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Review
. 2009 Jul-Aug;7(4):357-63.
doi: 10.1370/afm.983.

Defining comorbidity: implications for understanding health and health services

Affiliations
Review

Defining comorbidity: implications for understanding health and health services

Jose M Valderas et al. Ann Fam Med. 2009 Jul-Aug.

Abstract

Comorbidity is associated with worse health outcomes, more complex clinical management, and increased health care costs. There is no agreement, however, on the meaning of the term, and related constructs, such as multimorbidity, morbidity burden, and patient complexity, are not well conceptualized. In this article, we review definitions of comorbidity and their relationship to related constructs. We show that the value of a given construct lies in its ability to explain a particular phenomenon of interest within the domains of (1) clinical care, (2) epidemiology, or (3) health services planning and financing. Mechanisms that may underlie the coexistence of 2 or more conditions in a patient (direct causation, associated risk factors, heterogeneity, independence) are examined, and the implications for clinical care considered. We conclude that the more precise use of constructs, as proposed in this article, would lead to improved research into the phenomenon of ill health in clinical care, epidemiology, and health services.

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Figures

Figure 1.
Figure 1.
Chronologic aspects of comorbidity. Each block represents the duration of a different comorbid disease. Two comorbid diseases can either be present at the same point in time (vertical arrow), or occur within a given time period without being simultaneously present at any given point in that period (horizontal arrow) (a). Irrespective of the selected time span, the sequence in which the diseases appear is of particular interest in the study of etiological association (b).
Figure 2.
Figure 2.
Comorbidity constructs.
Figure 3.
Figure 3.
Etiological models of comorbid diseases. For ease of presentation, we have only considered 2 different diseases, and 2 corresponding risk factors. Each model relies on the interaction between either diseases or risk factors. The relationships described above apply both to protective factors and to risk factors.

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