AI-Enabled Workflow Redesign for EECP Microcirculation Follow-Up: A Design Science Approach

Abstract

Enhanced external counterpulsation (EECP) is a non-invasive cardiovascular rehabilitation therapy, but its follow-up in routine outpatient practice is often difficult to standardize, interpret efficiently, and communicate consistently. Although nailfold videocapillaroscopy (NVC) offers a direct view of peripheral microcirculation, its practical use remains constrained by image-quality variation, manual reading burden, and inconsistent reporting.

To address these issues, this study adopts a Design Science Research perspective to develop a generative-AI–assisted medical information system for NVC-based EECP follow-up. The proposed artifact integrates image quality control, structured AI-assisted interpretation, report generation, human review, and audit logging into a governable outpatient workflow. A pilot implementation in a single clinic involving three physicians suggests that the system can reduce turnaround time and labor burden, support more scalable service delivery, and provide a structured basis for improving report consistency, though systematic consistency evaluation remains for future work. This study contributes an MIS artifact that demonstrates how generative AI can be operationally embedded into EECP follow-up.