Health Organizations Overview

Joint Commission

• A quasi-regulatory organization responsible for inspecting and accrediting hospitals.
• Uses a rigorous set of scored criteria to evaluate healthcare facilities.
• Aims to ensure quality and safety standards in healthcare settings.

Leapfrog Group

• A third-party organization focused on improving healthcare safety.
• Provides consumers with data to aid in making informed hospital choices.
• Works alongside state organizations to enhance healthcare quality.

Department of Health

• A third-party external reporting agency monitoring healthcare quality metrics.
• Evaluates key metrics for healthcare standards at state and national levels.
• Ensures accountability and improvement in public health services.

Categories of Change Adoption

• Innovators

  • Pioneers of change, characterized by curiosity and bravery.
  • Willing to embrace uncertainty and learn from failures.
  • Eager to experiment with new tools and methods.

• Early Adopters

  • Respected opinion leaders within organizations.
  • Open to change and innovation, using Innovators' experiences to guide their decisions.
  • Their acceptance helps to validate new ideas and technologies.

• Early Majority

  • Cautious and cooperative individuals who adopt innovations thoughtfully.
  • Aim to align with positive changes and follow directions from organizational leaders.
  • Represent a significant group that bridges the gap between early adopters and the late majority.

• Late Majority

  • Individuals who adopt change or new technology after the majority has already done so.
  • Typically resistant at first but shift when the cost of not changing outweighs the effort to adapt.
  • Viewed as followers rather than leaders in the innovation process.

• Laggards

  • Traditionalists who resist change and prefer established methods.
  • Usually adopt innovations only after they are well-established and considered standard.
  • Seen as the last group to conform, often avoiding anything perceived as radical.

Velocity

• Refers to the speed at which data is generated, processed, and utilized across applications.
• Data momentum is growing exponentially, enhancing user experiences.
• Cellular technology advancements allow consumers to track health metrics and interact digitally with healthcare providers.

Volume

• Indicates the vast amount of data available, with exponential growth patterns.
• Significant implications for healthcare data management and operational efficiency.
• Data growth in healthcare is expected to surpass other sectors, except for global security and social media.

Variety

• Encompasses the diverse types and sources of data being generated.
• Expansion of data descriptions points to limitless possibilities.
• New personal electronic devices will facilitate the measurement of various bodily functions.

Veracity

• Denotes the accuracy and reliability of data and analytics systems.
• High veracity is essential for user trust in software applications and resulting data outputs.

Machine Learning vs Deep Learning

• Machine learning automates model improvement through data analytics, continuously enhancing performance with additional data.
• Deep learning mimics brain functionality by creating artificial neural networks with multiple layers, allowing for complex learning patterns as data is processed.

Health Spending Measures

• Refers to the final consumption of healthcare goods and services, encompassing both personal healthcare and collective services while excluding investments.
• Per Capita Expenditure represents the average healthcare spending per individual in a population.
• Total National Health Expenditure accounts for the comprehensive financial outlay on healthcare services and products across an entire country.
• Spending by Payer Types analyzes healthcare costs across various groups, including government programs, private insurers, and out-of-pocket expenses.