This thesis develops and evaluates an Implementation Optimization Framework to improve healthcare client implementations. The framework standardizes onboarding and integration, enables interoperable collaboration for multidisciplinary teams, uses closed-loop satisfaction metrics to identify and address service gaps, and applies workflow analysis and redesign supported by scalable data governance. Using mixed methods (process analysis and time studies, interviews, usability measures, and service-quality metrics), the study measures changes in time-to-value, adoption, clinician burden, integration defects, and client satisfaction. Deliverables include reusable templates, a metrics dashboard, and a governance model.
Graduate & Continued Education Projects
Client Satisfaction Improvement
Data-driven analysis aimed at identifying service gaps and implementing corrective loops.
Innovative Healthcare Solutions
Exploration of emerging digital health trends and their application in chronic disease management.
Data Management for Growth
Architectural strategy focused on scalable data warehousing and governance for expanding networks.
Let's Collaborate
Open to research inquiries and technology-driven collaboration. I am looking for opportunities to apply innovation and leadership within professional healthcare and academic research projects.