Healthcare Information Systems and Data Analytics
What to know
Understand the EHR, its modules (CPOE, eMAR, clinical documentation, results viewing), and interoperability standards (HL7, FHIR, CCD). Know the difference between structured and unstructured data, data governance, and privacy/security safeguards under HIPAA. Grasp analytics tiers-descriptive, diagnostic, predictive, prescriptive-and common metrics (readmission rate, length of stay, HEDIS measures, risk-adjusted rates). Recognize the role of health information exchange and population health dashboards.
Traps
Questions often confuse CPOE (order entry) with eMAR (medication administration record). Another trap is treating raw counts as rates; rates require denominators. Do not assume predictive analytics establishes causation-it identifies associations. Watch for confusion between interoperability (systems exchanging data) and integration (systems unified under one platform).
Worked example
A hospital reports 150 readmissions out of 3,000 discharges. The readmission rate is 150 ÷ 3,000 = 5%. If a question asks whether this is high, risk adjustment and benchmark comparison are required. Rule of thumb: always check the denominator before interpreting a metric.
Review how data quality (completeness, accuracy, timeliness) affects analytics, since scenario questions test data reliability.