Abstract

Background/Objectives Illness severity and comorbidity rating scales have been found to predict long-term outcomes for older hospitalized adults. This study was designed to determine if these rating systems could also predict short-term hospital outcomes. Design Prospective observational study of hospitalized adults 65 and older. Medical students calculated comorbidity and illness severity using the CCI and the CIRS based on information available in electronic medical records during the first 24 hours after admission. Setting The ICU and wards of two metropolitan hospitals. Participants Senior adults admitted over a three-year period. There were 597 enrolled patients with a mean age of 76.1 years. Participants were 35.5% male, 50.9% Caucasian, and 48.1% African American. Results Logistic regression models found the CIRS (OR = 1.13, 95% CI 1.02, 1.26), but not the CCI (OR = 1.01, CI 0.82, 1.25), was significantly associated with in-hospital death and the receipt of discharge services (OR = 1.086, CI 1.049, 1.124) compared to (OR = 1.002, CI 0.993, 1.131). In further analysis, it was found that a CIRS score of 29 or greater was associated with significant increase in a patient's chance of death during that hospitalization (OR = 14.05, CI 1.60, 123.17) compared to the reference group (OR = 2.57 CI 1.42, 4.66) for requiring additional services post discharge. Conclusions The admission calculated CIRS is useful for predicting important hospital outcomes. Such information may allow clinicians to target intensive care to appropriate patients at high risk of death or long stays and to better anticipate end of life issues. Furthermore, this information may be helpful in risk adjustment for researchers and policy makers.

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