EHR Data Analytics & Population Health 5 — Questions and Answers
Question 1: Which term describes the use of EHR data to identify geographic clusters of patients with unusually high disease rates?
- Time-series analysis
- Spatial epidemiology (Correct answer)
- Longitudinal cohort tracking
- Propensity score matching
Correct answer: Spatial epidemiology
Spatial epidemiology maps disease occurrence geographically to detect clusters and identify environmental or social contributors to health disparities.
Question 2: In EHR analytics, 'data latency' refers to:
- The delay between data generation and its availability for analysis (Correct answer)
- Missing values in clinical data fields
- Encryption processing time for PHI
- The time needed to train a machine learning model
Correct answer: The delay between data generation and its availability for analysis
Data latency is the lag between when clinical events occur or are documented and when that data becomes queryable in analytics systems.
Question 3: A value-based care organization tracks the 'cost per member per month' (PMPM). What does this metric primarily measure?
- Revenue generated per patient visit
- Average total healthcare expenditure per enrolled member each month (Correct answer)
- Out-of-pocket costs paid by patients
- Pharmacy costs allocated to each provider
Correct answer: Average total healthcare expenditure per enrolled member each month
PMPM divides total healthcare costs by the number of enrolled members per month, providing a standardized measure of population-level spending.
Question 4: Which method is used in population health to evaluate whether two patient groups are comparable when randomization is not possible?
- Cluster sampling
- Propensity score matching (Correct answer)
- Monte Carlo simulation
- Stratified randomization
Correct answer: Propensity score matching
Propensity score matching uses predicted probability of group assignment to create comparable groups in observational studies, reducing selection bias.
Question 5: Which data governance practice ensures that the same clinical concept—such as 'blood pressure'—is defined and measured consistently across all EHR analytics reports?
- Data masking
- Common data model (CDM) adoption (Correct answer)
- Database sharding
- Record-level encryption
Correct answer: Common data model (CDM) adoption
Common data models like OMOP or PCORnet standardize how clinical concepts are defined and stored, ensuring consistent measurement across studies and reports.
Question 6: Which analytic technique segments a patient population into groups based on shared clinical and demographic characteristics without a predefined outcome label?
- Supervised classification
- Unsupervised clustering (Correct answer)
- Logistic regression
- Survival analysis
Correct answer: Unsupervised clustering
Unsupervised clustering algorithms (e.g., k-means) group patients by similarity without needing labeled outcomes, useful for discovering natural patient subpopulations.
Question 7: A health informatics team is building an alert to flag patients overdue for colorectal cancer screening. Which EHR component is the primary source for this logic?
- Billing claims database
- Clinical decision support (CDS) rule engine (Correct answer)
- Radiology PACS system
- Patient portal messaging module
Correct answer: Clinical decision support (CDS) rule engine
Clinical decision support rule engines process patient data against evidence-based criteria to generate timely, context-specific alerts and reminders.
EHR Data Analytics & Population Health 5
Which term describes the use of EHR data to identify geographic clusters of patients with unusually high disease rates?