Data Analytics & Population Health Flashcards
7 cards from real Clinical Informatics Certification practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Data Analytics & Population Health flashcards as text
In value-based care analytics, which metric directly measures the cost-effectiveness of care delivered to a population over time?
Answer: Total cost of care per member per month (PMPM)
Total cost of care PMPM is the primary financial metric in value-based contracts, capturing all healthcare expenditures attributed to a defined population.
A clinical informaticist reviews a natural language processing (NLP) output that extracted smoking status from clinical notes. Which validation step is most critical?
Answer: Measuring precision and recall against a manually annotated gold standard
Comparing NLP output against a manually labeled gold standard dataset measures precision (accuracy of extractions) and recall (completeness), validating clinical utility.
Which population stratification approach assigns patients to tiers based on predicted future healthcare utilization and clinical complexity?
Answer: Risk-based segmentation
Risk-based segmentation uses predictive models to classify patients into tiers by expected care needs and costs, enabling prioritized care management resources.
What does 'data linkage' mean in population health research?
Answer: Joining records about the same individual from multiple disparate data sources
Data linkage combines records from different data sources — such as EHR, claims, registries, and social services — that pertain to the same individual to create a comprehensive view.
A health system is implementing a clinical decision support rule to flag patients with eGFR < 30 who are prescribed NSAIDs. This is an example of:
Answer: Real-time alert-based CDS
Real-time alert-based CDS triggers at the point of care — during prescribing — to warn clinicians about contraindicated medications based on current patient data.
Which approach is most effective for reducing missing data bias in a population health analytics study?
Answer: Multiple imputation using observed data patterns
Multiple imputation generates plausible values for missing data based on observed relationships, reducing bias and preserving sample size compared to complete case analysis.
In population health, what does the concept of 'attributable risk' measure?
Answer: The proportion of disease in the exposed group attributable to the exposure
Attributable risk (risk difference) quantifies the excess risk of disease in exposed individuals that is due to the exposure itself, beyond background risk.