Faculty and ResearchExpert Guide

Education

• Ph.D. in Business Administration
  College of Business, University of South Florida, Tampa, Florida

Professional Activities

As a faculty member at FIU’s Department of Information Systems and Business Analytics, and a Research Associate at the VA HSR&D/RR&D Center of Innovation on Disability and Rehabilitation Research, my research involves the use of innovative analytics methods to improve patient experience, increase provider productivity and reduce overall healthcare costs. These include the the design of a blockchain-based solution that would enable patients to share their validated comprehensive treatment records with peers, a real-time clinical recommender system that provides recommendations for medications along with associated cost information, a solution to automate provider documentation, and an auditing algorithm to maximize deterrence from fraud, waste, and abuse.

Courses Taught

• Artificial Intelligence for Business
• Business Analytics Applications
• Management of the Information Systems Function
• Managing Distributed Architectures
• Quality and Outcomes Analytics

Refereed Journal Articles

Bouayad, L.

(2022).

Applying NLP to extract clinician recorded affect to advance depression clinical research: A proof of concept.

. Journal of Medical Internet Research – Formative Research.

.

Bouayad, L., Padmanabhan, B., & Chari, K. (2020). Can Cost Transparency in Recommendations Reduce Healthcare Costs? The Role of Time Pressure and Cost-Framing. MIS Quarterly.

Subramanian, H., Cousins, K., Bouayad, L., Alpen, S., & Conway, D. (2020). Blockchain Regulations and Decentralized Applications. Communications of the Association for Information Systems.

Bouayad, L., Padmanabhan, B., & Chari, K. (2019). Audit Policies under the Sentinel Effect: Deterrence-Driven Algorithms. Information Systems Research.

Singh, V. K., Shrivastava, U., Bouayad, L., Padmanabhan, B., Ialynytchev, A., & Schultz, S. K. (2018). Machine learning for psychiatric patient triaging: An investigation of cascading classifiers. Journal of the American Medical Informatics Association : JAMIA, 25.

Fodeh, S. J., Finch, D., Bouayad, L., Luther, S. L., Ling, H., Kerns, R. D., & Brandt, C. (2018). Classifying clinical notes with pain assessment using machine learning. Medical & Biological Engineering & Computing, 56.

Luther, S. L., Thomason, S. S., Sabharwal, S., Finch, D. K., McCart, J., Toyinbo, P., . . . Powell-Cope, G. (2017). Leveraging Electronic Health Care Record Information to Measure Pressure Ulcer Risk in Veterans With Spinal Cord Injury: A Longitudinal Study Protocol. JMIR Research Protocols, 6.

Bouayad, L., Ialynytchev, A., & Padmanabhan, B. (2017). Patient Health Record Systems Scope and Functionalities: Literature Review and Future Directions. Journal of Medical Internet Research, 19.