Healthcare generates vast amounts of data every day from electronic health records and lab systems to imaging, devices, and claims. If you’re looking to build analytics skills for healthcare, or eager to understand and work with healthcare data more effectively, this course is for you.
Foundations of Healthcare Data Analytics
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niveau Intermédiaire
Expérience recommandée
9 heures à compléter
Planning flexible
Apprenez à votre propre rythme
Ce que vous apprendrez
Describe the types and sources of healthcare data, including electronic health records, claims data, and clinical trial data.
Explain data privacy regulations (HIPAA) and best practices for secure healthcare data handling.
Apply data collection and cleaning techniques specific to healthcare datasets using Python, Excel, and SQL.
Generate descriptive statistics and data quality reports by integrating, cleaning, and validating healthcare data.
Compétences que vous acquerrez
- Catégorie : Spreadsheet Software
- Catégorie : Database Design
- Catégorie : Data Integration
- Catégorie : Health Informatics
- Catégorie : Relational Databases
- Catégorie : Data Preprocessing
- Catégorie : Descriptive Analytics
- Catégorie : Health Care Procedure and Regulation
- Catégorie : Data Literacy
- Catégorie : Health Insurance Portability And Accountability Act (HIPAA) Compliance
Détails à connaître
Certificat partageable
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Enseigné en Anglais
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Il y a 4 modules dans ce cours
In this module, you will learn about the fundamentals of healthcare data. The module begins with an overview of key data types, including electronic health records (EHRs), claims, registries, and clinical research data, and how they support decision-making and analytics across healthcare settings. You will explore healthcare data standards and classification systems, such as ICD, CPT, HL7, and FHIR, which ensure interoperability across systems. Through real-world examples, you will see how healthcare data flows from hospitals and clinics to research databases, enabling clinical, operational, and analytical insights. The module concludes with a discussion on how structured, standardized, and well-managed data contributes to improved patient care, efficient healthcare operations, and effective evidence-based decision-making.
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In this module, you will learn how to safeguard sensitive healthcare data. The module begins with an exploration of privacy, security, and compliance requirements, emphasizing the importance of ethical data handling and patient protection. You will examine global regulations, including HIPAA and GDPR, and understand their impact on healthcare operations. The module introduces practical data protection strategies such as encryption, anonymization, and access control, illustrated through real-world examples of data breaches and prevention measures. Through hands-on labs, you will apply these principles to securely manage healthcare data, maintain regulatory compliance, and build trust and accountability in healthcare analytics and decision-making.
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In this module, you will learn the technical skills needed to collect, organize, and prepare healthcare data for analysis. The module begins with importing data from multiple sources and building relational databases using Excel and SQL. You will practice essential data management techniques, including validation, cleaning, transformation, and standardization, to ensure data consistency and quality. Through real-world exercises, you will learn how to convert raw, inconsistent healthcare datasets into structured, reliable formats. By the end of this module, you will be able to prepare data that supports accurate reporting and evidence-based decision-making in healthcare.
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This module consolidates the knowledge and skills acquired throughout the course, guiding learners through a comprehensive, hands-on healthcare data analytics project. You will apply your understanding of healthcare data sources, privacy regulations, and data management techniques to solve a real-world healthcare analytics challenge. You will work with authentic healthcare datasets, demonstrating your ability to collect, clean, integrate, and analyze data while maintaining HIPAA compliance and ensuring data quality standards. Through structured problem-solving, you will demonstrate your competence in using Excel and SQL to generate meaningful insights from healthcare data, preparing yourself for entry-level roles in healthcare analytics.
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Foire Aux Questions
Yes! You’ll work with realistic, de-identified healthcare datasets that reflect common structures found in EHRs, claims files, and clinical registries. Through guided exercises, you’ll practice importing, cleaning, validating, and preparing data for analysis.
No. This course focuses on the fundamentals of healthcare data, not programming. Exercises are tool-based and step-by-step, using spreadsheets, query builders, and simple SQL snippets. No prior coding experience is required.
Privacy and data protection are core themes. You’ll learn how regulations like HIPAA and GDPR shape the handling of patient data, why concepts like PHI, access control, and de-identification matter, and how organizations safeguard sensitive information in real workflows.
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