Health Informatics Certification
Master the systems, standards, and data practices that power modern healthcare. This course covers electronic health records, healthcare data standards such as HL7 and FHIR, HIPAA privacy and security, clinical decision support, and the implementation work that turns health data into better patient care.
About This Course
Health informatics sits at the intersection of clinical care, information technology, and data science. This Intermediate-level certification course gives you a working understanding of how electronic health records, data standards, and analytics support safe, efficient, and equitable patient care across hospitals, clinics, and public health agencies.
Over 12 weeks (roughly 6 hours per week), you will move from the structure of the healthcare system and clinical workflows through interoperability standards such as HL7 v2, FHIR, ICD, and SNOMED CT, into privacy and security under HIPAA, clinical decision support, healthcare databases, population health, and quality reporting. The course closes with implementation, change management, and ethics, plus a capstone project where you scope a realistic informatics initiative end to end. No programming is required.
What You'll Learn
- Explain how clinical, administrative, and financial data flow through the healthcare system
- Navigate EHR/EMR systems and map their data to real clinical workflows
- Apply interoperability standards including HL7 v2, FHIR, ICD-10, and SNOMED CT
- Assess and apply HIPAA privacy and security requirements to health data
- Evaluate clinical decision support tools and their effect on care and alert fatigue
- Design and query healthcare databases and data warehouses for reporting
- Build quality measures and population health reports from clinical data
- Plan a system implementation using change management and ethical principles
Requirements
- A computer with internet access (Windows, Mac, or Linux)
- A background in healthcare or IT is helpful but not required
- No programming experience needed - standards and tools are taught from the ground up
- Comfort working with spreadsheets and basic data concepts
- Interest in how health data is created, exchanged, and protected
Who This Course Is For
- Clinicians and nurses moving into informatics or EHR-focused roles
- IT and software professionals entering the healthcare sector
- Health information management and HIM/RHIA candidates building informatics depth
- Analysts and project staff who work with clinical or claims data
- Public health and quality-improvement professionals who use health data
- Anyone preparing for a health informatics certification or career transition
Establish a shared vocabulary for health informatics and see how care delivery, reimbursement, and regulation shape the data you will work with.
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1.1 What Health Informatics Is and Why It Matters
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1.2 How the Healthcare System Is Organized and Paid
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1.3 Roles in Informatics: Clinical, Nursing, and Technical
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1.4 Types of Health Data: Clinical, Administrative, Claims
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1.5 Case Study: Mapping a Patient Journey to Data
Understand the structure of EHR and EMR systems and how documentation, orders, and results follow real clinical workflows.
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2.1 EHR vs EMR and Core System Components
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2.2 Clinical Documentation and the Problem List
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2.3 CPOE, Medication Orders, and Results Review
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2.4 Mapping and Optimizing Clinical Workflows
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2.5 Usability, Burnout, and Documentation Burden
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2.6 Case Study: Redesigning an Order Workflow
Work with the standards that let systems exchange and understand health data: HL7 v2 messaging, FHIR resources and APIs, and the ICD and SNOMED CT terminologies.
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3.1 Why Interoperability Is Hard
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3.2 HL7 v2 Messaging and ADT Feeds
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3.3 FHIR Resources, Profiles, and RESTful APIs
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3.4 Clinical Terminologies: ICD-10, SNOMED CT, LOINC, RxNorm
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3.5 Mapping, Coding, and Semantic vs Syntactic Interoperability
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3.6 Hands-On: Reading an HL7 Message and a FHIR Patient Resource
Learn the HIPAA Privacy and Security Rules, what counts as protected health information, and how organizations safeguard data and respond to breaches.
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4.1 HIPAA Overview and Protected Health Information (PHI)
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4.2 The Privacy Rule: Use, Disclosure, and Minimum Necessary
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4.3 The Security Rule: Administrative, Physical, Technical Safeguards
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4.4 De-identification, Breach Notification, and Business Associates
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4.5 Case Study: Investigating a Data Access Incident
Explore how clinical decision support (CDS) delivers alerts, order sets, and guidance at the point of care, and how to balance benefit against alert fatigue.
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5.1 What CDS Is and the Five Rights of CDS
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5.2 Alerts, Reminders, Order Sets, and Documentation Templates
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5.3 Knowledge Representation and Rule Logic
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5.4 Alert Fatigue, Governance, and AI-Assisted CDS
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5.5 Case Study: Tuning a Drug-Interaction Alert
See how clinical data is stored, modeled, and governed, from relational databases and clinical data warehouses to common data models and data quality practices.
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6.1 Relational Databases and Health Data Models
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6.2 Querying Clinical Data with SQL (No Prior Coding Needed)
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6.3 Clinical Data Warehouses and Common Data Models (OMOP)
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6.4 Data Quality, Governance, and Master Patient Index
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6.5 Hands-On: Building a Patient Cohort Query
Move from the individual patient to populations: registries, risk stratification, social determinants of health, and the systems used for disease surveillance and reporting.
