1. Which of the following is a key component of evidence-based practice in nursing?
a) Personal experience
b) Clinical expertise
c) Research evidence
d) Institutional protocols
Answer: c) Research evidence
2. What is the primary purpose of predictive analytics in healthcare?
,a) To increase patient satisfaction
b) To manage hospital budgets
c) To forecast patient outcomes and improve care
d) To streamline administrative tasks
Answer: c) To forecast patient outcomes and improve care
3. Which statistical method is commonly used to determine the likelihood of a
specific outcome based on historical data?
a) Chi-square test
b) Regression analysis
c) ANOVA
d) Descriptive statistics
Answer: b) Regression analysis
4. In the context of risk assessment in nursing, what does a Receiver Operating
Characteristic (ROC) curve measure?
a) The accuracy of a predictive model
b) The correlation between two variables
c) The distribution of patient demographics
d) The frequency of adverse events
Answer: a) The accuracy of a predictive model
5. What is one of the main benefits of integrating predictive analytics into patient
care?
a) Reducing the need for ongoing staff training
b) Enhancing the ability to personalize treatment plans
,c) Minimizing the need for electronic health records
d) Increasing the number of administrative tasks
Answer: b) Enhancing the ability to personalize treatment plans
6. Which type of data is most useful for developing predictive models in healthcare?
a) Qualitative data
b) Historical clinical data
c) Administrative data
d) Social media data
Answer: b) Historical clinical data
7. In predictive modeling, what does the term "sensitivity" refer to?
a) The ability to correctly identify patients who do not have the condition
b) The ability to correctly identify patients who have the condition
c) The proportion of true negatives among all negatives
d) The likelihood of a false positive result
Answer: b) The ability to correctly identify patients who have the condition
8. Which of the following is a common challenge when implementing predictive
analytics in healthcare?
a) Overestimating the benefits of predictive models
b) Ensuring data privacy and security
c) Reducing the volume of data collected
d) Simplifying data collection methods
Answer: b) Ensuring data privacy and security
, 9. What role does machine learning play in predictive analytics?
a) It replaces the need for human expertise
b) It automates data collection processes
c) It improves the accuracy of predictions by learning from data
d) It eliminates the need for statistical analysis
Answer: c) It improves the accuracy of predictions by learning from data
10. Which of the following is an example of a predictive tool used in healthcare?
a) Electronic health record (EHR) system
b) Risk prediction algorithms
c) Patient satisfaction surveys
d) Clinical guidelines
Answer: b) Risk prediction algorithms11. What is the primary objective of risk
stratification in healthcare?
a) To categorize patients based on their risk for adverse outcomes
b) To reduce healthcare costs
c) To increase the number of hospital admissions
d) To standardize treatment protocols
Answer: a) To categorize patients based on their risk for adverse outcomes
12. Which of the following is a common method for validating a predictive model?
a) Cross-validation
b) Focus groups
c) Benchmarking
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