1 2 3 4 6 7 8 9 10 11 13 14 15 16 17 The objective of this study is to obtain more precise estimates of nosocomial infection risks associated with laparoscopic and open approaches for cholecystectomy, appendectomy, and hysterectomy. We hypothesize that laparoscopic surgery will reduce the risk of nosocomial infections for each of these surgical modalities. To test these hypotheses we performed a retrospective analysis of more than 11,000 admissions, each with one of the procedures of interest, from 22 hospitals that have implemented a nosocomial infection monitoring system that can detect nosocomial infections up to 30 days post discharge. Methods The Nosocomial Infection Marker (NIM) The Nosocomial Infection Marker (NIM, patent pending, Cardinal Health) monitors and tracks nosocomial infection rates for hospitals and communities. Cardinal Health extracts data from client facilities on an ongoing basis using a secure, Health Insurance Portability and Accoutability Act- (HIPAA) compliant method. Data are cleaned and mapped in real time as they arrive at the Cardinal Health data center by proprietary software systems. Rare exceptions that are not electronically modeled are modeled by technical and clinical experts, processed and loaded. The new models are then used by the systems to process like data in the future. 18 18 18 19 19 Data 1 Table 1 DRGs included in the analysis  % admissions  NIM rate % laparoscopy Simple presentations (complexity = 0) 166 Appendectomy W/O complicated Principal Diag W Cc 3.16 2.71 67.21 167 Appendectomy W/O Complicated Principal Diag W/O Cc 14.53 1.12 71.66 195 Cholecystectomy W C.D.E. W Cc 0.52 14.75 16.39 196 Cholecystectomy W C.D.E. W/O Cc 0.21 0.00 25.00 197 Cholecystectomy Except By Laparoscope W/O C.D.E. W Cc 3.64 9.43 11.79 198 Cholecystectomy Except By Laparoscope W/O C.D.E. W/O Cc 2.01 2.56 40.60 358 Uterine & Adnexa Proc For Non-Malignancy W Cc 11.43 3.30 36.53 359 Uterine & Adnexa Proc For Non-Malignancy W/O Cc 25.72 1.20 47.92 493 Laparoscopic Cholecystectomy W/O C.D.E. W Cc 14.86 4.15 100 494 Laparoscopic Cholecystectomy W/O C.D.E. W/O Cc 11.42 0.68 100 Complex presentations (complexity = 1) 164 Appendectomy W Complicated Principal Diag W Cc 2.96 9.28 47.25 165 Appendectomy W Complicated Principal Diag W/O Cc 3.39 3.04 54.43 354 Uterine, Adnexa Proc For Non-Ovarian/Adnexal Malig W Cc 2.24 8.05 5.36 355 Uterine, Adnexa Proc For Non-Ovarian/Adnexal Malig W/O Cc 2.04 2.10 19.33 357 Uterine & Adnexa Proc For Ovarian Or Adnexal Malignancy 1.89 10.00 5.00 Diag = Diagnosis; W/O = Without; C.D.E. = Common Duct Exploration; Proc = Procedure; Malig = Malignancy; W = With; Cc = Complication and comorbidities 1 Statistical Analysis Single and multiple logistic regression analyses were performed to quantify the associations between NIM rate and procedure, approach, patient age, gender, insurance type, complexity of presentation, ED admission status, and hospital CMI. The first model pooled all three procedures and included binary variables to adjust for the influence of each procedure on the acquisition of NIMs. Then separate models for cholecystectomy, appendectomy, and hysterectomy were constructed. Finally models were constructed for procedure and approach for wound, urinary tract, bloodstream, and respiratory tract NIMs. Results Hysterectomies comprised 43.3% of all procedures, cholecystectomies 32.7%, and appendectomies 24.0%. The percentage of cholecystectomies, appendectomies, and hysterectomies that were laparoscopic was 84.7%, 65.6%, and 39.5%, respectively. Unsurprisingly, fewer than one-quarter of all patients were male. Approximately 19.3% of admissions were covered by Medicare, 7% by Medicaid, 58.8% by private health insurance, and the remaining 14.8% by other types of insurance. 2 Table 2 Nosocomial infection rates by approach and procedure  Admissions Admissions with ≥1 NIM Rate (%)  11,662 337 2.89 Approach   Laparoscopic 7061 149 2.11   Open 4601 188 4.09 Procedure   Cholecystectomy 3808 136 3.57   Appendectomy 2803 73 2.60   Hysterectomy 5051 128 2.53 Approach by procedure   Laparoscopic     Cholecystectomy 3226 84 2.60     Appendectomy 1840 42 2.28     Hysterectomy 1995 23 1.15   Open     Cholecystectomy 582 52 8.93     Appendectomy 963 31 3.21     Hysterectomy 3056 105 3.44 There were 399 NIMs identified in 337 admissions. Of all NIMs identified, 118 (30%) were from surgical wounds, 122 (31%) were from the urinary tract, 37 (9%) were from the blood, 29 (7%) were from the respiratory tract, and 93 (23%) were from other sources. At least one post-discharge NIM was identified in 136 admissions, accounting for 40% of all admissions with a NIM. Of the 147 post-discharge NIMs, 39% were from surgical wounds, 31% were from the urinary tract, 7% were from blood, and 22% were from other sources. Of