Introduction: Surgical site infections (SSIs) occur in 0.69% of total hip and knee arthroplasty (THA/TKA) patients (Berrios-Torres et al., 2014). As the U.S. population ages, the number of arthroplasty procedures is expected to increase as arthroplasty is more common among individuals age 65 and older. If the infection rate remains stable, we expect to see an increase in the infection burden. This analysis projects the burden of SSIs in the years 2020 through 2030 to provide evidence for or against a significant increase in the infection burden. Methods: Historical procedure rates were estimated using the National Inpatient Sample (NIS) dataset by averaging the years 2012 through 2014. Infection rates obtained from the National Healthcare Safety Network (NHSN) were averaged across the years 2006 through 2009. All rates were stratified by age and gender. We used a Markov Chain Monte Carlo (MCMC) decision tree to model the U.S. population in the years 2020 through 2030 and track the procedures and infections in each year. We then used the Cox-Stuart test for trend to test for significant increases in procedures and infections. Results: The model projected a significant increase in infections from 2020 to 2030 for both hip and knee arthroplasty (Cox-Stuart test, p = 0.04 for THA infections; p = 0.004 for TKA infections). The average projected SSIs following THA increased from 3,850 in 2020 to 4,360 infections 2030 while the average projected SSIs following TKA increased from 4,710 in 2020 to 5,060 infections in 2030. The age 65 to 84 cohort contributed the largest number of projected procedures and infections and females contributed more procedures and infections than males. Discussion: Given a projected increase in infection burden, we expect that attributable patient hospital costs and mortality will increase as well. We should consider interventions to reduce the potential impact on the U.S. healthcare system. Our results indicate that females age 65 to 84 are a high-risk group that would be available to target for interventions. Next steps in this research include adding the infection risk of additional patient characteristics and assessing the effect of interventions on overall SSI burden.
Table of Contents
Chapter 1. Introduction 6 Background 6 Problem Statement and Purpose Statement 6 Significance Statement 6 Definition of Terms 8 Chapter 2. Review of the Literature 12 Chapter 3. Methodology 19 Monte Carlo Method 20 Markov Chain Process 20 Markov Chain Monte Carlo (MCMC) Model Design 21 Model Inputs 21 Population Cohort 21 Procedure Counts 22 Table 1. Total knee arthroplasty and total hip arthroplasty procedure and infection rates stratified by age cohort and gender 23 Infection Rates 23 Background Mortality Rate 23 Applying Model Parameterization to MCMC 23 Figure 1. Markov Chain Monte Carlo decision tree for hip or knee arthroplasty 25 Statistical Analysis 26 Model Outputs 26 Credible Intervals 26 Test for Trend 27 Limitations 27 Software Packages 29 Chapter 4. Results 30 Total Hip Arthroplasty 30 Table 2. Total hip arthroplasty Monte Carlo estimators for annual procedure and infection burden for males stratified by age with results of the Cox-Stuart test for trend 31 Table 3. Total hip arthroplasty Monte Carlo estimators for annual procedure and infection burden for females stratified by age with results of the Cox-Stuart test for trend 32 Table 4. Total hip arthroplasty Monte Carlo estimators for annual procedure and infection burden stratified by age with results of the Cox-Stuart test for trend 33 Total Knee Arthroplasty 34 Table 5. Total knee arthroplasty Monte Carlo estimators for annual procedure and infection burden for males stratified by age with results of the Cox-Stuart test for trend 35 Table 6. Total knee arthroplasty Monte Carlo estimators for annual procedure and infection burden for females stratified by age with results of the Cox-Stuart test for trend 36 Table 7. Total knee arthroplasty Monte Carlo estimators for annual procedure and infection burden stratified by age with results of the Cox-Stuart test for trend 37 Comparing 2006 to 2014 estimates to model projections 38 Figure 2. Graph of estimated and projected total hip and knee arthroplasty (THA/TKA) procedures from 2006-2030 38 Figure 3. Graph of estimated and projected surgical site infections as a result of total hip and knee arthroplasty (THA/TKA) from 2006-2030 40 Chapter 5. Discussion 41 Summary of Results 41 Conclusions 41 Infection Burden 41 Impact of Age 42 Impact of Gender 42 Impact of Surgery Type 43 Limitations 43 Static Model 43 Stable Historical Rates 43 Small Sample Size 44 Credible Intervals 44 Table 8. Comparison of credible intervals (CR) and Monte Carlo mean estimates for 100 samples and 1,000 samples in male total hip arthroplasty 46 Immigration 47 Table 9. Comparison of Monte Carlo population estimators to U.S. Census projections in 2030 47 Recommendations for Further Study 47 Poisson Regression Validation 47 Comorbidity Rates 47 Mortality 48 Interventions 48 Public Health Implications 49 Final Summary 50 References 51
About this Master's Thesis
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|Projecting Hip and Knee Arthroplasty Procedures and Surgical Site Infections Using a Markov Chain Monte Carlo Decision Tree for the Years 2020 through 2030 ()||2018-08-28 15:38:56 -0400||