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Value Health. 2010 Jan-Feb;13(1):138-47. doi: 10.1111/j.1524-4733.2009.00587.x. Epub 2009 Aug 20.

Relationships among self-management, patient perceptions of care, and health economic outcomes for decision-making and clinical practice in type 2 diabetes.

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Department of Health Policy & Management, Section of Health Economics-Medical Technology Assessment (HE-MTA), Erasmus MC, Erasmus University Rotterdam, The Netherlands.



Type 2 diabetes (T2D) treatment involves complex interactions between biological, psychological, and behavioral factors of care, requiring multifaceted efforts in clinical practice and disease management to reduce health and economic burdens. We aimed to quantify correlations among these factors and characterize their level of inclusion in economic analyses that are part of informed medical decision-making.


A comprehensive, stepwise systematic literature review was performed on published articles dated 1993 to 2008 using medical subject heading and keyword searches in electronic reference libraries. Data were collected using standardized techniques and were analyzed descriptively.


A total of 97 articles fulfilling all inclusion criteria were reviewed, including 16 on economic models (17% of articles). Most studies were retrospective (41 of 97; 42%) and from managed care perspectives (66%). Oral antidiabetic drugs were a central focus, appearing in 83% of studies. Patient behaviors, particularly medication adherence and persistence in real-world settings, are well researched (n=65) and may influence diabetes outcomes, cardiovascular risk, mortality rates, and treatment-specific resource use (e.g., hospitalizations) and costs (<or=$3400 annually per patient). Nevertheless, they are absent from current economic models.


Strong correlations exist between patient behaviors, perspectives of care, health outcomes, and costs in T2D. Enhancing their inclusion in pharmacoeconomic modeling, notably the influence on clinical effectiveness of variation in self-management between treatments, should ultimately lead to more accurate estimates of comparative cost-effectiveness, and thereby improve value-based resource allocation and patient access to appropriate therapy.

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