the 136 total admissions with at least one post-discharge NIM, 92 patients had NIM-associated readmissions. Univariate Analyses 3 Table 3 Univariate analyses of factors associated with NIM Variable  Category NIM rate (%) OR 95% CI Gender Male 3.84 1.50 1.19–1.90 Female 2.59   Age <18 years 2.41 0.82 0.49–1.39 18–34 years 1.50 0.46 0.32–0.65 35–49 years 2.20 0.66 0.52–0.84 50–64 years 3.41 1.25 0.97–1.61 65–74 years 3.89 1.41 1.02–1.95 ≥75 years 7.10 2.96 2.25–3.90 Insurance Private 2.11 0.51 0.42–0.65 Medicare 5.24 2.32 1.85–2.92 Medicaid 3.19 1.12 0.74–1.68 Other 2.77 0.95 0.70–1.29 Approach Laparoscopic 2.11 0.32 0.21–0.52 Open 4.09   Procedure Cholecystectomy 3.57 1.41 1.13–1.76 Appendectomy 2.60 0.87 0.67–1.13 Hysterectomy 2.53 0.79 0.64–0.97 CMI   2.28 1.59–3.27 Complexity Complex 6.31 2.74 2.14–3.50 Not complex 2.40   Emergency department admission Emergent 3.03 1.06 0.72–1.55 Nonemergent 2.88   CI: confidence interval; NIM: nosocomial infection marker; OR: odds ratio Multivariable analyses  Since ED admission status was insignificant in the univariate analysis, it was excluded from the multivariable analyses. Pairwise correlations of all remaining covariates were performed, and all pairs were reasonably uncorrelated. Therefore, all were included in the multivariable analyses. p p 4 Table 4 Multivariable logistic regression analyses of factors associated with NIM Variable Odds ratio for NIM n n n n Laparoscopy 0.48** 0.34** 0.97 0.48** Type of procedure     Cholecystectomy 1.87** – – –     Hysterectomy 1.05  – – – Age     <18 years 0.83 – 0.90 –     18–34 years 0.64* 0.47 0.84 0.72     50–64 years 1.22 2.13* 1.00 0.96     65–74 years 1.02* 2.21* 0.58 0.51     ≥75 years 1.92** 4.04** 3.31 0.61 Male 1.4* 1.11 1.89* – Type of insurance     Medicare 1.42 1.33 1.12 2.09*     Medicaid 1.45 3.47** 1.11 0.79     Others 1.29 1.53 1.22 1.32     CMI 1.63* 1.09 1.31 2.88*     Complexity 2.45** NS 3.95 2.54** ** Statistically significant at the 1% level * Statistically significant at the 5% level 95 p 5 Table 5 Odds ratios by source  Urinary tract Wound  Respiratory tract Bloodstream Others Overall OR (95% CI) 0.61 (0.38–0.96) 0.41 (0.27–0.62) 0.20 (0.08–0.49) 0.31 (0.14–0.65) 0.52 (0.33–0.82) By procedure     Cholecystectomy 0.48 (0.24–0.97) 0.20 (0.11–0.39) 0.17 (0.06–0.45) 0.23 (0.10–0.55) 0.34 (0.18–0.64)     Appendectomy 0.83 (NS) 1.06 (NS) 0.27 (NS) Too few NIMs 0.91 (NS)     Hysterectomy 0.76 (NS) 0.27 (0.09–0.79) Too few NIMs  0.48 (NS) 0.62 (NS) OR: odds ratio, CI: confidence interval, NS: not significant p 12 p 95 Discussion 10 12 20 This study also demonstrates statistically significant differences in source-based infection risks by procedure and approach. Specifically, wound, bloodstream, respiratory tract, urinary tract, and other nosocomial infections were all statistically significantly less likely to occur in association with laparoscopic cholecystectomy. Risks of wound infections in laparoscopic hysterectomy were also significantly lower than in open procedures. However, no differences in infection risks were found between laparoscopic and open appendectomy. 1 The difference in patient severity between hospitals was accounted for by using CMI, and indeed CMI is significant in the univariate and multivariable models, with CMI contributing to nosocomial infection risks. Interestingly, admission through the emergency department was not significant in determining differences in nosocomial infection risks. One possible explanation is that emergency department use is a crude measure of patient severity because it may also be related to other factors such as time of day of admission and socioeconomic status. However, other variables associated with comorbidity, like age and certain payer types, were significant. Limitations While a variety of confounders were controlled for, this study is limited by the absence of certain data; for example, antibiotic use, anesthesia scores, wound class, body mass index, prior hospitalization, and certain comorbidities (i.e., cardiovascular status, diabetes mellitus, and immunodeficiency) were unavailable. These variables could explain additional NIM risk. Although omitted-variable bias is often a concern in multivariable modeling using retrospective databases, the similarity of findings in our univariate and multivariable analyses suggest that these results are robust. p p Other important directions for future research include controlling for potentially important confounders to test the robustness of our results and extending the analysis to examine the effect of laparoscopic versus open surgery on the risk of nosocomial infections for additional surgical procedures. Another interesting avenue for future research would be to examine the effect of hospital volume on the rate of nosocomial infections.