PhD ceremony Mr. G.Sidorenkov: Predictive value of treatment quality indicators on outcomes in patients with diabetes
|When:||We 18-09-2013 at 14:30|
PhD ceremony: Mr. G.Sidorenkov, 14.30 uur, Academiegebouw, Broerstraat 5, Groningen
Dissertation: Predictive value of treatment quality indicators on outcomes in patients with diabetes
Promotor(s): prof. F.M. Haaijer-Ruskamp, prof. D. de Zeeuw
Faculty: Medical Sciences
Quality indicators are tools for measuring the quality of health care. An important requirement for measuring quality of care is credible evidence linking higher quality estimates to better patient outcomes. This thesis presents an overview of current knowledge and new findings about the relationship between indicators measuring the quality of drug treatment and outcomes in patients with diabetes. Although it may seem obvious that better treatment leads to better outcomes, quality indicators that are not correctly defined or indicators using wrong assumptions will not result in better outcomes, and may even stimulate suboptimal treatment. In this thesis, a number of treatment quality indicators are identified that are related to better patient outcomes. For example, the indicator measuring lipid-lowering treatment in patients with diabetes was associated with better cholesterol control and a lower risk of complications. Indicators measuring whether treatment was intensified when indicated were mainly associated with better short-term outcomes, e.g. HbA1c. There were also indicators that should be restricted to specific patients groups, for example, the indicators measuring the quality of glucose-lowering treatment. Finally, there were several indicators that were not related to better outcomes, especially the ones trying to measure the quality of blood pressure treatment. The important implication of this research is that some of the currently used or proposed quality indicators may stimulate care which is not equally beneficial for all patients. Therefore, quality of care indicators for diabetes may require restriction or stratification on patient characteristics, such as age or level of risk factor control.