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Treatment quality indicators predict short-term outcomes in patients with diabetes: a prospective cohort study using the GIANTT database


Objective To assess whether quality indicators for treatment of cardiovascular and renal risk factors are associated with short-term outcomes in patients with diabetes.

Design A prospective cohort study using linear regression adjusting for confounders.

Setting The GIANTT database (Groningen Initiative to Analyse Type 2 Diabetes Treatment) containing data from primary care medical records from The Netherlands.

Participants 15 453 patients with type 2 diabetes mellitus diagnosed before 1 January 2008. Mean age 66.5 years, 47.5% men.

Exposure Quality indicators assessing current treatment (CT) status or treatment intensification (TI) for patients with diabetes with elevated cardiovascular or renal risk factors.

Main outcome measures Low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), and albumin:creatinine ratio (ACR) before and after assessment of treatment quality.

Results Use of lipid-lowering drugs was associated with better LDL-C levels (−0.41 mmol/litre; 95% CI −0.48 to −0.34). Use of blood pressure-lowering drugs and use of renin–angiotensin system inhibitors in patients with elevated risk factor levels was not associated with better SBP and ACR outcomes, respectively. TI was also associated with better LDL-C (−0.82 mmol/litre; CI −0.93 to −0.71) in patients with elevated LDL-C levels, and with better SBP (−1.26 mm Hg; CI −2.28 to −0.24) in patients with two elevated SBP levels. Intensification of albuminuria-lowering treatment showed a tendency towards better ACR (−2.47 mmol/mg; CI −5.32 to 0.39) in patients with elevated ACR levels.

Conclusions Quality indicators of TI were predictive of better short-term cardiovascular and renal outcomes, whereas indicators assessing CT status showed association only with better LDL-C outcome.

  • Quality measurement
  • Diabetes mellitus
  • Health services research
  • Practice-based research network
  • Performance measures

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