questionable cases needing further clarification were reviewed and resolved by consensus with 1 or 2 additional senior investigators (M.C.E. and N.T.).
Statistical Analysis
Descriptivestatisticswereusedtooutlinethesurveillancestruc- turesand processesofparticipating hospitals. Differences between groups were assessed in univariate analyses using the χ2, Fisher’s exact test, Wilcoxon rank-sum test, or Student t test, as appropriate. Multivariate linear regression analysis was used to evaluate associations between surveillance parameters (ie, lan- guage region, hospital size, hospital status [private vs public], number of hospital beds, full-time equivalents dedicated to sur- veillance, duration of participation in surveillance) and validation scores for the overall score and scores within individual domains. Multivariate analyses assessing the association between surveil- lance structure and process parameters (ie, language region, hospital size, hospital status [private vs public], number of pro- cedures included per year, full-time equivalents dedicated to surveillance, understaffing, and overall validation score and scores of individual domains, respectively), and misclassification of infections status and types of infections, respectively, were performed using generalized estimating equations (GEE; logit link models with binomial distribution of the dependent variable and exchangeable within-group correlation structure). This method accounted for cluster effects on the hospital level, as several cases per hospital that shared the same surveillance structure and process parameters were assessed.
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132 |
Page 133 |
Page 134 |
Page 135 |
Page 136 |
Page 137 |
Page 138 |
Page 139 |
Page 140 |
Page 141 |
Page 142 |
Page 143 |
Page 144
