Sharon K. Inouye

Objectives: To validate a chart‐based method for identification of delirium and compare it with direct interviewer assessment using the Confusion Assessment Method (CAM). Design: Prospective validation study. Setting: Teaching hospital. Participants: Nine hundred nineteen older hospitalized patients. Measurements: A chart‐based instrument for identification of delirium was created and compared with the reference standard interviewer ratings, which used direct cognitive assessment to complete the CAM for delirium. Trained nurse chart abstractors were blinded to all interview data, including cognitive and CAM ratings. Factors influencing the correct identification of delirium in the chart were examined. Results: Delirium was present in 115 (12.5%) patients according to the CAM. Sensitivity of the chart‐based instrument was 74%, specificity was 83%, and likelihood ratio for a positive result was 4.4. Overall agreement between chart and interviewer ratings was 82%, kappa=0.41. By contrast, using International Classification of Diseases, Ninth Revision, Clinical Modification , administrative codes, the sensitivity for delirium was 3%, and specificity was 99%. Independent factors associated with incorrect chart identification of delirium were dementia, severe illness, and high baseline delirium risk. With all three factors present, the chart instrument was three times more likely to identify patients incorrectly than with none of the factors present. Conclusion: A chart‐based instrument for delirium, which should be useful for patient safety and quality‐improvement programs in older persons, was validated. Because of potential misclassification, the chart‐based instrument is not recommended for individual patient care or diagnostic purposes.

To develop and validate a new risk adjustment index-the Burden of Illness Score for Elderly Persons (BISEP)-which integrates multiple domains, including diseases, physiologic abnormalities, and functional impairments. RESEARCH DESIGN SUBJECTS: The index was developed in a prospective cohort of 525 patients aged > or = 70 years from the medicine service of a university hospital. The index was validated in a cohort of 1246 patients aged > or = 65 years from 27 hospitals. The outcome was 1-year mortality. Five risk factors were selected from diagnosis, laboratory, and functional status axes: high-risk diagnoses, albumin < or = 3.5 mg/dL, creatinine >1.5 mg/dL, dementia, and walking impairment. The BISEP score (range 0-7) created four groups of increasing risk: group I (score 0-1), group II (2), group III (3), and group IV (> or = 4). In the development cohort, where overall mortality was 154/525 (29%), 1-year mortality rates increased significantly across each risk group, from 8% to 24%, 51%, and 74%, in groups I to IV respectively (chi(2) trend, = 0.001)--an overall 17-fold increased risk by hazard ratio. The c-statistic for the final model was 0.83. Corresponding rates in the validation cohort, where overall mortality was 488/1246 (39%), were 5%, 17%, 33%, and 61% in groups I to IV, respectively (chi(2) trend, = 0.001)-an overall 18-fold increased risk by hazard ratio. The c-statistic for the final model was 0.77. In each cohort, sequential addition of variables from different sources (eg, administrative, laboratory, and chart) substantially improved model fit and predictive accuracy. BISEP had significantly superior mortality prediction compared with five widely used measures. BISEP provides a useful new risk adjustment system for hospitalized older persons. Although index performance using different data sources has been evaluated, the full BISEP model, incorporating disease, laboratory, and functional impairment information, demonstrates the best performance.