Clinical research study
A Prognostic Model for 1-Year Mortality in Older Adults after Hospital Discharge

https://doi.org/10.1016/j.amjmed.2006.09.021Get rights and content

Abstract

Purpose

To develop and validate a prognostic index for 1-year mortality of hospitalized older adults using standard administrative data readily available after discharge.

Subjects and methods

The prognostic index was developed and validated retrospectively in 6382 older adults discharged from general medicine services at an urban teaching hospital over a 4-year period. Potential risk factors for 1-year mortality were obtained from administrative data and examined using logistic regression models. Each risk factor associated independently with mortality was assigned a weight based on the odds ratios, and risk scores were calculated for each patient by adding the points of each independent risk factor present. Patients in the development cohort were divided into quartiles of risk based on their final risk score. A similar analysis was performed on the validation cohort to confirm the original results.

Results

Risk factors independently associated with 1-year mortality included: aged 70 to 74 years (1 point); aged 75 years and greater (2 points); length of stay at least 5 days (1 point); discharge to nursing home (1 point); metastatic cancer (2 points); and other comorbidities (congestive heart failure, peripheral vascular disease, renal disease, hematologic or solid, nonmetastatic malignancy, and dementia, each 1 point). In the derivation cohort, 1-year mortality was 11% in the lowest-risk group (0 or 1 point) and 48% in the highest-risk group (4 or greater points). Similarly, in the validation cohort, 1-year mortality was 11% in the lowest risk group and 45% in the highest-risk group. The area under the receiver operating characteristic curve was 0.70 for the derivation cohort and 0.68 for the validation cohort.

Conclusion

Reasonable prognostic information for 1-year mortality in older patients discharged from general medicine services can be derived from administrative data to identify high-risk groups of persons.

Section snippets

Participants

The data used in these analyses were collected on individuals enrolled in a prospective cohort study comparing costs and outcomes of care by hospitalist and non-hospitalist physicians. It was conducted on an academic general medicine service at the University of Chicago Hospitals in Chicago, Ill from July 1, 1997 through June 30, 2001. The study included 14,661 patients admitted to the general medicine service either directly or transferred from nonmedical services or intensive care. Details of

Study Populations

Characteristics of the derivation and validation cohorts are listed in Table 1. The mean (SD) age of the patients in the derivation cohort was 78 (8.3) years. Sixty-three percent were female, 81% were African American, and 15% were discharged to a nursing home or skilled nursing facility. Thirty-five percent had a length of stay of at least 5 days in the hospital before discharge. During 1-year of follow-up, 722 patients (26%) died.

The mean (SD) age of the patients in the validation cohort was

Discussion

We have created a relatively simple prognostic index for older adults discharged from a general medicine service that stratifies patients at risk for 1-year mortality using information readily available from standard administrative data. Because many Medicare beneficiaries are hospitalized at least once in the year before death,22 the hospital admission becomes an important window of opportunity for recognizing persons at risk for further decline and mortality. As medical records are becoming

Acknowledgments

Supported by the University of Chicago Hospitals, Chicago, Illinois; the Charles E. Culpeper Foundation, New York, New York; the National Institute of Aging, Bethesda, Maryland; the Robert Wood Johnson Foundation, Princeton, New Jersey; the Hulda B. and Maurice L. Rothschild Foundation, Chicago, Illinois; the Academic and Managed Care Forum, Hartford, Connecticut; and the John A. Hartford Foundation/American Federation for Aging Research, New York, New York.

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