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7.1 Population Health Management Fundamentals
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7.2 Patient Registries and Risk Stratification
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7.3 Social Determinants of Health and Health Equity Data
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7.4 Public Health Reporting, Surveillance, and Immunization Registries
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7.5 Case Study: Building a Diabetes Population Dashboard
Turn clinical data into quality metrics. Learn how measures are defined, calculated, and submitted for value-based care and regulatory programs.
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8.1 Quality, Safety, and Value-Based Care
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8.2 Electronic Clinical Quality Measures (eCQMs)
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8.3 Numerators, Denominators, and Measure Logic
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8.4 Dashboards, Benchmarking, and Reporting Programs
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8.5 Hands-On: Calculating a Preventive-Screening Measure
Plan and deliver an informatics initiative: project lifecycle, workflow redesign, training, go-live support, and the ethical questions raised by health data and algorithms.
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9.1 The System Implementation Lifecycle
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9.2 Stakeholders, Governance, and Requirements Gathering
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9.3 Change Management, Training, and Go-Live Support
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9.4 Ethics, Bias, and Responsible Use of Health Data and AI
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9.5 Measuring Adoption and Realizing Benefits
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9.6 Case Study: An EHR Optimization Rollout
Bring it all together by scoping a realistic informatics initiative end to end, from problem definition and data standards through privacy, workflow, measurement, and a final presentation.
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10.1 Choosing and Scoping Your Capstone
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10.2 Defining the Problem and Stakeholders
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10.3 Data, Standards, and Privacy Plan
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10.4 Workflow, Measurement, and Implementation Plan
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10.5 Preparing Your Final Deliverable
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10.6 Capstone Review and Certification
Dr. Priya Raghavan
Clinical Informaticist, RN, PhD, FAMIA
About the Instructor
Dr. Priya Raghavan is a board-certified clinical informaticist with more than 14 years of experience bridging nursing practice and health information technology. She holds a PhD in Health Informatics, is a registered nurse, and is a Fellow of the American Medical Informatics Association (FAMIA).
She has led EHR implementations and optimization programs at large academic medical centers, served as a clinical lead on FHIR-based interoperability projects, and built clinical decision support and quality-reporting pipelines used across multi-hospital systems. Her work focuses on reducing clinician documentation burden while improving data quality and patient safety.
Dr. Raghavan teaches health informatics at the graduate level and speaks regularly on interoperability, HIPAA, and responsible use of health data. She designed this course to give working professionals a practical, standards-grounded path into informatics roles.
Other Courses by Dr. Priya Raghavan
Monica Alvarez
As a bedside nurse moving into an informatics role, this was exactly the bridge I needed. The HL7 and FHIR module finally made interoperability click, and the HIPAA section was practical rather than just legal jargon. I went into my new job already understanding how the EHR connects to everything else.
James Okafor
I came from a software background with no healthcare experience, and the foundations and clinical workflow modules gave me the context I was missing. The SQL lessons were approachable even though I expected them to assume more. Four stars only because I would have liked more depth on FHIR profiling, but overall a strong, well-organized course.
Lena Hoffmann
The quality measurement and population health modules were the highlight for me. I work in quality improvement and now understand how eCQMs are actually built from the underlying data. The capstone forced me to tie privacy, workflow, and reporting together, which is the part most courses skip. Dr. Raghavan clearly knows the real-world side of this.
No. A background in healthcare or IT is helpful for context, but it is not required, and no programming experience is needed. Standards, terminologies, and even the basic SQL used in the data module are taught from the ground up. The course is designed for clinicians, IT professionals, and analysts alike.
The course is structured over 12 weeks at roughly 6 hours per week, which includes about 52 hours of video plus reading and case-study work. Because you have lifetime access, you can move faster or slower than that pace and revisit modules whenever you need a refresher.
Yes. After you complete all modules and submit the capstone project, you will receive a certificate of completion. You can add it to your LinkedIn profile or resume to demonstrate your health informatics knowledge to employers. Note that this certificate is not a substitute for board certifications such as those offered by AMIA or AHIMA.
It builds a strong foundation across the domains covered by recognized credentials, including EHR systems, interoperability standards, HIPAA, clinical decision support, data management, and quality reporting. While it is not an official exam-prep program, many learners use it to strengthen their understanding before pursuing certifications offered by professional bodies.
No. All exercises use de-identified sample data, example HL7 messages and FHIR resources, and provided datasets, so you never work with real protected health information. You can complete every hands-on activity with the materials included in the course.
Yes. The course includes a Q&A discussion board where you can ask questions and get help from the instructor and fellow learners. Dr. Raghavan and the teaching team typically respond within 24-48 hours, and there is a community space for connecting with other students working in healthcare and IT.
Yes. Standards such as FHIR, terminologies, and reporting programs evolve, so we update the material to reflect current versions and regulatory expectations. When significant changes are released you will be notified by email, and you have access to all future updates at no additional cost.
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