TY - JOUR
T1 - Framework for evaluating disease severity measures in older adults with comorbidity
AU - Boyd, Cynthia M.
AU - Weiss, Carlos O.
AU - Halter, Jeff
AU - Han, K. Carol
AU - Ershler, William B.
AU - Fried, Linda P.
N1 - Funding Information:
ACKNOWLEDGMENTS This work was supported by a task order from the National Institute on Aging. Drs. Boyd and Fried are supported by the National Institute on Aging’s Older Americans Independence Center, P30 AG021334. Dr. Boyd is a Bayview Scholar at the Center for Innovative Medicine. Dr. Weiss was supported by Training Grant T32 AG00247 from the National Institute on Aging.
PY - 2007/3
Y1 - 2007/3
N2 - Background. Accounting for the influence of concurrent conditions on health and functional status for both research and clinical decision-making purposes is especially important in older adults. Although approaches to classifying severity of individual diseases and conditions have been developed, the utility of these classification systems has not been evaluated in the presence of multiple conditions. Methods. We present a framework for evaluating severity classification systems for common chronic diseases. The framework evaluates the: (a) goal or purpose of the classification system; (b) physiological and/or functional criteria for severity graduation; and (c) potential reliability and validity of the system balanced against burden and costs associated with classification. Results. Approaches to severity classification of individual diseases were not originally conceived for the study of comorbidity. Therefore, they vary greatly in terms of objectives, physiological systems covered, level of severity characterization, reliability and validity, and costs and burdens. Using different severity classification systems to account for differing levels of disease severity in a patient with multiple diseases, or, assessing global disease burden may be challenging. Conclusions. Most approaches to severity classification are not adequate to address comorbidity. Nevertheless, thoughtful use of some existing approaches and refinement of others may advance the study of comorbidity and diagnostic and therapeutic approaches to patients with multimorbidity.
AB - Background. Accounting for the influence of concurrent conditions on health and functional status for both research and clinical decision-making purposes is especially important in older adults. Although approaches to classifying severity of individual diseases and conditions have been developed, the utility of these classification systems has not been evaluated in the presence of multiple conditions. Methods. We present a framework for evaluating severity classification systems for common chronic diseases. The framework evaluates the: (a) goal or purpose of the classification system; (b) physiological and/or functional criteria for severity graduation; and (c) potential reliability and validity of the system balanced against burden and costs associated with classification. Results. Approaches to severity classification of individual diseases were not originally conceived for the study of comorbidity. Therefore, they vary greatly in terms of objectives, physiological systems covered, level of severity characterization, reliability and validity, and costs and burdens. Using different severity classification systems to account for differing levels of disease severity in a patient with multiple diseases, or, assessing global disease burden may be challenging. Conclusions. Most approaches to severity classification are not adequate to address comorbidity. Nevertheless, thoughtful use of some existing approaches and refinement of others may advance the study of comorbidity and diagnostic and therapeutic approaches to patients with multimorbidity.
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U2 - 10.1093/gerona/62.3.286
DO - 10.1093/gerona/62.3.286
M3 - Article
C2 - 17389726
AN - SCOPUS:34248522807
SN - 1079-5006
VL - 62
SP - 286
EP - 295
JO - Journals of Gerontology - Series A Biological Sciences and Medical Sciences
JF - Journals of Gerontology - Series A Biological Sciences and Medical Sciences
IS - 3
ER -