Impact of an all-inclusive diagnosis-related group payment system on inpatient utilization.
OBJECTIVE
Although case-based payment is one of the main reimbursement mechanisms for hospitals, little is known about its effects in the general population. Prior studies have focused on Medicare or on all-payer systems in particular states. This study estimates the effect of a prospective payment system based on diagnosis-related groups (DRGs) nationwide in the Department of Veterans Affairs.


METHODS
Multiple regression analysis was used to estimate the effect of Department of Veterans Affairs's diagnosis-related group system separately for 22 diagnoses. The dependent variables were length of stay, inpatient days per patient, and discharges per patient. Covariates included patient, hospital, and area characteristics.


RESULTS
Department of Veterans Affairs's diagnosis-related group system reduced lengths of stay and inpatient days per patient. The largest impacts were for the psychiatric diagnoses and several surgical procedures. The magnitudes of the effects were generally moderate. Department of Veterans Affairs's case-based system had a negligible effect on discharges per patient.


CONCLUSIONS
Per case reimbursement is a potentially useful tool for improving the efficiency of inpatient care for all types of diagnoses and age groups. The effect may be larger than estimated here because of institutional barriers and caps on financial impact.
Center for Quality of Care and Utilization Studies, Veterans Affairs Medical Center, Houston, TX 77030, USA. tmenke@bcm.tmc.edu
T J
TJ
Menke
C M
CM
Ashton
N J
NJ
Petersen
F D
FD
Wolinsky
D000368:Aged; D003953:Diagnosis-Related Groups / Q000145:classification* / Q000191:economics; D005260:Female; D019538:Health Care Surveys; D006760:Hospitalization / Q000191:economics / Q000706:statistics & numerical data* / Q000639:trends; D006787:Hospitals, Veterans / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data / Q000639:trends; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D010351:Patient Discharge / Q000191:economics / Q000706:statistics & numerical data / Q000639:trends; D012052:Reimbursement, Incentive; D012959:Socioeconomic Factors; D014481:United States; D014493:United States Department of Veterans Affairs