Question 1

The process of knowledge discovery and data mining is best characterized as:

Accepted Answer

A)  machine learning, use of statistical methods, and large amounts of data. 
B)  a process wherein patients are selected for clinical trials. 
C)  "fishing" for information in data. 
D)  cleaning data for further analysis using other methods. 
A)  machine learning, use of statistical methods, and large amounts of data. 
B)  a process wherein patients are selected for clinical trials. 
C)  "fishing" for information in data. 
D)  cleaning data for further analysis using other methods. A

Question 2

In a set of consistently coded clinical data, the data should be analyzed using descriptive statistics and visualization with respect to the following: (Select all that apply.)

Accepted Answer

A)  Distribution 
B)  Arcing 
C)  Sparsity 
D)  Identifiers 
E)  Outliers 
A)  Distribution 
B)  Arcing 
C)  Sparsity 
D)  Identifiers 
E)  Outliers A, C, D, E

Question 3

As organizations mature over time in their use of data science, they progress from what to what?

Accepted Answer

A)  Retrospective analysis; exploratory data analyses 
B)  Real-time analytics; retrospective analytics 
C)  Exploratory data analyses; prescriptive analytics 
D)  Data mining; knowledge discovery 
A)  Retrospective analysis; exploratory data analyses 
B)  Real-time analytics; retrospective analytics 
C)  Exploratory data analyses; prescriptive analytics 
D)  Data mining; knowledge discovery C

Question 4

Which of the following are examples of analytics tools? (Select all that apply.)

Accepted Answer

A)  Graphics programs like Photoshop and 3DS Max 
B)  Spreadsheets like MS Excel 
C)  Database management systems like SQL Server 
D)  Statistical analysis programs like Rapidminer 
E)  Programming languages like R or Python 
A)  Graphics programs like Photoshop and 3DS Max 
B)  Spreadsheets like MS Excel 
C)  Database management systems like SQL Server 
D)  Statistical analysis programs like Rapidminer 
E)  Programming languages like R or Python

Question 5

Assigning individual records or rows in a dataset for specific purposes (eg, model development, model validation) is a process known as:

Accepted Answer

A)  partitioning. 
B)  sampling. 
C)  data mining. 
D)  Bayesian networking. 
A)  partitioning. 
B)  sampling. 
C)  data mining. 
D)  Bayesian networking.

Question 6

Which methods are examples of data mining? (Select all that apply.)

Accepted Answer

A)  Decision trees 
B)  Stratified random sampling 
C)  Bayesian networks 
D)  Artificial neural networks 
E)  Factor analysis 
A)  Decision trees 
B)  Stratified random sampling 
C)  Bayesian networks 
D)  Artificial neural networks 
E)  Factor analysis

Question 7

Which specialized method is used in knowledge discovery and data mining?

Accepted Answer

A)  Stratified sampling 
B)  Conceptual analytic methods 
C)  Selection of the optimal subset of variables/features for use in modeling 
D)  Machine learning 
A)  Stratified sampling 
B)  Conceptual analytic methods 
C)  Selection of the optimal subset of variables/features for use in modeling 
D)  Machine learning

Question 8

Which measure is most important for evaluating the performance of classifiers, models that predict class membership?

Accepted Answer

A)  Root mean squared error (RMS
E)  
B)  Area under the receiver operating characteristic (RO
C)  curve 
C)  Percentage of correctly classified cases 
D)  Hosmer-Lemeshow statistic 
A)  Root mean squared error (RMS
E)  
B)  Area under the receiver operating characteristic (RO
C)  curve 
C)  Percentage of correctly classified cases 
D)  Hosmer-Lemeshow statistic

Question 9

A health analytics professional must be skilled in all of the following except:

Accepted Answer

A)  computer hacking. 
B)  healthcare operations. 
C)  management and economics. 
D)  statistical understanding. 
A)  computer hacking. 
B)  healthcare operations. 
C)  management and economics. 
D)  statistical understanding.

Question 10

Which of the following data characteristics are important in understanding big data in healthcare? (Select all that apply.)

Accepted Answer

A)  Variety 
B)  Vagrancy 
C)  Venality 
D)  Velocity 
E)  Volume 
A)  Variety 
B)  Vagrancy 
C)  Venality 
D)  Velocity 
E)  Volume

Exam 23: Data Science and Analytics in Healthcare

The process of knowledge discovery and data mining is best characterized as:

In a set of consistently coded clinical data, the data should be analyzed using descriptive statistics and visualization with respect to the following: (Select all that apply.)

As organizations mature over time in their use of data science, they progress from what to what?

Which of the following are examples of analytics tools? (Select all that apply.)

Assigning individual records or rows in a dataset for specific purposes (eg, model development, model validation) is a process known as:

Which methods are examples of data mining? (Select all that apply.)

Which specialized method is used in knowledge discovery and data mining?

Which measure is most important for evaluating the performance of classifiers, models that predict class membership?

A health analytics professional must be skilled in all of the following except:

Which of the following data characteristics are important in understanding big data in healthcare? (Select all that apply.)

An Introduction to Health Informatics

Theoretical Foundations of Health Informatics

Evidence-Based Practice, Practice-Based Evidence, and Informatics

Models, Theories, and Research for Program Evaluation

Technical Infrastructure to Support Healthcare

Electronic Health Records and Applications for Managing Patient Care

Administrative Applications Supporting Healthcare Delivery

Telehealth and Applications for Delivering Care at a Distance

Home Health and Related Community-Based Systems

Clinical Decision Support Systems in Healthcare

Public Health Informatics

The Evolving Epatient

Social Media Tools for Practice and Education

Personal Health Records PHRS

Mhealththe Intersection of Mobile Technology and Health

Identifying and Selecting an Information System Solution

Project Management Principles and Clinical Systems

Contract Negotiations and Software Licensing

Implementing and Upgrading an Information System Solution

Health Information Systems: Downtime and Disaster Recovery

Improving the User Experience for Health Information Technology Products

Informatics-Related Standards and Standards-Setting Organizations

Patient Safety and Quality Initiatives in Informatics

Legal Issues, Federal Regulations, and Accreditation

Privacy and Security

The Health Information Technology for Education and Clinical Health Hitech Act, Meaningful Use Mu, and Medicare Access & Chip Reauthorization Act of 2015 Macra

Health Policy and Health Informatics

Health Information Technology Governance

Informatics in the Curriculum for Healthcare Professionals

Distance Education: Applications, Techniques, and Issues

Informatics Tools for Educating Health Professionals

Simulation in Healthcare Education

International Informatics Efforts

The Evolution of Health Informatics

Future Directions and Future Research in Health Informatics

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