Operational Analytics for Quality & Performance Improvement 
 

NIHI - McMaster CE Microcredential Course

Format
8 Sessions, 14.5 Hours
5 Recorded, 3 Live & Online
 

Instructor

Trevor Strome, MSc
Director, Digital Airport Solutions, Winnipeg Airports Authority; Assistant Professor, Department of Emergency Medicine, College of Medicine, Faculty of Health Sciences, University of Manitoba

The Data Analytics I: Operational Analytics for Quality & Performance Improvement certificate program will provide executives, managers, analysts, and other stakeholders with the essential information needed to fully leverage the power of the data within their healthcare organizations. The goal is to provide decision-makers with the knowledge and tools to immediately improve analytics effectiveness and return-on-investment within your organization, branch, department, or unit. The sessions will cover how to synthesize data from source systems and combine it with proven Quality Improvement (QI) methodologies, well-defined quality and performance goals, and powerful analytical methods to enable more insightful, fact-based decisions that achieve desired outcomes and create an impact within an organization.

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: Operational Analytics for Quality and Performance Improvement. A microcredential is issued in a digital format, provides details of acquired competencies and is shareable and transportable.

Learning Objectives

• Prepare organizations to gain maximum value from the data typically “locked” in source systems and/or departmental silos.
• Demonstrate that analytics must be thought of as a “system” (with specific inputs and outputs) if real organizational transformation and return on investment is to be achieved.
• Showcase how analytics tools and techniques can (and should!) be used in concert with established quality improvement methodologies.

Module Plan

• ​Session 1 - Course Overview and Introduction to Analytics - 1.5 Hour
   
• Session 2 (Recorded) - Analytics System Model - 2 Hours
  • Analytics is the system of tools, techniques, and people required to consistently and reliably generate accurate, validated, and trustworthy business insight necessary to drive decision-making and guide appropriate action.
    1. Introduction to quality & system performance
    2. Improvement, Innovtion, & Transformation
    3. Analytics "Value Chain" - Moving from data to decisions
        
• Session 3 (Recorded) - Analytics System Inputs - 2 Hours
  • The inputs to an analytics system can be considered “raw materials” that when combined, processed, and transformed are able to provide value to an organization as a whole.
    1. The essential dialogue required with (and among) stakeholders to better understand their requirements
    2. What factors within an organization are driving the need for data-driven transformation
    3. How to determine what data sources are required, available, and accessible to enable analytics within an organization.
        
• Session 4 (Recorded) - Analytics System Enablers - 2 Hours
  • The enablers of an analytics system the tools, technology, and techniques that transform the system inputs and are what enable an organization to achieve data-informed decision-making, deeper insight into performance, and operations excellence.
     
• Session 5 - Content Review, Q&A, Assignment Discussion  - 1.5 Hour
   
• Session 6 (Recorded) - Analytics and Improvement methodologies - 2 Hours
  • Using examples from Lean and Six Sigma, this session will focus on methodologies, principles, and tools necessary required for an organization to achieve a sustainable competitive advantage by addressing inefficiencies, waste, and other negative impacts on (and from) processes and stakeholders.
     
• Session 7 (Recorded) - Data Visualization and User Experience - 2 Hours
  • To enhance the usability of data analytics by end users, this session will focus on the elements of good design and best practices relating to data visualization (including dashboards).
     
• Session 8 - Course summary, Q&A  - 1.5 Hour

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

• Identify how organizations can gain maximum value from the data typically “locked” in source systems and/or departmental silos.
• Explain the benefit of analytics as a “system” and its impact on organizational transformation and return on investment.
• Explore how analytics tools and techniques are applied to established quality improvement methodologies.

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.