Reports suggest that preoperative optimization of a patient’s serious comorbidities is associated with a reduction in postoperative complications.
The purpose of this study was to assess the cost and benefits of preoperative optimization, accounting for total costs associated with postoperative morbidity.
This study is a decision tree cost-effectiveness analysis with probabilistic sensitivity analysis (10,000 iterations).
This is a hypothetical scenario of stage II colon cancer surgery.
The simulated 65-year-old patient has left-sided, stage II colon cancer.
Focused preoperative optimization targets high-risk comorbidities.
Total discounted (3%) economic costs (US $2018), effectiveness (quality-adjusted life-years), incremental cost-effectiveness ratio (incremental cost-effectiveness ratio, cost/quality-adjusted life-years gained), and net monetary benefit.
We calculated the per individual expected health care sector total cost of preoperative optimization and sequelae to be $12,395 versus $15,638 in those not optimized (net monetary benefit: $1.04 million versus $1.05 million). A nonoptimized patient attained an average 0.02 quality-adjusted life-years less than one optimized. Thus, preoperative optimization was the dominant strategy (lower total costs; higher quality-adjusted life-years). Probabilistic sensitivity analysis demonstrated 100% of simulations favoring preoperative optimization. The breakeven cost of optimization to remain cost-effective was $6421 per patient.
Generalizability must account for the lack of standardization among existing preoperative optimization efforts, and decision analysis methodology provides guidance for the average patient or general population, and is not patient-specific.
Although currently not comprehensively reimbursed, focused preoperative optimization may reduce total costs of care while also reducing complications from colon cancer surgery.
The full study is available here.