Infection Control & Hospital Epidemiology Statistical analyses
As our primary method, we assessed costs for all of the patients’ hospitalization and emergency room, day surgery, and day medicine visits over the subsequent 12 and 24 months. In a complementary analysis, to better estimate the incremental cost of the infection itself, we only included the cost of hospitalizations and emergency room, day surgery, and day medicine visits for admissions with International Classification of Disease, Tenth Revision (ICD-10) codes that were likely to represent infection. These were determined by tracking the infected cohort of patients over time and identifying the 6 most commonly used ICD-10 codes related to infection: T8453 (infection and inflammation reaction due to hip prosthesis), T8454 (infection and inflamma- tion reaction due to knee prosthesis), Z508 (rehabilitation care), T814 (infection following a procedure), T847 (infection and inflammatory reaction due to other internal orthopedic prosthetic devices, implants and grafts), and T8403 (mechanical complica- tion of hip prosthesis). Once the mean costs were determined for the infected and noninfected cohorts, they were compared to each other using Mann-Whitney U tests. To adjust for differences in patients developing infections (ie, age, gender, and comorbidities), the association between having a complex SSI and 1-year costs was determined using multiple variable linear regression, with the goal
Table 1. Baseline Characteristics for the Infected and Noninfected Cohort
Entire Cohort (N=24,667)
Age, mean y (SD) Female, no. (%)
Joint replaced, no. (%) Hip
Knee First Nations, no. (%)
Socioeconomic status, no. (%) Income support Social assistance Other
Comorbidities, no. (%) Congestive heart failure Diabetes
Diabetes with chronic complications Metastatic cancer Hypertension Renal Failure
Elixhauser index 0
Elixhauser index 1 or 2 Elixhauser index 3
aP value comparing the infected vs noninfected cohorts. 66.5 (10.4) 14,044 (57.0)
9,765 (39.6) 14,902 (60.4) 354 (1.4)
705 (2.9)
14,448 (58.6) 8,591 (34.8)
157 (0.6)
2,608 (10.6) 891 (3.6) 20 (0.1)
8,800 (35.7) 236 (1.0)
11,627 (47.1) 7,992 (32.4) 5,048 (20.5)
Infected Cohort (N=258)
66.8 (11.7) 123 (47.7)
145 (56.2) 113 (43.8) 5 (1.9)
12 (4.7)
156 (60.5) 85 (32.9)
7 (2.7)
35 (13.6) 8 (3.1) 1 (0.4)
127 (49.2) 4 (1.6)
86 (33.3) 93 (36.1) 79 (30.6)
Non-Infected Cohort (N=24,409) 66.5 (10.4)
13,921 (57.0)
9,620 (39.4) 14,789 (60.6) 349 (1.4)
693 (2.8)
14,292 (58.6) 8,506 (34.8)
150 (0.6)
2,573 (10.5) 883 (3.6) 19 (0.1)
8,673 (35.5) 232 (1.0)
11,541 (47.3) 7,899 (32.4) 4,969 (20.4)
P Valuea .562 .003
<.001 <.001 .495
.082 .535 .524
<.001 .116 .658 .082
<.001 <.001 <.001 .208
<.001
1185
of determining an attributable cost of complex joint infection. A linear regression model using ordinary least squares estimation was used based on its interpretability and ability to model the mean costs for each group. While ordinary least squares estima- tion assumes a normal distribution of the residual values, if the sample size is large enough, then this assumption being violated does not impact the magnitude of coefficients when compared with other regression methods.19 When compared to other linear models including log total costs with smearing retransformation, negative binomial (γ), and inverse Gaussian distributions, ordinary least squares performed well on measures of con- cordance, mean absolute error, root mean squared error, and probability plots. All statistical analyses were conducted using Stata version 14 software (StataCorp, College Station, TX). The University of Calgary Health Research Ethics Board
approved this study.
Results Baseline characteristics
The baseline characteristics for the population are listed in Table 1. In total, 24,925 primary hip and knee arthroplasties were completed in Alberta between April 1, 2012, and March 31, 2015.
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