Bernhard Kulzer1, Wilfried Daenschel2, Ingrid Daenschel3, Erhard G Siegel4, Wendelin Schramm5, Christopher G Parkin6, Diethelm Messinger7, Joerg Weissmann8, Zdenka Djuric8, Angelika Mueller8, Iris Vesper8, Lutz Heinemann9. 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 chris@cgparkin.org. 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.
RCT Entities:
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 diabetespatients. 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.
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