Comparative experimental design is a research method used to determine the effectiveness of an intervention by comparing outcomes in a group that receives the intervention (the treatment group) with a group that does not (the control group). This rigorous approach allows researchers to isolate the impact of the intervention from other factors. This article explores a comparative experimental design used to evaluate the impact of a clinical decision support (CDS) tool on antibiotic prescribing for acute respiratory infections (ARIs).
Understanding the Comparative Design in ARI Research
This study, conducted within a primary care research network in the United States, utilized a comparative experimental design to assess the efficacy of a CDS tool in improving antibiotic prescribing practices for ARIs. The researchers compared outcomes between an intervention group and a control group. The key elements of the design include:
Participants and Setting
The study involved nine practices across nine states in the intervention group and 61 practices in the control group. All participating practices used a common electronic medical record (EMR) system, enabling standardized data collection and analysis. Data was pooled quarterly for quality improvement and research purposes.
Intervention and Control
The intervention group received a multifaceted intervention centered on a point-of-care CDS tool integrated into their EMR system. This tool offered customizable progress note templates aligned with Centers for Disease Control and Prevention (CDC) guidelines for ARI diagnosis and treatment based on patient symptoms and age. The CDS tool aided in diagnosis, prompted appropriate antibiotic use, documented decisions, and provided access to patient and provider educational materials.
The control group continued their usual practices without access to the CDS tool or any related training. This allowed researchers to isolate the impact of the CDS intervention.
Figure 1. Comparison of Intervention and Control groups based on inappropriate antibiotic prescription.
Data Collection and Analysis
Baseline data was collected for three months before CDS implementation, followed by 15 months of post-implementation data collection. Outcomes measured included the frequency of inappropriate antibiotic prescribing, broad-spectrum antibiotic use, and diagnostic shifts. Data was analyzed quarterly, weighted by the number of ARI episodes to account for varying practice sizes and seasonal fluctuations in ARI incidence. Statistical analysis involved weighted means, 95% confidence intervals, t-tests, and linear mixed models to compare changes between the two groups over time, adjusting for practice characteristics.
Outcomes and Findings
The study demonstrated the effectiveness of the CDS tool in reducing inappropriate antibiotic prescribing. For adult ARI patients, inappropriate prescribing declined significantly more in the intervention group compared to the control group. A substantial reduction in broad-spectrum antibiotic use was observed in both adult and pediatric patients in the intervention group, contrasting with an increase in the control group. The CDS tool had a modest effect on reducing inappropriate prescribing for adults but significantly impacted the reduction of broad-spectrum antibiotic prescriptions in both adult and pediatric patients.
Conclusion: The Power of Comparative Design
This case study highlights the value of comparative experimental design in healthcare research. By comparing outcomes between intervention and control groups, researchers were able to demonstrate the positive impact of the CDS tool on antibiotic prescribing practices. This type of rigorous research is crucial for informing evidence-based practice and improving patient care. The findings support the implementation of CDS tools to promote judicious antibiotic use and combat antibiotic resistance. Further research could explore the long-term effects of CDS interventions and their impact on patient outcomes.
