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Health Informatics Course
More than 2 million students worldwide

Health Informatics Course

4.3

Health informatics is reshaping how care is delivered, managed, and measured — and professionals who understand it are in high demand. This course gives you the technical knowledge and strategic skills to work confidently across EHR systems, data governance, clinical analytics, and health IT leadership. Whether you're advancing your current role or pivoting into the field, this is the training that gets you there.

Dedika for businesses

What you will learn:

You will gain a thorough understanding of health data standards, interoperability frameworks, and EHR architecture. You will learn how to manage data quality, apply governance principles, and protect patient information through proven security and compliance practices. The course covers clinical decision support design, predictive analytics, and quality measure reporting. You will also explore AI applications, telehealth technologies, and population health informatics. By the end, you will be equipped to lead health IT projects, manage stakeholders, and drive strategic technology decisions in complex healthcare organizations.

How you study in practice Health Informatics Course

How you practice Health Informatics Course

For companies that want to train their team

With Dedika for Business, the course includes exercises and examples tailored to your own business and the way your company needs.

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Course content

8 Chapters • 40 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

Foundations of Health Informatics

  • Lesson 1 • History and Evolution of the Field

    Traces milestones from paper records to digital systems. Provides context for understanding why current standards and workflows exist.

  • Lesson 2 • Informatics Roles and Career Pathways

    Profiles clinical informaticist, analyst, and CMIO roles with required skills. Helps students map course content to real career trajectories.

  • Lesson 3 • Data Types in Healthcare

    Distinguishes structured, unstructured, and semi-structured clinical data. Prepares students to select appropriate tools for each data category.

  • Lesson 4 • Defining Health Informatics

    Covers the discipline's definition, boundaries, and relationship to adjacent fields. Anchors all subsequent chapters by establishing shared terminology.

  • Lesson 5 • Healthcare System Structures

    Maps care delivery settings, payer models, and governance bodies. Students connect informatics tools to the organizational contexts where they operate.

Chapter 2See details

Health Data Standards and Interoperability

  • Lesson 1 • Clinical Terminology Systems

    Introduces SNOMED CT, LOINC, ICD, and CPT as the vocabulary layer of interoperability. Students map clinical concepts to correct code sets.

  • Lesson 2 • Interoperability Frameworks

    Explains syntactic, semantic, and organizational interoperability layers. Students assess real-world exchange scenarios against each layer.

  • Lesson 3 • Messaging and Document Standards

    Covers HL7 v2, HL7 FHIR, and CDA document architecture. Students trace a message from source system to receiving application.

  • Lesson 4 • Evaluating Interoperability Maturity

    Applies maturity models to score an organization's exchange capability. Connects standards knowledge to strategic improvement planning.

  • Lesson 5 • Health Information Exchange Models

    Compares federated, centralized, and hybrid HIE architectures. Students recommend an architecture for a given organizational scenario.

Chapter 3See details

Electronic Health Record Systems

  • Lesson 1 • EHR Configuration and Build

    Covers order sets, clinical decision support rules, and form design within EHR build environments. Students apply configuration principles to a simulated scenario.

  • Lesson 2 • EHR Architecture and Components

    Breaks down clinical, administrative, and technical modules within an EHR. Establishes the system map students use throughout the chapter.

  • Lesson 3 • EHR Implementation and Go-Live

    Outlines project phases, training strategies, and go-live support models. Students draft a high-level implementation plan for a small clinic scenario.

  • Lesson 4 • Clinical Workflow Mapping

    Uses process mapping to document current-state and future-state clinical workflows. Students identify friction points that informatics interventions can resolve.

  • Lesson 5 • Usability and User Experience

    Applies usability heuristics and cognitive load theory to EHR interface evaluation. Students conduct a structured usability review of a sample interface.

Chapter 4See details

Health Data Management and Governance

  • Lesson 1 • Data Lifecycle Management

    Maps data from creation through archival and destruction with retention policy guidance. Students apply lifecycle stages to a clinical data scenario.

  • Lesson 2 • Data Quality Dimensions

    Applies accuracy, completeness, timeliness, and consistency dimensions to clinical datasets. Students score a sample dataset and propose remediation steps.

  • Lesson 3 • Metadata and Data Cataloging

    Explains business, technical, and operational metadata and their role in data discovery. Students build a metadata schema for a clinical data element.

  • Lesson 4 • Data Governance Principles

    Defines governance roles, policies, and accountability structures for health data assets. Provides the organizational foundation for all data management activities.

  • Lesson 5 • Master Data Management in Healthcare

    Covers enterprise master patient index, provider registry, and location master files. Students resolve duplicate records using probabilistic matching logic.

