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Using causal rule mining to identify opportunities for value improvement in regional CABG care: A proof-of-concept
Sophie van Heuveln1, Gijs J van Steenbergen2, Mileen R D van de Kar2
1Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, the Netherlands.
Objective:
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.
Methods:
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.
Results:
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.
Conclusion:
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.
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