Comparative Analysis Purpose: Comparative analysis involves comparing current data to historical data or established benchmarks to identify trends, outliers, and patterns. Methods: Trend Analysis: Review performance over time by plotting data points on a graph to observe trends. This can utilize line graphs or bar charts. Benchmarking: Compare your data against industry standards or best practices. Example: Compare your hospital's average length of stay (ALOS) with the national average. Cross-sectional Comparisons: Analyze different segments (e.g., by department, service line, or demographics) within your data. Example: Comparing readmission rates for different departments (e.g., cardiology vs. orthopedics). Statistical Tests: Use statistical tests (e.g., t-tests, ANOVA) to assess whether differences between groups are statistically significant. Example: Suppose the historical average length of stay was 5 days, and the current ALOS is 4 days. This signifies an improvement, which can be visually represented on a graph to show the trend over time