Techniques for masking data.
A. List three techniques for masking data.
B. What are the differences between generalization, suppression, and subsampling?
2. A. What caused HL7 to gain popularity in the US?
B. Explain what the incentive program promoted the adoption of.
C. Provide one example of a population health use case for the incentive program.
3. Big data has five (5) characteristics and is classified into five (5) main categories. Explain the characteristics and categories.
4. Discuss the four (4) drivers of innovation in healthcare.
5. Discuss two compelling use cases of HIE for population health improvement.
6.For what reasons would some argue that data are never truly anonymous?
7.Friedman (2009) posits that “informatics is about the use of technology to help people carry out cognitive tasks more effectively rather than about constructing technological infrastructure to replace experts.” What do you think he meant by this statement?
8.Name five (5) functionalities that EMRs deliver.
9.Name three challenges that limit the integration of social determinants of health data.
10.What are four factors that have empowered the collection and development of new population-wide data sources?
11.What are the three (3) criteria for meaningful use of electronic health records (EHRs) and what are the five (5) objectives of meaningful use?
12.What are the three structural barriers to the adoption of technology in healthcare?
13.What years did the United States begin a CDC fellowship program and the National Center for Public Health Informatics?
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