Population Health Reference Series
The Population Health
Bible for Healthcare
Professionals
Volume I — Interactive Table of Contents
2
Parts
9
Chapters
54
Sections
596
Pages
I
Ch. 1
▾
1.1Population health vs public health vs population medicine›
1.2Why the denominator matters — attribution, empanelment, membership logic›
1.3Outcomes and distribution — variation, disparities, and equity gradients›
1.4Prevention across the continuum — primary, secondary, tertiary, and quaternary›
1.5Population health as an operating discipline, not a department›
1.6Common failure modes — pilot culture, fragmented workflows, unclear ownership›
Ch. 2
▾
2.1Why voluntarism failed — adverse selection and uneven participation›
2.2The “hard” era — mandated accountability, tighter margins, fewer escape routes›
2.3Mixed economy constraints — risk contracts layered on a fee-for-service chassis›
2.4Workforce scarcity as a design constraint — care redesign becomes mandatory›
2.5Technology dependence — analytics, automation, and governance as survival tools›
2.6What changes for leaders — from program management to fiduciary discipline›
Ch. 3
▾
3.1Equity vs equality — measurement, interpretation, and action thresholds›
3.2Structural determinants and institutional accountability›
3.3Allocation ethics — prioritization, rationing, and fairness in resource scarcity›
3.4Consent, privacy, trust, and community legitimacy›
3.5Algorithmic ethics — bias, transparency, explainability, and liability›
3.6Practical ethics for leaders — tradeoffs, documentation, and governance›
Ch. 4
▾
4.1Health systems as complex adaptive systems›
4.2Feedback loops and unintended consequences — reinforcing and balancing dynamics›
4.3Theories of change — causal pathway mapping, logic models that survive reality›
4.4Constraints and bottlenecks — throughput, access, staffing, and network capacity›
4.5Continuous improvement as infrastructure — reliability science and PDSA›
4.6Learning health systems — measurement to action to redesign cycles›
II
Ch. 5
▾
5.1Measures of frequency and association — incidence, prevalence, risk ratios›
5.2Study designs and what they can claim — causal caution for leaders›
5.3Confounding, selection bias, information bias — real-world pitfalls›
5.4Screening science — sensitivity, specificity, predictive values, thresholds›
5.5Population attributable risk and prioritization for action›
5.6Translating evidence into operations — what changes on Monday morning›
Ch. 6
▾
6.1Outcomes, processes, balancing measures — and what to avoid›
6.2Stratification and subgroup reporting — race, ethnicity, geography, payer, risk›
6.3Composite indices and weighting — interpretability and gaming risk›
6.4Patient-reported outcomes and experience measures in operating models›
6.5Measurement governance — definitions, dictionaries, audit trails›
6.6From reporting to control systems — cadence, huddles, escalation, and accountability›
Ch. 7
▾
7.1Risk adjustment fundamentals — why it helps and where it misleads›
7.2Clinical segmentation — chronic disease, frailty, multimorbidity›
7.3Utilization-based segmentation — high-cost, high-need, rising-risk identification›
7.4Social and behavioral risk signals — documentation, validity, equity implications›
7.5Predictive models vs rules-based segmentation — the actionability test›
7.6Segment-to-intervention mapping — designing strata around services that exist›
Ch. 8
▾
8.1Total cost of care vs margins — why savings do not equal sustainability›
8.2The sustainability paradox — outcome goals funded by activity-based billing›
8.3Incentives and timing — delayed savings, attribution ambiguity, benchmarks›
8.4ROI categories — utilization avoidance, quality bonuses, coding uplift, leakage control›
8.5Portfolio management — stage gates, stop rules, and “kill criteria” for programs›
8.6Building CFO-grade business cases — sensitivity analysis and implementation cost realism›
Ch. 9
▾
9.1Claims data — lag, completeness, and the limits of retrospective truth›
9.2EHR data — documentation bias, coding behavior, workflow artifacts›
9.3Data quality operations — stewardship, lineage, validation, exception handling›
9.4Interoperability as workflow, not interface — reducing swivel-chair failure›
9.5National exchange and standards — TEFCA rails, FHIR write-back concepts›
9.6Data governance — access controls, privacy, minimum necessary, audit readiness›
A
Population Health Measurement and Analytics
Appendix
Comprehensive reference for measurement frameworks, analytic methods, and operational tools discussed throughout the volume. Includes worked examples, data templates, and decision-support matrices for population health teams.
Page 562
Glossary of Key Terms
Glossary
Authoritative definitions for clinical, epidemiological, financial, and operational terminology used across all nine chapters. Designed for rapid reference during leadership meetings, contract negotiations, and program design sessions.
Page 591
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