New Index Developed by Yale Researcher to Assess The Risk of Mortality in an Elderly Population

In order to foster sound health care programs and policies concerning an aging population, a Yale researcher has devised a new index that forecasts which patients are most likely to die within one year after being discharged from the hospital.

In order to foster sound health care programs and policies concerning an aging population, a Yale researcher has devised a new index that forecasts which patients are most likely to die within one year after being discharged from the hospital.

“It’s very important to be able to compare how sick patients are across populations, across hospitals and across studies,” said Sharon Inouye, M.D., associate professor of internal medicine and geriatrics at Yale School of Medicine and senior author of the study published this month in the Journal of the American Geriatrics Society. “Any time we are looking at the outcome of treatment and quality of care, it all impinges on understanding how comparable patients are.”

What she and her co-researchers found were that elderly patients with 10 conditions were at higher risk for dying within one year of being hospitalized. Those conditions, in descending order of risk, are: congestive heart failure; pneumonia; chronic lung disease; solid tumor cancer that is localized; metastatic cancer; lymphoma/leukemia; major stroke; acute renal failure; chronic renal failure, and diabetes with end organ damage.

The study included 524 patients 70 and older with a comparison group of 852 patients of the same age who also were hospitalized. The researchers first identified 16 high risk medical diagnoses for older patients, based on a review of medical literature and expert opinion. The experts added six more diagnoses. From this group, the 10 final diagnoses were selected.

Inouye cautioned that the risk assessment is not for use with individuals.

“Given the potential for misuse, or misinterpretation, we do not advocate use of this index at the bedside for individual patients,” she said. “The index is recommended for mortality prediction in patient groups or populations.”

She said some examples of clinical usefulness might include identification of high risk groups who would benefit from early intervention or case management services; comparisons of treatment effectiveness or outcomes between patient groups, and evaluation of clinical performance or quality of care across health systems.

Other risk assessment systems, she said, either do not apply to the elderly because they do not address the elderly’s multiple chronic diseases and high burden of illness. Still other risk assessments were targeted for the elderly, but required extensive physicals or reviewing charts in great detail.

“We wanted to come up with a system that is based on administrative data that is readily available, identifies high risk diagnoses and indicates which segments of the elderly population are at high risk for mortality,” said Inouye. “We’re hoping this will be useful to people who do research with older patients or develop new systems to care for older patients.”

Co-authors include Mayur Desai, Sidney Bogardus, M.D., Christianna Williams and Gail Vitagliano, M.D. The research was supported in part by grants from the National Institute on Aging with in-kind support from the Claude D. Pepper Older Americans Independence Center.

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