Literature DB >> 21568751

A structured self-monitoring of blood glucose approach in type 2 diabetes encourages more frequent, intensive, and effective physician interventions: results from the STeP study.

William H Polonsky1, Lawrence Fisher, Charles H Schikman, Deborah A Hinnen, Christopher G Parkin, Zhihong Jelsovsky, Matthias Axel-Schweitzer, Bettina Petersen, Robin S Wagner.   

Abstract

BACKGROUND: We evaluated how a structured patient/physician self-monitoring of blood glucose (SMBG) intervention influenced the timing, frequency, and effectiveness of primary care physicians' treatment changes with type 2 diabetes mellitus (T2DM) patients over 12 months.
METHODS: The Structured Testing Program (STeP) study was a cluster-randomized, multicenter trial with 483 poorly controlled, insulin-naive T2DM subjects. Primary care practices were randomized to the Active Control Group (ACG) or the Structured Testing Group (STG), the latter of which included quarterly review of structured SMBG results. STG patients used a paper tool that graphs seven-point glucose profiles over 3 consecutive days; physicians received a treatment algorithm based on SMBG patterns. Impact of structured SMBG on physician treatment modification recommendations (TMRs) and glycemic outcomes was examined.
RESULTS: More STG than ACG patients received a TMR at each study visit (P < 0.0001). Of patients who received at least one TMR, STG patients demonstrated a greater reduction in glycated hemoglobin A1c (HbA1c) than ACG patients (-1.2% vs. -0.8%, P < 0.03). Patients with a baseline HbA1c ≥8.5% who received a TMR at the Month 1 visit experienced greater reductions in HbA1c (P = 0.002) than patients without an initial TMR. More STG than ACG patients were started on incretins (P < 0.01) and on thiazolidinediones (P = 0.004). The number of visits with a TMR was unrelated to HbA1c change over time.
CONCLUSIONS: Patient-provided SMBG data contribute to glycemic improvement when blood glucose patterns are easy to detect, and well-trained physicians take timely action. Collaborative use of structured SMBG data leads to earlier, more frequent, and more effective TMRs for poorly controlled, non-insulin-treated T2DM subjects.

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Year:  2011        PMID: 21568751     DOI: 10.1089/dia.2011.0073

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  35 in total

1.  Accuracy and User Performance Evaluation of a New, Wireless-enabled Blood Glucose Monitoring System That Links to a Smart Mobile Device.

Authors:  Timothy S Bailey; Jane F Wallace; Scott Pardo; Mary Ellen Warchal-Windham; Bern Harrison; Robert Morin; Mark Christiansen
Journal:  J Diabetes Sci Technol       Date:  2017-02-01

2.  A new test strip technology platform for self-monitoring of blood glucose.

Authors:  Robert Bernstein; Joan Lee Parkes; Amy Goldy; Daniel Brown; Bern Harrison; Amy Chu; Brian K Pflug; David A Simmons; Scott Pardo; Timothy S Bailey
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

3.  Impact on Diabetes Self-Management and Glycemic Control of a New Color-Based SMBG Meter.

Authors:  Oliver Schnell; Gerd Klausmann; Bettina Gutschek; Rosa Maria Garcia-Verdugo; Michael Hummel
Journal:  J Diabetes Sci Technol       Date:  2017-04-26

Review 4.  Self-monitoring of blood glucose: one STeP forward?

Authors:  Wendelin Schramm
Journal:  J Diabetes Sci Technol       Date:  2012-07-01

Review 5.  Blood glucose pattern management in diabetes: creating order from disorder.

Authors:  Pratik Choudhary; Stefano Genovese; Gérard Reach
Journal:  J Diabetes Sci Technol       Date:  2013-11-01

6.  Utilization of blood glucose data in patient education.

Authors:  Yaa Kumah-Crystal; Shelagh Mulvaney
Journal:  Curr Diab Rep       Date:  2013-12       Impact factor: 4.810

Review 7.  Self-monitoring of blood glucose in diabetes: from evidence to clinical reality in Central and Eastern Europe--recommendations from the international Central-Eastern European expert group.

Authors:  Leszek Czupryniak; László Barkai; Svetlana Bolgarska; Agata Bronisz; Jan Broz; Katarzyna Cypryk; Marek Honka; Andrej Janez; Mladen Krnic; Nebojsa Lalic; Emil Martinka; Dario Rahelic; Gabriela Roman; Tsvetalina Tankova; Tamás Várkonyi; Bogumił Wolnik; Nadia Zherdova
Journal:  Diabetes Technol Ther       Date:  2014-04-09       Impact factor: 6.118

8.  A Post-Marketing Surveillance Study to Evaluate Performance of the EXIMO™ Blood Glucose Monitoring System.

Authors:  Sonia R Chandnani; C D Ramakrishna; Bhargav A Dave; Pankaj S Kothavade; Ashok S Thakkar
Journal:  J Clin Diagn Res       Date:  2017-05-01

9.  Translating What Works: A New Approach to Improve Diabetes Management.

Authors:  Lawrence S Phillips; Diana Barb; Chun Yong; Anne M Tomolo; Sandra L Jackson; Darin E Olson; Mary K Rhee; Ingrid M Duva; Qing He; Qi Long
Journal:  J Diabetes Sci Technol       Date:  2015-03-09

10.  Evaluation of a blood glucose monitoring system with automatic high- and low-pattern recognition software in insulin-using patients: pattern detection and patient-reported insights.

Authors:  Mike Grady; Denise Campbell; Kirsty MacLeod; Aparna Srinivasan
Journal:  J Diabetes Sci Technol       Date:  2013-07-01
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