Using causal rule mining to identify opportunities for value improvement in regional CABG care: A proof-of-concept study.

Abstract

To explore the potential of causal rule mining (CRM) as a complementary method to outcome monitoring in identifying plausible causal patterns that may explain undesired clinical outcomes or elevated care consumption in cardiac surgery. In this proof-of-concept study, CRM was applied to data from 1,068 patients who underwent elective isolated coronary artery bypass grafting between January 2016 and March 2021 at a single heart center and its referral network in the Netherlands. Outcomes of interest included: 1-year and 120-day mortality, in-hospital stroke, 30-day deep sternal wound infection (DSWI), 30-day re-explorations, 1-year coronary reinterventions, event-free survival, 30-day emergency department (ED) visits, postoperative length of stay, and preoperative fractional flow reserve (FFR) testing. Causal rules were considered relevant if both the odds ratio (OR) and its 95 % confidence interval (CI) were > 1. Identified rules were independently reviewed by clinical experts. CRM identified 114 significant rules. Five rules were rated as 'new and interesting' and two additional rules were included based on special interest. In follow-up discussions, clinical experts agreed that three rules warrant further clinical investigation: (1) the absence of fractional flow reserve (FFR) testing reducing the likelihood of coronary reintervention, (2) absence of red blood cell (RBC) transfusion during admission reducing the likelihood of 30-day re-explorations, and (3) RBC transfusion increasing the likelihood of 30-day re-explorations. CRM helped identify potential explanations for certain outcomes and care consumption, providing structured input for hypothesis-driven quality improvement and supporting efforts to enhance patient value.