Faculty Spotlight: Solving Business Problems
Inkyoung Hur, Ph.D., is an assistant professor of information technology and operations management in the College of Business.

Faculty Spotlight: Solving Business Problems

How a Data Analyst Measures Information Technology

Inkyoung Hur, Ph.D., always found herself drawn to technology and to business. Those passions led her to research the relationship between social media, technology and their impact on people’s lives at Florida Atlantic University, particularly in the healthcare system.

“I believe technology is influential. I see how it can change a business and an individuals’ everyday life. I am thrilled when I see how my research and my teaching changes people,” said Hur, an assistant professor in the College of Business.

A native of South Korea, Hur earned a bachelor’s degree in industrial engineering from Pusan National University, South Korea. She spent five years working as a data analyst at Samsung in Seoul, South Korea, learning how to manage data used for businesses. She also earned a master's degree in industrial engineering with a specialization in information visualization in a healthcare domain from Purdue University in West Lafayette, Indiana. And, she earned a doctorate in business administration and management information systems from Florida International University, where she also received awards like the presidential fellowship for her multidisciplinary experience in engineering, information systems, decision science and business.

She was an assistant professor at Nova Southeastern University for three years before coming to FAU. “I love dealing with practical problems, collaborating with students, faculty and alumni like real practitioners to solve the problems and get back research outcomes to practice. I believe it is the best part of teaching and research together,” she said. “I wanted to move to FAU to continue my research activities, a place that will allow me to increase my research efforts.”

Here’s a look at Hur’s journey to FAU:

Q: What is your research focus?

A: Generally, I am a data analytics researcher. I love playing with data, both numbers and texts, to figure out some interesting patterns and provide solutions in a variety of fields, from information security to health information technologies and blockchain technology. I have developed a research program that studies technology-enabled process changes using data mining, text mining and process mining.

I have an interest in healthcare, so for my other research projects, I study how online health communities can enable people to proactively manage their own health care, termed patient engagement and empowerment. Unlike most health applications that focus on supporting healthcare professionals, my research considers how individuals and family members use health technologies mainly designed for patients and interact with other patients through the results of text mining technique.

Q: Why do you have an interest in this research?

A: I have a special research interest in data analytics and data mining. My doctorate dissertation was about the effects of the use of social media technology on healthcare process changes using process mining and text mining techniques. My work experience as data analysts would encourage me to dig deep in business analytics.

Q: What do you want people to know about your research?

A: Many people say that the use of information technology and information systems dramatically changed our daily lives and business. With the COVID-19 pandemic, the world turned more digital than ever, and the role of information technologies became more important. Businesses took actions to alter their business strategies to come up with a business environment that has been changing. I would find some interesting patterns with the technology use either in business or in personal life based on the data analysis.

Q: What do you hope to accomplish from your research?

In my predictive analytics project, I develop and apply predictive models for treatment choices which extends the lives of kidney disease patients using data mining. Prediction models are developed with 15-year data of 250 patients with a kidney disease admitted to a large, urban academic hospital in China. We would like to see how the prediction models are used among physicians.

Q: Do you have any advice for becoming a researcher in your field?

A: My advice to upcoming researchers is to have critical thinking and deep thinking about questions and problems that interest you. Your insights and curiosity come from that kind of thinking. It’s also helpful to meet researchers who work in other disciplines, as each person offers their own experiences, perspectives, and values carved by their backgrounds. You’ll never know what they could contribute to some aspect of your research, by providing a unique view. Sharing these different views and experiences creates opportunities for researchers to understand problems and solutions better. Finally, I would encourage you to find a mentor who supports your idea and research goals.

Q: Where do you see your research continuing in the future?

A: I would like to continue working on the healthcare domain. Nowadays, healthcare practices have been changing to telemedicine and the extensive use of the electronic medical record. This is the foundation of digital personalized medical practice, and it is time to utilize the record data to apply data analytics algorithms to provide better personalized healthcare. Furthermore, we need to make medical databases secure. In one of my projects, I study how an integrative social media platform changes health care processes, in terms of interactions between patients and physicians toward patient-centered care. Patient-centered care becomes feasible because of technology that revolutionizes the way healthcare information is collected, personalized and shared.

I collected system usage data of social media mobile app to understand the relationships around the use of the integrative social media platform and its impacts on individual behaviors and clinical processes. Text analysis with communication contents in the technology revealed the interactions between patients and physicians. The analysis results of process mining show that the patient-centered care process is enabled using an integrative social media platform, and how different system usage affect process changes. By using an integrative social media platform, physicians better understand the patients’ needs and want. Patients and physicians decide what they would do for the patient.

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