Explaining price variations for the inpatient treatment of congestive heart failure.
OBJECTIVE
To identify key factors affecting hospital charge variations in the treatment of congestive heart failure.


METHODS
The determinants of total charges and average charges (the latter being a measure of treatment intensity) were evaluated using hospital discharge abstract data from 1994. Multivariate regression methods were used to help isolate the impact of key predictors of charges. In addition to relating a variety of factors (e.g., drug treatment regimens, patient comorbidities, demographic characteristics, insurance status, treatment course) to hospital charges, the analysis controlled for hospital-specific fixed effects. The study includes the effects of pharmacologic agents--information typically unavailable on inpatient claims-based data.


RESULTS
Drug treatment regimens, particularly treatment with inotropic agents, were associated with substantially higher total charges. Comorbidities also increased the cost of treating congestive heart failure, particularly when septicemia, pneumonia, or acute myocardial infarction were involved. In contrast, gender, race, and insurance status bore little relationship to total charges or average charges.


CONCLUSIONS
The fixed-effects estimates revealed that substantial interhospital variations in charges persisted, suggesting that there may be significant opportunities to control the inpatient costs of treating congestive heart failure.
Rizzo
J A
JA
Yale University, School of Medicine, New Haven, CT 06520, USA. John.Rizzo@Yale.edu
Simons
W R
WR
D003710:Demography; D016527:Drug Costs / Q000706:statistics & numerical data*; D006302:Health Services Research / Q000379:methods; D006333:Heart Failure / Q000188:drug therapy* / Q000191:economics*; D017722:Hospital Charges / Q000706:statistics & numerical data*; D017721:Hospital Costs / Q000706:statistics & numerical data; D006801:Humans; D007350:Insurance, Hospitalization / Q000706:statistics & numerical data; D008329:Managed Care Programs / Q000191:economics; D006278:Medicare / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data; D014481:United States