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Course Description

FREE "POWER UP YOUR CAREER" SEMINAR SERIES WITH COURSE REGISTRATION

Data analytics is frequently described as a “new” methodology, but most healthcare professionals have been analyzing data their entire careers. The big difference today is the volume of data available to inform healthcare business decisions. Data enables your organization to improve patient care, manage population health and reduce operating costs.

This one-day seminar arms you with tools and strategies to determine what data is useful, ask the right questions of analysts who support you, interpret results to make good business decisions and effectively communicate your conclusions to varied audiences.

Learn how the different healthcare transformation activities fit together to form a cohesive population health approach that can be operationalized.

Topics include:

• Healthcare informatics

• Using data to make informed population health decisions

• Techniques for using data in your operation

• How to report and communicate results

Who should participate?

• Clinical supervisors and managers

• Data analysts and business analysts

• Healthcare leaders (all levels)

• Healthcare professionals who need to understand the interrelationships between health informatics, data analytics and population health management

Course Outline

The one-day course outline is as follows:

Topic 1: Introduction to Informatics including – The basics of healthcare informatics (2 hours)

Course Content:

  • Application in the clinical setting
  • Knowledge Management
  • Knowledge Management Hierarchy
  • Population Health
  • Secondary Data Analysis (Big Data vs. Small Data)
  • Establishing roles – Who does the work?
  • Learning Activity – Data, Information, Knowledge & Wisdom

 

Topic 2: Data Infrastructure – A description of the supporting infrastructure (1 hour)

Course Content:

  • Performance Measurement
  • Clinical & Business Intelligence Evolution
  • Database architecture
  • Healthcare information systems – The building blocks
  • Mapping data sources
  • Connecting disparate information systems
  • Data governance & management of data assets
  • Learning activity – data mapping my organizations data assets

 

Topic 3: Data insight for clinical practice (3 hours)

Course Content:

  • Population Health Lifecycle
  • Health IT enablers of population health activities
  • Managing population health risk
  • Attribution
  • Applying risk methods to stratification
  • Population characteristics
  • Developing health improvement strategy
  • Using evidence
  • Improvement strategies
  • Choosing outcomes
  • Learning activity – evidence vs. practice preference

 

Topic 4: Measures, Scorecards and Dashboards – methods to report results (2 hours)

Course Content:

  • Baselines and trending
  • Improvement science
  • Driving improvement
  • Process improvement process – Lean-lite for health care
  • Examples in health care operation
  • Quality Connection – using data to tell your story
  • Case study – analysis of end-user report design
  • Learning activity – presenting information in the health care setting

 

Learner Outcomes

Topic 1: Introduction to Informatics including – The basics of healthcare informatics (2 hours)

By the end of this session the learner will be able to:

  • State the definition of healthcare informatics.
  • Understand basic clinical application of informatics.
  • Identify the key features of data and information.
  • Name the structural components of the knowledge management hierarchy and describe the significance of each component.

Topic 2: Data Infrastructure – A description of the supporting infrastructure (1 hour)

By the end of this session the learner will be able to:

  • Describe challenges of performance management.
  • Identify technical infrastructures types that exist in health care today.
  • Define information exchange capabilities available in typical health care systems.
  • Understand the tools necessary to transform data from electronic health records and information systems, into useable data sets for health care.

Topic 3: Data Insight for Clinical Practice (3 hours)

By the end of this session the learner will be able to:

  • Understand the basic principles of health data analysis.
  • Identify at least one risk identification model used in total cost of care arrangements.
  • Recognize basic data pattern from population health data analysis demonstration.
  • Name at least two technical enablers needed to transform health care into a population health system.

Topic 4: Measures, Scorecards and Dashboards – methods to report results (2 hours)

By the end of this session the learner will be able to:

  • Define purpose of Performance Improvement processes and outcomes.
  • Describe types of measures, scorecards and dashboards available.
  • Discuss report structures and end-user preference.
 
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