Cost-Effectiveness in Perioperative Care: Application of Markov Modeling to Pathways of Perioperative Care

OBJECTIVES: This study aimed to evaluate the application of cost-effectiveness modeling to redesign of perioperative care pathways, from a hospital perspective. METHODS: A Markov cost-effectiveness model of patient transition between care locations, each with different characteristics and cost, was developed. Inputs were derived from clinical trials piloting a preoperative call center and a postoperative medium-acuity care unit. The effect chosen was days at home (DAH) after surgery, reflecting quality of in-hospital care, acknowledged financially by fundholders, and relevant to consumers. Cost was from the hospital's perspective. A model cycle time of 4 hours for 30 days reflected relevant timelines and costs. RESULTS: A Markov model was successfully created, accounting for the care locations in the 2 pathways as model states and accounting for consequences and costs. Cost-effectiveness analysis allowed the calculation of an incremental cost-effectiveness ratio comparing these pathways, providing a mean incremental cost-effectiveness ratio of -$427 per additional DAH, where incremental costs and DAH were -$644 and +1.51, respectively. Probabilistic sensitivity analysis suggested the new pathway had a 61% probability of reduced costs and a 74% probability of increased DAH and a 58% probability this pathway was dominant. Tornado analysis revealed the major contributor to increased costs as intensive care unit stay and the major contributor to decreased costs as ward stay. For the new pathway, the probability of transfer from ward to home and the probability of staying at home had the greatest impact on DAH. CONCLUSIONS: These data suggest Markov modeling may be a useful tool for the cost-effectiveness analysis of initiatives in perioperative care.