Healthcare Analyst Data Analysis & Interpretation Flashcards

A healthcare analyst observes that hospital readmission rates spike every January. Which analytical approach best determines if this is a seasonal pattern versus random variation?

Answer: Apply time-series decomposition to isolate seasonal components

Time-series decomposition separates trend, seasonal, and residual components, directly identifying recurring seasonal patterns.

When analyzing a dataset with a heavily right-skewed distribution of patient lengths of stay, which measure of central tendency best represents a 'typical' patient stay?

Answer: Median

The median is resistant to extreme high values (outliers) that cause right skew, making it the most representative measure for skewed distributions.

A hospital wants to predict 30-day readmissions using age, comorbidity count, and discharge disposition. Which model type is most appropriate?

Answer: Logistic regression

Logistic regression is designed for binary outcomes (readmitted vs. not readmitted) and produces probability estimates.

An analyst finds a Pearson correlation of r = 0.85 between hospital staffing ratios and patient satisfaction scores. What is the most accurate interpretation?

Answer: There is a strong positive linear association between the two variables

Correlation measures the strength and direction of linear association; r = 0.85 indicates a strong positive relationship but does not imply causation.

A healthcare analyst is tasked with identifying patient subgroups with similar utilization patterns without predefined categories. Which technique is most suitable?

Answer: K-means clustering

K-means clustering is an unsupervised method that groups observations by similarity without requiring predefined outcome labels.

In a clinical dataset, an analyst notices that 15% of BMI values are missing. The missing values appear to be concentrated among patients over age 80. This pattern is best described as:

Answer: Missing at random (MAR)

MAR means the probability of missingness depends on observed variables (age), not on the missing value itself.

A healthcare analyst compares average cost per discharge across five hospital departments using one-way ANOVA and finds F = 4.2, p = 0.003. What is the correct next step?

Answer: Perform post-hoc pairwise comparisons to identify which departments differ

ANOVA only signals that at least one mean differs; post-hoc tests (e.g., Tukey's HSD) are needed to identify which specific pairs differ.