Benefit of Digital Tools Used for Integrated Personalized Diabetes Management: Results From the PDM-ProValue Study Program.

BACKGROUND: Integrated personalized diabetes management (iPDM) is a digitally supported therapeutic concept to improve patient-physician interaction to overcome the aspects of clinical inertia. Integrated personalized diabetes management can support decision making and improve therapeutic outcomes of suboptimally controlled persons with insulin-treated type 2 diabetes (T2D). In this paper, we report the results of an analysis of the PDM-ProValue study program on the effectiveness and perceived benefit of this approach, with a focus on how physicians used and assessed the digital tools provided for the iPDM process. MATERIALS AND METHODS: The study program included two 12-month, prospective, controlled, cluster-randomized multicenter trials. A total of 101 practices participated with 907 patients. Practices were cluster-randomized to an intervention group and a control group. Digital tools for data visualization and analysis applied were used. HCP were asked to assess the use, relevance, and usefulness of the tools. RESULTS: A clear preference was stated for the visual overview over more statistically complex analyses. A total of 83% of the participants rated a high relevance of the "daily profile," 81% of the "total profile," and 68% the "risk illustrated by traffic light symbols" for the therapy decision. The overall iPDM process was very favorably rated with respect to structuredness and potential for personalized treatment and well accepted among health care professionals (HCP). CONCLUSIONS: Embedding digital tools in a structured process (iPDM) were proved to provide a benefit for insulin-treated T2D patients and their physicians. These results offer insight for further development and improvement of the tools and add information on how to overcome clinical inertia.

IT-supported integrated care pathways for diabetes: A compilation and review of good practices.

INTRODUCTION: Integrated Care Pathways (ICPs) are a method for the mutual decision-making and organization of care for a well-defined group of patients during a well-defined period. The aim of a care pathway is to enhance the quality of care by improving patient outcomes, promoting patient safety, increasing patient satisfaction, and optimizing the use of resources. To describe this concept, different names are used, e.g. care pathways and integrated care pathways. Modern information technologies (IT) can support ICPs by enabling patient empowerment, better management, and the monitoring of care provided by multidisciplinary teams. This study analyses ICPs across Europe, identifying commonalities and success factors to establish good practices for IT-supported ICPs in diabetes care. METHODS: A mixed-method approach was applied, combining desk research on 24 projects from the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) with follow-up interviews of project participants, and a non-systematic literature review. We applied a Delphi technique to select process and outcome indicators, derived from different literature sources which were compiled and applied for the identification of successful good practices. RESULTS: Desk research identified sixteen projects featuring IT-supported ICPs, mostly derived from the EIP on AHA, as good practices based on our criteria. Follow-up interviews were then conducted with representatives from 9 of the 16 projects to gather information not publicly available and understand how these projects were meeting the identified criteria. In parallel, the non-systematic literature review of 434 PubMed search results revealed a total of eight relevant projects. On the basis of the selected EIP on AHA project data and non-systematic literature review, no commonalities with regard to defined process or outcome indicators could be identified through our approach. Conversely, the research produced a heterogeneous picture in all aspects of the projects' indicators. Data from desk research and follow-up interviews partly lacked information on outcome and performance, which limited the comparison between practices. CONCLUSION: Applying a comprehensive set of indicators in a multi-method approach to assess the projects included in this research study did not reveal any obvious commonalities which might serve as a blueprint for future IT-supported ICP projects. Instead, an unexpected high degree of heterogeneity was observed, that may reflect diverse local implementation requirements e.g. specificities of the local healthcare system, local regulations, or preexisting structures used for the project setup. Improving the definition of and reporting on project outcomes could help advance research on and implementation of effective integrated care solutions for chronic disease management across Europe.

Use of an integrated strip-free blood glucose monitoring system increases frequency of self-monitoring and improves glycemic control: Results from the ExAct study.

