The trade-off between costs and outcome after cardiac surgery. Evidence from an Italian administrative registry

• Published in: Health policy (Amsterdam) 2020-12, Vol.124 (12), p.1345-1353
• Main Authors: Caruso, Enza, Rossi Zadra, Andrea
• Format: Article
• Language: English
• Subjects: Administrative registry; Cardiac surgery; Cardiac surgical procedures; Classification; Clinical decision making; Disease; Endogenous; Health administration; Health care expenditures; Heart surgery; Hospital costs; Hospitalization; Italy; Long term; Outcome; Patients; Postoperative morbidity; Readmission; Resource allocation; Risk factors; Risk of readmission; Surgery
• ISSN: 0168-8510; 1872-6054
• DOI: 10.1016/j.healthpol.2020.09.005

•Trade-off analysis of costs and outcome in cardiac surgery may be informative for policymakers.•Determinants of readmission after surgery may be captured by administrative data.•Real-world clinical conditions (comorbidities and complications) are approximated by ICD-9CM codes.•A 6-month time window may be appropriate to capture the potential long-lasting sequelae of cardiac procedures.•The higher the costs at first admission, the lower the hazard of readmissions. Effective resource allocation policies relating to the long-term effects of complex surgical procedures require accurate prediction of the likelihood of future hospitalization. By approximating clinical conditions with administrative data and controlling for complex case-mix scenarios, we provide evidence of a trade-off between costs and outcome in cardiac surgery. We modelled administrative data to account for clinical conditions in a population of patients admitted for cardiac surgery and their readmissions for complications. Costs were calculated at first admission, the outcome variable was defined as time to readmission within six months post-discharge. Risk factors for readmission were defined as comorbidities and postoperative complications, derived by clinical judgement from the International Classification of Diseases. We predicted health outcome as a function of costs and other patient- and hospital-level features using a two-stage residual inclusion estimation method to tackle endogenous relationships applied to Cox proportional hazard models. We confirmed the trade-off and negative association between costs and hazard of readmission when controlling for all complex risk factors. Accurate matching of standard codes for diseases and procedures with clinical conditions may be a reliable methodology to assess time to readmissions and costs on a large population scale.