Knowing how to write a SQL statement is no longer enough to succeed in health informatics. AI can generate the syntax - but it cannot tell you whether the answer is correct. That requires domain expertise - and this book builds it. Healthcare Analytics: Comprehensive Guide is the definitive desk reference for data professionals working in managed care, health plans, and population health programs. With 31 chapters and over 100 real-world analytics scenarios, it bridges the critical gap between programming syntax and the deep domain knowledge required to produce results that actually hold up in front of a CFO, a quality director, or a CMS auditor. Structured around the STAR methodology (Situation, Task, Action, Result), every scenario teaches not just how to write the query - but why the data looks the way it does, what the business rule actually requires, and what the number means to the organization. What you will master:
Claims and Enrollment Fundamentals - Inpatient vs. outpatient billing, claim adjudication gates, member months, coordination of benefits, continuous enrollment logic, voids and reversals. Quality and Population Health - HEDIS measure construction from denominator to rate, CMS Star Ratings end-to-end pipeline, 30-day readmission prevention, and risk stratification models that identify rising-risk populations before costs escalate. Risk Adjustment and Regulatory Compliance - CMS-HCC RAF score calculation, RAPS/EDPS encounter submission, retroactive payment cycles, and RADV audit preparation. Financial and Network Analytics - PMPM medical cost trend decomposition, MLR calculation, Value-Based Care shared savings, fee schedule analysis, and out-of-network leakage detection. Advanced Domain Analytics - Pharmacy adherence (PDC), PBM spread pricing detection, oncology cost decomposition, maternal care episodes, and behavioral health parity analytics. Data Architecture and Advanced SQL - Star schema design, SCD Type 2 joins, claims lag management, window functions, recursive hierarchies, and query optimization for enterprise-scale datasets.
Every chapter closes with key takeaways and a unit test - multiple choice and short answer - so you can immediately verify your mastery of both the business rules and the SQL logic required to execute them. This guide gives you the framework, the logic, and the confidence to turn raw claims data into defensible, actionable answers
