Moving from Data to Insight with Analytics 
 

NIHI - McMaster CE Microcredential Course

 

Instructor
Trevor Strome, MSc,
Manager, Digital Airport Solutions, Winnipeg Airports Authority; Assistant Professor, Department of Emergency Medicine, College of Medicine, Faculty of Health Sciences, University of Manitoba; Author "Healthcare Analytics for Quality and Performance Improvement"

This course will provide you the essential information you need to make the right decisions about the right analytics for your organization. This course is built around the generally accepted four types of analytics. Which type of analytics you choose will depend on the analytics needs of your organization, as well as the capability of your organization to deliver. This course will draw examples from industries such as air transportation, healthcare, insurance, and other of today’s top industries.

This 8 Session (14.5 Hours) certificate program is for anyone who is responsible for managing, developing, or using analytics within their organization, or is interested in being part of their organization’s analytics team.

Upon completion you will be awarded a NIHI - McMaster CE microcredential in Data Analytics: Moving from Data to Insight with Analytics. A microcredential is issued in a digital format, provides details of acquired competencies and is shareable and transportable.

Please note that you do not need to take the NIHI - McMaster University CE Course Data Analytics I: Operational Analytics for Quality & Performance Improvement in order to register for this course. 

Module Plan

• ​Session 1 - Course Overview and Introduction - 1.5 Hours
   
• Session 2 (Recorded) - Analytics System and Outputs Overview - 2 Hours
  1. Choosing your analytics approach
     • Understanding the analytical needs of your organization
     • Analytic capabilities of your organization
  2. Developing & deploying an analytics model
      
• Session 3 (Recorded) - Descriptive analytics - 2 Hours
  • Analytics that typically examine past or current (i.e., real-time) performance, answering questions such as “what happened” or “what is happening”. Topics covered in this session will include:
    • Statistical analysis & reporting
    • Information dashboards
       
• Session 4 (Recorded) - Diagnostic analytics  - 2 Hours
  • Dive deeper into a problem to help understand why performance, quality, or other factors are the way they are. Topics discussed in this session will include:
    • Statistical process control
    • Relationships & correlations in data
    • Drilldown / drill-through
       
• Session 5 - Content Review, Q&A, Assignment Discussion  - 1.5 Hours
   
• Session 6 (Recorded) - Predictive & Prescriptive Analytics - 2 Hours
  • Algorithms that attempt to determine what will happen next, or what performance and/or quality will be like. Prescriptive analytics – optimization algorithms and approaches that offer suggestions of what actions to take to achieve/maintain optimal performance. 
    • Machine Learning algorithms (i.e. Regression, Classification, Clustering)
    • Optimization algorithms
    • Simulation
       
• Session 7 (Recorded) - Data Provisioning and Management - 2 Hours
  • The tools and approaches required to move high-quality data from source systems to where it is required throughout an organization. 
    1. Measuring & improving data quality
    2. Building & maintaining data pipelines
    3. DataOps
        
• Session 8 - Course summary, Q&A  - 1.5 Hours

Expected Outcomes

• Discover how to transform your organization’s analytics from a collection of reports and dashboards to an integrated leadership/management system.
• Identify the critical inputs, enablers, and context that, when applied to the proper analytical methods, generate deep insight into past, current, and predicted future performance.
• Learn from examples and real-life case studies how analytics can be deployed to inform decision-making at all levels of an organization by providing the right insight at the right time to the right people.
• Deploy the optimal data, team, technology, and analytical techniques to achieve the performance goals of your organization
• Align quality and performance goals of management, departments, and programs to provide actionable intelligence for healthcare executives and transformation teams

Competencies Achieved

• Transform data from a collection of reports and dashboards to an integrated leadership/management system.
• Identify the critical inputs, enablers, and context that, when applied to the proper analytical methods, generate deep insight into past, current, and predicted future performance.
• Survey case studies on how analytics can be deployed to inform decision-making at all levels of an organization Deploy the optimal data, team, technology, and analytical techniques to achieve the performance goals of your organization.
• Examine the impact of data analytics on the quality and performance goals of an organization.

Intended Audience

• Anyone responsible for developing or utilizing analytics in public or private sector organizations
• Chief Analytics Officers
• Chief Data Officers
• Chief information officers
• Data Scientists
• Business Intelligence Analysts
• Data Analysts
• Policy Analysts
• Systems / Business Analysts
• Database Administrators
• Consultants and solution providers who need to offer analytics-related products and services to private and public sector organizations
• Technical architects and developers who design and build cloud, mobile, and other analytical solutions.