ClinicalLaboratory

ClinicalLaboratory forecasts clinical laboratory test volumes using time-series analysis to support demand prediction and resource planning.

Key Features:

• Predictive Analytics: Generates quantitative forecasts of future test volumes from historical time-series data.
• Time-Series Models: Implements Holt-Winters multiplicative, Holt-Winters additive, and simple linear regression models for temporal analysis.
• Model Ranking and Selection: Ranks model performance by predictive accuracy and identifies the top-performing model for each dataset.

Scientific Applications:

• Clinical laboratory demand forecasting: Predicts test volumes to inform staffing, inventory, and budget planning in laboratory operations.
• Utilization management evaluation: Compares predicted volumes with actual test volumes to assess the impact of utilization management initiatives.

Methodology:

Performs time-series analysis using Holt-Winters multiplicative, Holt-Winters additive, and simple linear regression models; computes predictive accuracy metrics to rank models and compares predicted versus actual test volumes.