BSAN 160 - Activities and Quiz Questions
Which of the following statement describes the key take away points of Analytics Applications in Healthcare - Humana Example 1?
a) Humana's prevention efforts aim to treat all injuries after a fall more efficiently.
b) As a strategy to enhance well-be...
BSAN 160 - Activities and Quiz
Questions
Which of the following statement describes the key take away points of Analytics
Applications in Healthcare - Humana Example 1?
a) Humana's prevention efforts aim to treat all injuries after a fall more efficiently.
b) As a strategy to enhance well-being of its members, Humana promotes increased
utilization of physical therapy as a better alternative than investing in high-cost
analytics.
c) Using analytics can reduce healthcare costs by identifying subgroups of Humana
members that are at high risk of falling and managing their fall risk.
d) For Humana members, cost of treatment and recovery are less expensive than
preventative measures. - Answer- c) Using analytics can reduce healthcare costs by
identifying subgroups of Humana members that are at high risk of falling and
managing their fall risk.
According to Humana Example 1, and the article by Gates et al. (2008), many risk
assessment methods, such as screening tools to identify fall risk factors, already
exist. In your own words, give two reasons to why your team should not use one of
the existing risk assessment methods? - Answer- · Existing models have limited
reach - Different test attributes may be needed to predict falls successfully in
different populations; for example, the timescale over which a prediction is needed
varies from a few days or weeks in hospitalized patients to a year or more for
community-living populations. Tools developed for one population may therefore be
less accurate when used in a different setting.
· Lack sufficient predictive power - not based on sound evidence that they are useful
in discriminating between people who will fall and those who will not.
Which methods would your team use to forecast the risk factors that are most likely
to result in a newly enrolled senior member's fall at home using existing Humana
members' data?
a) Descriptive analytics methods
b) Central tendency methods
c) Predictive analytics methods
d) Prescriptive analytics methods - Answer- c) Predictive analytics methods
According to the Humana Example 3 (Section 1.6, Pg. 32-33), which data source(s)
mentioned in the example can be used to identify the patterns of risk factors that
increase an individual's risk of falling?
a) A: Medical claims
b) B: Self-reported health risk assessment data
c) C: Pharmacy data
d) A, B, and C - Answer- d) A, B, and C
,Congratulations! The model your team developed to identify the factors that increase
the risk of a senior individual to fall at home and experience an injury was well
received by the upper-level management. Now, your team is tasked with turning this
predictive model to a prescriptive analytics model. Which of the below action would
make your analytics model a prescriptive model?
a) Create a data visualization tool that shows the fall risk distribution of Humana
members
b) Identify at-risk members soon after their enrollment and offer those individuals
devices and services that detect risk factors to prevent falls at home
c) Describe the variation in fall risk of Humana members to better understand low
and high risk levels
d) Predict the top 5% highest risk members within the newly enrolled member
population - Answer- b) Identify at-risk members soon after their enrollment and offer
those individuals devices and services that detect risk factors to prevent falls at
home
________ analytics help managers understand what is happening in the organization
by analyzing trends and patterns in data.
a) Descriptive
b) Predictive
c) Prescriptive
d) Data warehouse - Answer- a) Descriptive
Is the following statement true or false?
"Decision support system are computer-based support systems that have precise
definitions agreed to by practitioners."
True
False - Answer- False
What type of analytics seeks to forecast the future/unknown values of outcomes of
interest using past and current available data?
a) descriptive
b) predictive
c) prescriptive
d) domain - Answer- b) predictive
Using characteristics of first year undergraduate students, such as age, gender,
major, location, workout/sports activities, if we developed a model to forecast which
students are at risk of dropping out after the first year of college, decided which
students to reach out to and offered them support services to reduce their risk of
dropping out, what kind of analytics application would this work represent?
a) descriptive analytics
b) data warehouse analytics
c) prescriptive analytics
d) predictive analytics - Answer- c) prescriptive analytics
, Figure 1 shows the Annual Salary distribution (histogram) at Department 1. Figure 2
shows Annual Salary distribution (histogram) at Department 2. Which of the following
statement(s) is/are correct?
Figure 1. Annual salary histogram for Department 1.
Figure 2. Annual salary histogram for Department 2.
A: Annual salary values are more spread out at Department 2 compared with
Department 1.
B: At Department 1, there are some outlier (extreme) salary values, e.g., there are a
few employees that make a lot more than the majority of other employees
C: At Department 2, the annual salary is symmetrically distributed with zero
skewness.
A and B - Answer- A: Annual salary values are more spread out at Department 2
compared with Department 1.
Julie Miller, a manager at the health tech company, Wellness Path, oversees two
departments in the wearables business line: Product Development (referred as
Department 1), and Product Testing (referred as Department 2). Both departments
focus on bringing impactful products to the market that provide competitive
advantage due to their design features and interoperability with other devices. Table
1 below shows selected descriptive statistics for age in Department 1 and
Department 2. Table 1. Selected descriptive statistics of age at Department 1 (left)
and Department 2 (right).
(a) Department 2 has a larger spread with regards to age compared to Department
1.
(b) Age distribution at Department 1 is negatively skewed
(c) Age distribution at Department 2 is negatively skewed
(d) 95% of the age values at Department 1 are between the ages 29 and 41 -
Answer- (c) Age distribution at Department 2 is negatively skewed
Employees of both departments were asked the following question: " On a scale
from 0 (worst value) to 10 (best value), how would you rate your job satisfaction at
your current work position?" Results are shown in Figure 3. Which of the following
statement is correct?
Figure 3. Boxplots of job satisfaction for Departments 1 and 2 where 0 is the worst
possible satisfaction value and 10 is the best satisfaction value.
A. At Department 1, 25 % of all job satisfaction observations are below 2
B. At Department 1, 75% of all job satisfaction observations are below 4
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