If patients who are more severely ill have greater hospital costs for surgery, then health-care reimbursements need to be adjusted appropriately so that providers caring for more seriously ill patients are not penalized for incurring higher costs.
The authors'goal for this study was to determine if severity of illness, as measured by either the American Society of Anesthesiologists Physical Status (ASA PS) or the comorbidity index developed by Charlson, can predict anesthesia costs, operating room costs, total hospital costs, or length of stay for elective surgery.
The authors randomly selected 224 inpatients (60% sampling fraction) having either colectomy (n=30), total knee replacement (n=100), or laparoscopic cholecystectomy (n=94) from September 1993 to September 1994.
For each surgical procedure, backward-elimination multiple regression was used to build models to predict (1) total hospital costs, (2) operating room costs, (3) anesthesia costs, and (4) length of stay.
Explanatory candidate variables included patient age (years), sex, ASA PS, Charlson comorbidity index (which weighs the number and seriousness of coexisting diseases), and type of insurance (Medicare/Medicaid, managed care, or indemnity).
These analyses were repeated for the pooled data of all 224 patients.
Costs (not patient charges) were obtained from the hospital cost accounting software. (...)
Mots-clés Pascal : Coût, Hospitalisation, Homme, Chirurgie, Indice gravité, Prédiction, Economie santé, Etats Unis, Amérique du Nord, Amérique
Mots-clés Pascal anglais : Costs, Hospitalization, Human, Surgery, Severity score, Prediction, Health economy, United States, North America, America
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 97-0155589
Code Inist : 002B30A04B. Création : 21/05/1997.