Length of stay and procedure utilization are the major determinants of hospital charges for heart failure

Clin Cardiol. 2001 Jan;24(1):56-62. doi: 10.1002/clc.4960240110.


Background: Most of the 10 billion dollars spent annually on heart failure (HF) management in this country is attributed to hospital charges. There are widespread efforts to decrease the costs of treating this disorder, both by preventing hospital admissions and reducing lengths of stay (LOS).

Hypothesis: The objective of this study was to identify the major determinants of hospital charges for an acute hospitalization for HF among a large, diverse group of patients.

Methods: Administrative information on all 1995 New York State hospital discharges assigned ICD-9-CM codes indicative of HF in the principal diagnosis position were obtained. Bivariate and multivariate statistical analyses were utilized to determine those patient- and hospital-specific characteristics which had the greatest influence on hospital charges.

Results: In all, 43,157 patients were identified. Mean hospital charges were $11,507+/-15,995 and mean hospital LOS was 9.6+/-14.5 days. With multivariate analyses, the most significant independent predictors of higher hospital charges were longer LOS, admission to a teaching hospital, treatment in an intensive care unit, and the utilization of cardiac surgery, permanent pacemakers, and mechanical ventilation. Age, gender, race, comorbidity score, and medical insurance, as well as treatment by a cardiologist and death during the index hospitalization were not among the most significant predictors.

Conclusions: We conclude that LOS and procedure utilization are the major determinants of hospital charges for an acute episode of inpatient HF care. Reducing LOS and other initiatives to restructure hospital-based HF care may reduce total health care costs for HF.

MeSH terms

  • Aged
  • Female
  • Heart Failure / diagnosis
  • Heart Failure / economics*
  • Hospital Charges*
  • Humans
  • Length of Stay / economics*
  • Male
  • New York
  • Severity of Illness Index
  • Therapeutics / statistics & numerical data