Severity of illness and resource use differences among white and black hospitalized elderly.

BACKGROUND: Disparities between races in access to health care services continue to exist. We examined differences in illness severity, charges, and length of stay between white and black hospitalized elderly. METHODS: The study sample was 1184 elderly patients. Data using the Computerized Severity Index were collected for admission, maximum throughout the stay, and discharge. RESULTS: Blacks were admitted significantly more severely ill than whites. At discharge, 96% were severity level 1. At each severity level, blacks had significantly shorter hospitalizations and lower charges. The differences were not explained by disease, surgery, age, sex, hospital, and payer. CONCLUSIONS: Admission severity disparities may exist because of patients' decisions to seek care or provider admitting practices. We need to study whether differences in severity-adjusted resource use are due to underutilization for blacks or overutilization for whites.

Nursing care classification: a conceptual model.

Economic constraints, the information explosion, and advancement of scientific theories have resulted in the need for nurses to document their unique contribution to health care through validation of nursing resources consumed by patients. However, various classification systems have not predicted nursing resources well. This study reviews the theoretical frameworks, reliability, validity, and utility of nursing acuity and severity systems. It proposes a conceptual model for a new nursing classification system to be used for the validation of nursing resources, as the basis of a reimbursement system for nursing services, and for multiple practical and theoretical applications.

The relationship between severity of illness and hospital length of stay and mortality.

To address the question of quantification of severity of illness on a wide scale, the Computerized Severity Index (CSI) was developed by a research team at the Johns Hopkins University. This article describes an initial assessment of some aspects of the validity and reliability of the CSI on a sample of 2,378 patients within 27 high-volume DRGs from five teaching hospitals. The 27 DRGs predicted 27% of the variation in LOS, while DRGs adjusted for Admission CSI scores predicted 38% and DRGs adjusted for Maximum CSI scores throughout the hospital stay predicted 54% of this variation. Thus, the Maximum CSI score increased the predictability of DRGs by 100%. We explored the impact of including a 7-day cutoff criterion along with the Maximum CSI score similar to a criterion used in an alternative severity of illness measure. The DRG/Maximum CSI score's predictive power increased to 63% when the 7-day cutoff was added to the CSI definition. The Admission CSI score was used to predict in-hospital mortality and correlated R = 0.603 with mortality. The reliability of Admission and Maximum CSI data collection was high, with agreement of 95% and kappa statistics of 0.88 and 0.90, respectively.