Data Analysis Skills and Performance Index in Healthcare

• Define the concepts of data statistics and related administration concepts
• Identify the health care system and how can be used during data analysis and how to make sure the legality, ethicality, and privacy of patient data
• Explain how to improving data statistics in health care field and how improves the performance.
• Clarify the role of data statics during epidemiology and sampling technique.
• Describe the statics processes (analysis, validation, sampling, collection, designing, proper tools, display, monitoring, display and interpret)
• Identify the relationship and role between technology in data science and healthcare
• Differentiate between descriptive and Inferential Statistics and measurement tools for each one

First Day:

• Epidemiological theory and methodology
• Sampling techniques
• Statistical Handling of Numbers
• Process tools
• Display and Statistical tools
• Monitoring process variation
• Center of Healthcare Intelligence

Second Day:

• Definitions and goals; Basic concept to data and information management; type of information; data collection methodologies and tools.
• Legal and ethical changeless in dealing with data; medical/health record data.
• Health Information System.
• Introduction of Key Performance Indicators.
• Developing Key Performance Indicators.
• Safety Reporting System
• Data Driven Performance Improvement.

Third Day:

• Descriptive and Inferential Statistics
• Measure Selection
• Developing Key Performance Indicators
• Graphical Presentation of Data
• Data analysis and display using storytelling techniques
• Measurement Reporting
• Data Driven Performance Improvement
• Data validation
• Improvement Methodologies

• Identify the basics concepts and terms of data statistics
•  Identify how to improving the skills and knowledge on the institution by using data analysis.
• Explain how to use the data in proper way to improvement.
•  Illustrate how display data on the different methods methods depending on the type of data - Clarify the importance of the privacy of patient data