AIMS: We investigated the impact of using an integrated, strip-free system compared to the use of single-strip systems on testing frequency and glycemic control in individuals with insulin-treated diabetes. METHODS: This multinational, comparative, cluster-randomized, observational study included 311 patients with type 1 and insulin-treated type 2 diabetes who were performing SMBG at suboptimal frequencies. Sites were cluster-randomized to "integrated strip-free" system (EXP group) or any "single-strip" system (CNL group). Testing frequency and HbA1c were measured at baseline, 12 weeks and 24 weeks. RESULTS: At week 24, the EXP group showed an increase in SMBG frequency from baseline of 4.17 tests/week (95% CI 2.76, 5.58) compared with an increase of 0.53 tests/week (95% CI -0.73, 1.79) among CNL patients, resulting in a between-group difference of 3.63 tests/week (p < 0.0002). Mixed-effects models for repeated measurements (MMRM) controlling for baseline frequency of testing, country and clinical site confirmed a higher SMBG testing frequency in the EXP group compared to the CNL group, with a between-group difference of 2.70 tests/week (p < 0.01). Univariate analysis showed greater HbA1c reductions in the EXP group than CNL group: -0.44% (95% CI -0.59, -0.29) vs. -0.13% (95% CI -0.27, 0.01), respectively, p < 0.0002. MMRM analyses confirmed these HbA1c reductions. A greater percentage of EXP than CNL patients achieved HbA1c reductions of ≥0.5%: 45.1% vs. 29.1%, respectively, p < 0.01. CONCLUSIONS: The use of an integrated, strip-free SMBG system improved testing adherence and was associated with improvements in glycemic control.

Self-adjustment of insulin dose using graphically depicted self-monitoring of blood glucose measurements in patients with type 1 diabetes mellitus.

BACKGROUND: There is a need for patients to be able to adjust their insulin doses accurately and independently during continuous subcutaneous insulin infusion (CSII) therapy in order to avoid glycemic excursions and improve glycemic control. Use of new technology has the potential to aid patients in visualizing their circadian patterns and improving their understanding of data provided by self-monitored blood glucose (SMBG) measurements. METHODS: A 24-week crossover study was performed in 25 patients with type 1 diabetes mellitus using CSII and SMBG. Patients were randomized either to entering blood glucose data into handwritten logbooks or to using the Accu-Chek SmartPix information management system (IMS) coupled with instructions from a training manual to aid interpretation of the IMS readings. Patients analyzed these chart readings every 2 weeks, and outpatient visits were scheduled for both arms every 6 weeks. RESULTS: There was a significantly lower mean overall blood glucose level with the IMS compared with use of a logbook (139 ± 16.2 versus 150 ± 19.8 mg/dl; Δ = 10.8 mg/dl; p < .01), and a significantly higher proportion of blood glucose values was in the target range compared with use of a logbook (43.6% versus 38.5%; p < .001). Hypoglycemic events were also significantly lower with the IMS compared with logbooks (3.7 fewer events/6 weeks; p < .05). There was no significant difference between groups in the daily frequency of SMBG measurements. CONCLUSIONS: The use of an IMS, coupled with an easily understood training manual, enables patients to improve glycemic control by performing accurate and timely self-adjustments to their insulin regimens.

Changes in A1C levels are significantly associated with changes in levels of the cardiovascular risk biomarker hs-CRP: results from the SteP study.

OBJECTIVE: The effect of therapeutic strategies on cardiovascular (CV) disease can be evaluated by monitoring changes in CV risk biomarkers. This study investigated the effect of a structured self-monitoring of blood glucose (SMBG) protocol and the resulting improvements in glycemic control on changes in high-sensitivity C-reactive protein (hs-CRP) in insulin-naïve patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: The Structured Testing Program (STeP) study was a prospective, cluster-randomized, multicenter trial in which 483 poorly controlled, insulin-naïve patients with type 2 diabetes were randomized to active control (ACG) or structured testing (STG) that included quarterly structured SMBG. Changes in A1C, hs-CRP, and glycemic variability (STG subjects only) were measured at baseline and quarterly. RESULTS: Reductions in geometric mean hs-CRP values were significantly greater in the STG group at months 3 (P = 0.005), 6 (P = 0.0003), and 12 (P = 0.04) than in the ACG group. STG patients at high CV risk (>3 mg/L) showed significantly greater reductions in hs-CRP levels than ACG patients at high CV risk: -3.64 mg/dL (95% CI -4.21 to -3.06) versus -2.18 mg/dL (-2.93 to -1.43), respectively (P = 0.002). There was a strong correlation between reductions in hs-CRP and A1C in both groups: standardized coefficient (ß) was 0.25 for the entire cohort (P < 0.0001), 0.31 for STG (P < 0.0001), and 0.16 for ACG (P = 0.02). CONCLUSIONS: Reductions in hs-CRP level are associated with reductions in A1C but not reductions in lipids or glycemic variability. Comprehensive structured SMBG-based interventions that lower A1C may translate into improvements in CV risk, as evidenced by levels of the biomarker hs-CRP.