Integrated Personalized Diabetes Management (PDM)

Author:

Kulzer Bernhard1,Daenschel Wilfried2,Daenschel Ingrid3,Siegel Erhard G.4,Schramm Wendelin5,Parkin Christopher G.6,Messinger Diethelm7,Weissmann Joerg8,Djuric Zdenka8,Mueller Angelika8,Vesper Iris8,Heinemann Lutz9

Affiliation:

1. Forschungsinstitut Diabetes Akademie Bad Mergentheim, Bad Mergentheim, Germany

2. Ärztlicher Leiter Medizinisches Versorgungszentrums am Küchwald GmbH, Chemnitz, Germany

3. Hausarztpraxis, Lunzenau, Germany

4. St. Josefskrankenhaus Heidelberg, Heidelberg, Germany

5. GECKO Institute for Medicine, Informatics and Economics, Heilbronn University, Heilbronn, Germany

6. CGParkin Communications, Inc, Boulder City, NV, USA

7. Biometrics Department, IST GmbH, Mannheim, Germany

8. Roche Diabetes Care GmbH, Mannheim, Germany

9. Science & Co, Düsseldorf, Germany

Abstract

Background: Collaborative use of structured self-monitoring of blood glucose (SMBG) data and data management software, utilized within a 6-step cycle enables integrated Personalized Diabetes Management (PDM). The 2 PDM-ProValue studies shall assess the effectiveness of this approach in improving patient outcomes and practice efficiencies in outpatient settings. Methods: The PDM-ProValue studies are 12-month, prospective, cluster-randomized, multicenter, trials to determine if use of integrated PDM in daily life improves glycemic control in insulin-treated type 2 diabetes patients. Fifty-four general medical practices (GPs) and 36 diabetes-specialized practices (DSPs) across Germany will be recruited. The practices will be randomly assigned to the control groups (CNL) or the intervention groups (INT) via cluster-randomization. CNL practices will continue with their usual care; INT practices will utilize integrated PDM. The sample size is 1,014 patients (n = 540 DSP patients, n = 474 GP patients). Each study is designed to detect a between-group difference in HbA1c change of at least 0.4% at 12 months with a power of 90% and 2-sided significance level of .05. Differences in timing and degree of treatment adaptions, treatment decisions, blood glucose target ranges, hypoglycemia, self-management behaviors, quality of life, patients attitudes, clinician satisfaction, practice processes, and resource consumption will be assessed. Study endpoints will be analyzed for the modified intent-to-treat and per protocol populations. Trial results are expected to be available in late 2016. Discussion: Effective and efficient strategies to optimize diabetes management are needed. These randomized studies will help determine if PDM is beneficial.

Publisher

SAGE Publications

Subject

Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine

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