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 clinical analytics, what is the purpose of propensity score matching?
Answer: To reduce confounding in observational studies by balancing covariates between groups
Propensity score matching balances baseline characteristics between treatment and control groups in observational data, reducing confounding bias.
Which type of analysis examines the relationship between two continuous clinical variables, such as BMI and fasting glucose levels?
Answer: Pearson correlation
Pearson correlation measures the strength and direction of the linear relationship between two continuous variables.
A health system wants to identify patients at high risk for developing heart failure in the next 12 months. Which analytical approach is most appropriate?
Answer: Predictive modeling using machine learning
Predictive modeling uses historical clinical and claims data with machine learning algorithms to forecast future health events such as heart failure development.
What is the key distinction between a data warehouse and a data lake in healthcare analytics?
Answer: A data warehouse contains structured, processed data; a data lake stores raw data in any format
Data warehouses store structured, pre-processed data optimized for querying, while data lakes store raw data in its native format including unstructured and semi-structured data.
Which measure is used to evaluate screening test performance by combining sensitivity and specificity into a single metric?
Answer: F1 score
The F1 score is the harmonic mean of precision (PPV) and sensitivity (recall), providing a single metric that balances both dimensions of test performance.
When analyzing population health data for a Medicaid managed care organization, which denominator should be used to calculate a utilization rate?
Answer: Number of eligible member months
Member months represent the total time members were enrolled and are the standard denominator for utilization rates in managed care population analytics.
What is a key limitation of using ICD-10 diagnosis codes from claims data for population health surveillance?
Answer: Diagnosis codes may reflect billing intent rather than true clinical status
Claims-based diagnoses can be influenced by billing optimization practices, potentially misrepresenting actual clinical conditions in population-level analyses.