Chapter 5See details

Privacy, Security, and Compliance in Health IT

  • Lesson 1 • Compliance Frameworks and Auditing

    Maps security controls to healthcare compliance frameworks and audit requirements. Students perform a gap analysis against a selected compliance framework.

  • Lesson 2 • Risk Assessment and Management

    Applies qualitative and quantitative risk assessment methodologies to health IT environments. Students complete a structured risk register for a sample organization.

  • Lesson 3 • Privacy Principles in Healthcare

    Covers patient rights, minimum necessary standards, and notice of privacy practices. Grounds security work in the ethical and regulatory rationale for data protection.

  • Lesson 4 • Access Control and Identity Management

    Covers role-based access, multi-factor authentication, and privileged access management. Students design an access control matrix for a clinical application.

  • Lesson 5 • Information Security Fundamentals

    Introduces the CIA triad, threat modeling, and common attack vectors in healthcare. Students classify threats and map controls to each threat category.

Chapter 6See details

Clinical Decision Support and Knowledge Management

  • Lesson 1 • CDS Design and Alert Fatigue

    Applies evidence-based design principles to reduce non-actionable alerts. Students redesign an overriding alert using specificity and tiering strategies.

  • Lesson 2 • CDS Fundamentals and Taxonomy

    Defines CDS types including alerts, order sets, dashboards, and documentation templates. Establishes the classification framework used throughout the chapter.

  • Lesson 3 • Evaluating CDS Effectiveness

    Applies pre-post and interrupted time series designs to measure CDS impact on outcomes. Students select an evaluation design and define success metrics.

  • Lesson 4 • Knowledge Representation Methods

    Covers rule-based logic, ontologies, and clinical guidelines as knowledge sources for CDS. Students translate a clinical guideline into executable rule logic.

  • Lesson 5 • CDS Implementation and Governance

    Outlines governance workflows for CDS content review, approval, and retirement. Students draft a CDS governance policy for a hospital informatics committee.

Chapter 7See details

Health Data Analytics and Reporting

  • Lesson 1 • Clinical Quality Measures and Reporting

    Defines measure types, numerator-denominator logic, and reporting submission workflows. Students calculate a quality measure from a sample dataset.

  • Lesson 2 • Data Visualization for Healthcare

    Applies visualization best practices to clinical dashboards and executive scorecards. Students critique and redesign a poorly constructed clinical dashboard.

  • Lesson 3 • Data Warehousing and ETL Processes

    Covers dimensional modeling, ETL pipeline design, and data warehouse architecture for health data. Students design a star schema for a clinical quality measure.

  • Lesson 4 • Predictive Modeling in Clinical Settings

    Introduces regression, classification, and risk stratification models applied to patient populations. Students interpret model outputs and communicate findings to clinicians.

  • Lesson 5 • Analytics Maturity and Strategy

    Positions descriptive, diagnostic, predictive, and prescriptive analytics on a maturity curve. Students assess an organization's current analytics capability.

Chapter 8See details

Strategic Health IT Leadership and Innovation

  • Lesson 1 • Innovation and Emerging Technology Adoption

    Applies innovation adoption frameworks to assess readiness for AI, telehealth, and wearables. Students build a technology adoption roadmap for a selected innovation.

  • Lesson 2 • Health IT Strategic Planning

    Aligns IT investments with organizational mission, clinical goals, and financial constraints. Students conduct a SWOT analysis and draft strategic IT objectives.

  • Lesson 3 • Vendor Selection and Contract Management

    Covers RFP development, evaluation criteria, and contract negotiation for health IT systems. Students score vendor proposals using a weighted evaluation matrix.

  • Lesson 4 • Change Management in Healthcare IT

    Applies structured change management models to EHR and informatics initiatives. Students create a stakeholder engagement plan for a major system transition.

  • Lesson 5 • Measuring IT Value and ROI

    Quantifies financial, clinical, and operational returns on health IT investments. Students build a business case with cost-benefit analysis for a proposed system.

Certification

Your valid completion certificate

This course is for you:

  • Registered nurses: seeking to transition into clinical informatics or EHR analyst roles.

  • Healthcare administrators: wanting to engage more confidently with IT teams and vendors.

  • Medical coders: looking to expand their expertise into data governance and standards.

  • IT professionals: moving into healthcare and needing domain-specific clinical knowledge.

  • Public health workers: aiming to apply informatics tools to population-level data challenges.

  • Recent health sciences graduates: building a competitive edge before entering the job market.

What our students say

Your classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to switch platforms... I thank you for everything you do, I've already recommended you to other people...
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Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can switch chapters and skip content I don't need.
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Mariana FerresPhotography Student
I like the content and the presentation style and video transcription, which speeds up the process!
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Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.
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