Data Analytics Solution for Forecasting Healthcare Market Trends

Evaluate Statistical Analysis System (SAS) scripts and assess challenges in tracking recent changes.

Make necessary adjustments to the SAS scripts, including updating demographics to reflect the desired timeframe, execute the scripts, and thoroughly analyze the output for anomalies to ensure reliable and smooth analytics.

Filter data using SAS scripts based on medical institutions, age groups, disease types, and relevant criteria, remove irrelevant information, and optimize data loading for enhanced performance.

Ensure the relevance and accuracy of input data by updating it to reflect changes in the healthcare industry, aligning with current practices, standards, and terminology.

Utilize logistic regression formulas to generate insights and forecasts by considering factors like age, gender, and location, and evaluate logs and predictions within a specified timeframe (e.g., 5 and 10 years).

Analyze healthcare industry changes by comparing logs and previous years’ readings, visualize data through graphs, and identify areas requiring attention. Additionally, we developed Python script to investigate significant deviations from previous results and devise appropriate solutions.

Update and enhance the documentation of analytic models and processes, including clear explanations of the underlying logic, providing clients with up-to-date data.