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Data Analytics and Visualization in Health Care

Learn best practices in data analytics, informatics, and visualization to gain literacy in data-driven, strategic imperatives that affect all facets of health care.

Data Analytics and Visualization in Health Care

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Comienza el 15 oct
Termina el 20 dic
Comienza el 17 ene 2022
8 semanas estimadas
8–10 horas por semana
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Sobre este curso

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Big data is transforming the health care industry relative to improving quality of care and reducing costs--key objectives for most organizations. Employers are desperately searching for professionals who have the ability to extract, analyze, and interpret data from patient health records, insurance claims, financial records, and more to tell a compelling and actionable story using health care data analytics.

The course begins with a study of key components of the U.S. health care system as they relate to data and analytics. While we will be looking through a U.S. lens, the topics will be familiar to global learners, who will be invited to compare/contrast with their country's system.

With that essential industry context, we'll explore the role of health informatics and health information technology in evidence-based medicine, population health, clinical process improvement, and consumer health.

Using that as a foundation, we'll outline the components of a successful data analytics program in health care, establishing a "virtuous cycle" of data quality and standardization required for clinical improvement and innovation.

The course culminates in a study of how visualizations harness data to tell a powerful, actionable story. We'll build an awareness of visualization tools and their features, as well as gain familiarity with various analytic tools.

De un vistazo

  • Institución: RITx
  • Tema: Análisis de datos
  • Nivel: Advanced
  • Prerrequisitos:

    This course is ideal for those who have completed a bachelor's degree. Some experience in the health care field recommended, but not required. Fundamental knowledge of statistics and research methods preferred.

  • Idioma: English
  • Transcripción de video: English

Lo que aprenderás

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  • Identify current forces disrupting today's health care industry
  • Summarize current health care trends and their impact on cost, quality, and patient engagement
  • Describe health informatics' role in clinical workflow and patient engagement
  • Identify components of health information technology
  • Explain the importance interoperability in health care analytics
  • Summarize data collection, processing, and analysis best practices
  • Explore the implications of artificial intelligence on extraction and analysis of complex data sets
  • Interpret data analysis results from a visualization example
  • Identify visualization best practices
  • Prepare a simple data visualization using health care data

Plan de estudios

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Module 1: Introduction to Health Care

Components of Health Care
Stakeholders
Care Settings
Financing
Public Health
Regulatory/Research

Challenges and Opportunities
The Triple Aim
Quality and Cos
Patient Experience/Access

Systems Approach
Evidence-Based Medicine
Quality Improvement
Value-Based Reimbursement

Health Care Trends
Demographics/Population Health
Consumerism/Personalized Medicine
Emerging Trends in Health Care

Module 2: Introduction to Health Informatics

Overview of Health IT
What is Health Informatics?
How Health Informatics Supports Triple Aim

Health IT Systems and Components
EMR/EHR Modules and Ancillary Data Systems
Enterprise Systems vs. Best of Breed
Structured Versus Unstructured Data

EHR Adoption
EHR Regulations
Barriers to EHR Adoption

Interoperability and HIT Standards
Health IT Standards
Data Exchange
Clinical Decision Support
HIPAA Security

Public Health IT and Consumer Engagement

Module 3: Introduction to Data Analytics

Data Terms and Concepts
Why Data Analytics?
Virtuous Cycle in Analytics
Data Terminology
Big Data Terminology

Getting Data Ready for Analysis
Considerations Before Analyzing
Integrating Data Across Data Sets

Data Governance, Privacy, and Security
Data Governance Within the Organization
Patient Identification
Regulatory Considerations and Data Security

Analysis with Artificial Intelligence
Machine Learning in Health Care
Natural Language Processing in Health Care

Making Data Usable to Others
Finalizing Data for Analysis
Communicating Data

Module 4: Introduction to Visualizations

Value of Visualization

Visualization Best Practices
What Not to Do
Types Based on Use Case
Visualizations of Complex Data
Dashboard Design

Analyzing Visuals
Exploratory vs. Explanatory Visualization
Quantitative vs. Qualitative Visualization
Uses in Health Care

Tools for Analysis and Visualization
Gartner Software Benchmarking
Current Tools

Acerca de los instructores

¿Quién puede hacer este curso?

Lamentablemente, las personas residentes en uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.

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