Healthcare Analytics Practice Exam
Healthcare Analytics Practice Exam
About Healthcare Analytics Exam
The Healthcare Analytics Exam is designed to assess a candidate’s proficiency in using data and analytics to drive better healthcare outcomes. It evaluates skills in healthcare data management, predictive analytics, reporting tools, cost and quality analysis, and regulatory compliance. Candidates will gain exposure to key analytical methods and technologies used in hospitals, insurance companies, public health agencies, and healthcare startups. This exam is ideal for professionals who want to bridge the gap between clinical operations and data-driven decision-making.
Who should take the Exam?
This exam is ideal for:
- Healthcare data analysts and business intelligence professionals
- Clinical informatics specialists and medical data managers
- Public health professionals and policy analysts
- Hospital administrators and quality improvement staff
- IT professionals working in healthcare software or EMR systems
Skills Required
- Knowledge of healthcare data structures and terminologies
- Proficiency in SQL, Excel, and visualization tools like Power BI or Tableau
- Understanding of statistical and predictive modeling techniques
- Familiarity with healthcare compliance and data privacy regulations
- Ability to translate data insights into actionable healthcare improvements
Knowledge Gained
- Ability to work with clinical, operational, and financial healthcare data
- Insight into improving patient outcomes through data-driven decisions
- Expertise in using dashboards and KPIs for monitoring hospital performance
- Understanding of risk prediction, readmission analytics, and population health
- Skills to ensure data security and regulatory adherence in healthcare environments
Course Outline
The Healthcare Analytics Exam covers the following topics -
Domain 1 – Introduction to Healthcare Analytics
- Scope and importance of analytics in healthcare
- Types of healthcare data: clinical, operational, financial
- Challenges and opportunities in healthcare data analysis
Domain 2 – Healthcare Data Standards and Systems
- EMR/EHR systems and data integration
- HL7, ICD, CPT, SNOMED, and LOINC standards
- Data interoperability and exchange frameworks
Domain 3 – Data Preparation and Cleaning
- Data extraction, transformation, and loading (ETL)
- Handling missing data, duplicates, and data normalization
- Data governance and data quality assurance
Domain 4 – Descriptive and Diagnostic Analytics
- Use of dashboards, reports, and summary statistics
- Analyzing patient trends, service utilization, and treatment costs
- Identifying causes of readmissions and care gaps
Domain 5 – Predictive and Prescriptive Analytics
- Using regression, classification, and time-series models
- Predicting disease outbreaks, readmissions, and high-risk patients
- Optimization for resource allocation and scheduling
Domain 6 – Population Health Analytics
- Segmenting populations for chronic care management
- Tracking health outcomes and disparities across groups
- Utilizing social determinants of health (SDOH) in analysis
Domain 7 – Cost and Quality Analysis
- Benchmarking against national quality indicators
- Identifying cost drivers and reducing unnecessary expenses
- Analyzing performance metrics like LOS, HCAHPS, and readmissions
Domain 8 – Data Visualization and Reporting
- Creating interactive dashboards using Power BI, Tableau, or Qlik
- Designing executive-level reports and visual summaries
- Effective storytelling with healthcare data
Domain 9 – Regulatory Compliance and Data Privacy
- HIPAA, HITECH, and GDPR in healthcare analytics
- De-identification and secure data handling practices
- Auditing and governance frameworks
Domain 10 – Real-World Applications of Healthcare Analytics
- Case studies in hospitals, insurance firms, and public health systems
- Applications in telehealth, patient engagement, and care coordination
- Role of AI and machine learning in modern analytics
