NurseHack4Health™ Innovation Academy Post Test
Participant Disclosure: This nursing education activity was approved by the Pennsylvania State Nursing Association, an accredited approver by the American Nurses Credentialing Center’s Commission on Accreditation. To obtain 2 contact hours for this activity, learners must complete a post-test with a score of 80% or greater.
Name
First Name
Last Name
Email
example@example.com
_______ is the application or creation of something new or different that delivers value. (select the correct word to fit the sentence)
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Technology
Education
Innovation
Methodology
Creativity
Innovation Process = Nursing Process
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True
False
What is the first step to creating a problem statement?
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Defining the problem
Prototyping a solution
Test a Solution
Identify a Solution
Empathy is what nurses do best
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True
False
What are the components of the Empathy Map?
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Thinks
Says
User
Feels
All the above
What process follows the Define stage?
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Inspire
Ideate
Collaborate
Create
_______ allows designers to test the feasibility of their innovation. (select the correct word to fit the sentence)
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Hope
Collaborate
Create
Prototype
What are the 4-Hs that are covered in this training module?
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How, Help, Hope, Harmony
Headline, How, Heart, Hope
Headline, Heart, Head, Hope
None of the Above
Storytelling allows you to talk WITH people rather than talk to people.
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True
False
What is a component of HEADLINE?
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Very very long
Very very short
Set the context
None of the Above
What is a component of HEART?
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Set the context
Problem articulation
Business Plan
None of the Above
A minimal viable product (MVP) is the minimum set of functionalities that allows you to validate your product idea and assumptions with real customers.
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True
False
What is a component of HEAD?
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Set the context
Scalability
Business Plan
MVP
What is a component of HOPE?
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The BIG close
Scalability
Business Plan
None of the above
What is the most important thing to remember?
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Hope
Practice
Jump for joy
Give up
Which of the following are roles of nurses in incorporating AI into the healthcare setting?
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Providing date for AI algorithms through patient care documentation
Assisting in the development and refinement of AI tools
Educating patients about AI technologies and their potential impact
Collaborating with interdisciplinary teams to integrate AI solutions
All the above
AI is an area of computer science that emphasizes the creation of machines that work and react like humans, including learning, speech, problem-solving, vision, and knowledge generation.
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True
False
What is the difference between AI and Machine Learning?
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AI is a subset of machine learning, focusing on narrow tasks.
Machine learning is a subset of AI, focusing on the ability of machines to learn from data.
There is no difference; they are just two terms for the same concept.
Machine learning refers to the skills of robots, while AI refers to their ability to play chess.
What are some of the key areas for AI in healthcare?
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Predictive analytics in patient care
Automated administrative tasks
Personalized patient experience
Drug discovery and development
All the above
Some of the key areas for AI in healthcare include predictive care guidance, behavioral analytics, population health, medical image intelligence, telehealth, rules-based monitoring, anomaly detection, network analysis, text analysis, visual analytics, readmissions management, cost management, staffing management, throughput management, and claims management.
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True
False
What are some of the challenges and risks associated with AI in healthcare?
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Some of the challenges and risks associated with AI in healthcare include exacerbating societal biases, loss of jobs requiring training for new skills, and lack of regulatory oversight.
Challenges and risks associated with AI in healthcare primarily involve improved patient outcomes due to increased accuracy in diagnosis.
The only significant risk associated with AI in healthcare is an increase in healthcare costs due to expensive technology.
Risks related to AI in healthcare are negligible as it has been proven that AI can work without any errors or biases.
Some of the ethical questions that need to be considered when using AI in healthcare include thoroughly stress testing AI for unintended biases, effectively identifying and managing the ethical implications of technology, explaining how the AI makes decisions using data, and adhering to the fundamental principles of managing AI in an ethical way.
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True
False
What are some of the critical success factors for AI integration in healthcare?
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Multidisciplinary team management
Change management approach
Culture, partnering with AI experts
Workflow/ Project identification
All the above
Please verify that you are human
*
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