HAC Risk Stratification & Care Management Analytics Flashcards
6 cards from real HAC practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 HAC Risk Stratification & Care Management Analytics flashcards as text
Social determinants of health (SDOH) data are increasingly incorporated into risk stratification models because:
Answer: Non-clinical factors like housing instability and food insecurity independently predict poor health outcomes and utilization
Research consistently shows that social factors such as food insecurity, housing, and transportation barriers are strong independent predictors of health outcomes.
What is the purpose of a 'propensity score' in healthcare program evaluation analytics?
Answer: To statistically balance comparison groups in observational studies to reduce selection bias when measuring program impact
Propensity scoring estimates the probability that a subject receives a treatment given observed covariates, enabling fairer comparison between intervention and control groups.
Which utilization management metric measures the proportion of inpatient admissions that were potentially avoidable through better outpatient or preventive care?
Answer: Ambulatory care sensitive condition (ACSC) admission rate
ACSC admission rates track hospitalizations for conditions like uncontrolled diabetes or asthma that good outpatient care should prevent, serving as a proxy for care management effectiveness.
In transitional care analytics, what does a high '30-day post-discharge ED visit rate' typically signal?
Answer: Gaps in discharge planning, medication reconciliation, or outpatient follow-up that leave patients vulnerable after leaving the hospital
Frequent ED visits shortly after discharge indicate that patients' needs are not being adequately managed in the community, often due to poor care transition processes.
A risk stratification model has high sensitivity but low specificity. What does this mean for care management resource allocation?
Answer: It catches most truly high-risk patients but also flags many low-risk patients, leading to inefficient use of care management resources
High sensitivity ensures few high-risk patients are missed, but low specificity means many low-risk patients are also flagged, diluting care management resources across unnecessary enrollments.
Which analytical method is MOST appropriate for identifying clusters of patients with similar chronic disease patterns and utilization behaviors?
Answer: K-means clustering
K-means clustering partitions patients into groups with similar characteristics without predefined labels, making it ideal for discovering natural subpopulations.