Introduction: Irresponsible use of antibiotics has led to concern about antibiotic resistance. The Antibiotic Stewardship Program (ASP) was introduced nationally to control the antibiotic usage. At Grady Health System, an intervention was implemented by sending out an email to the internal medicine physicians with the report of their historical and current prescription of intravenous vancomycin. The objective of this quality improvement project was to evaluate whether the report card intervention was associated with the provider’s vancomycin prescription behavior. This thesis examines various modeling strategies to assess this association.
Methods: As of December 1, 2016, the intervention was implemented by sending out the bi-weekly report on physicians’ intravenous vancomycin use. In this analysis, the outcome measure is the days of therapy per 100 patient days, which is the vancomycin use rate. An Interrupted Time Series model, Negative Binomial repeated measures model with offset term, and linear mixed model with AR(1) covariance structure were fitted and compared to examine the impact of the intervention.
Results: A total of 64 physicians were included in this two-year period quality improvement project. The estimated baseline vancomycin prescription rate was 10.35 (95% confidence interval, 9.22 to 11.47). When physicians started to receive a report card, the vancomycin prescription rate declined by 2.33 (95% confidence interval, -3.79, to 0.87). Throughout the post-intervention year, the rate decreased by 0.13 (95% confidence interval, -0.24, -0.03) every two weeks.
Conclusion: During the historical year (pre-intervention period), no significant temporal trend of the vancomycin prescription rate was measured. However, once the intervention was introduced on December 1, 2016, there was an immediate drop of the vancomycin use rate. During the post-intervention period, constant decline of the vancomycin use rate was captured. These results were consistent over three modeling strategies that provides the audience options to choose based on their research questions.
Table of Contents
Table of Contents
2.1 Study Design and Intervention
2.2 Data Collection and Cleaning
2.3 Outcome of Interest
2.4 Statistical Analysis
2.4.1 Interrupted Time Series
2.4.2 Nonlinear mixed model
2.4.3 Linear mixed model with AR(1) covariance structure
Appendix: SAS Programming Code
About this Master's Thesis
|Committee Chair / Thesis Advisor|