DIgital Assisted MONitoring for DiabeteS - I
Condition: Diabetes Mellitus
Study type: Interventional

Summary: 
      The study aims to validate the clinical efficacy of a telemedicine- and web-based system
      platform for Self-monitoring of blood glucose (SMBG) data transmission and analysis in terms
      of improved metabolic control, assessed by measuring changes in HbA1c, in insulin-treated
      diabetic patients. The system platform involves (i.) systematic (real-time and anywhere)
      transmission of SMBG data to a decision supported software (DSS)-assisted server, (ii.)
      web-based analysis of data, and (iii.) feedback on patients and medical staff to implement
      metabolic control. The expected outcome is that using this telemedicine-based system with
      transmission of SMBG data, web-based analysis of data and medical feedback to patients and
      medical team will improve glucose control in insulin-treated individuals with type 1 or type
      2 diabetes mellitus.
    

Detailed description: 
      Self-monitoring of blood glucose (SMBG) is currently recommended in all type 1 diabetic
      patients and type 2 diabetic treated with insulin (≥4 glucose testing per day), as a tool to
      favor achievement of glucose control. It is still debated whether SMBG is also useful to
      achieve improved glucose control in non-insulin treated type 2 diabetes due to discordant
      results from intervention trials [Farmer AJ, 2009]. In general, it is assumed that the
      usefulness of SMBG is fully met when SMBG is performed in a structured manner, and both the
      patient and medical team make use of the SMBG results to optimize lifestyle and drug therapy;
      this should result in more effective control of both hyperglycemia and hypoglycemia,
      resulting in less glucose variability [IDF, 2009]. SMBG is currently performed by a majority
      of diabetic patients, including non-insulin treated type 2 patients; however, the SMGB
      procedure is often far from being satisfactory due to inappropriate frequency of testing,
      data collection and data analysis, resulting in a suboptimal impact on disease management.
      Thus, multiple unmet needs currently exist in the SMBG procedure, which could be resolved by
      (i.) implementing appropriate SMBG testing frequencies (# blood glucose (BG)
      tests/day-week-month); (ii.) temporally localizing BG tests with respect to fasting periods
      vs. meals/snacks; (iii.) improving the quality control of the SMBG procedure (use of strips,
      calibration, testing, data collection and analysis); (iv.) making SMBG results available for
      statistical and medical analyses to monitor diabetes status and adjust lifestyle and drug
      therapy when needed; (v.) providing the patient with appropriate feed-back driven by SMBG
      data analysis; and (vi.) monitoring real-time SMBG data to detect emergency situations (e.g.,
      severe hypoglycemia, persistent hyperglycemia) to assist the patient with appropriate and
      timely interventions.

      There is a growing body of evidence to suggest that telemedicine is an effective intervention
      for improving glucose control. Use of telephone contacts, video-conferencing, personal
      digital assistants and web-based systems offer new opportunities to bridge the gap in support
      for patients with diabetes between face to face visits with their health care providers.
      Several small-scale and non-randomized studies have found that patients exposed to
      telemonitoring interventions had lower HbA1c values than those without. Moreover, larger
      randomized controlled studies have also shown promising results. In the most comprehensive
      randomized comparison of telemonitoring interventions yet completed, the IDEATel study, 1,665
      participants were randomized to a telemedicine unit or conventional care. At 1 year, patients
      in intervention group showed significantly lower HbA1c (-0.38 % p<0.01), systolic and
      diastolic blood pressure, (respectively, -3.4 mmHg, p= 0.001; -1.9 mmHg, p<0.001), and low
      density lipoprotein (LDL) cholesterol (-9.5 mg/dL, p< 0.001). In patients blindly assessed
      annually over a period of five years, it was found that the telemedicine group scored better
      than the standard care group on virtually all outcome measures at each annual evaluation.
      Mortality was not different between the groups, although power was limited [Shea S, 2009].
      More recently, Charpentier et al., in a six-month multicenter study, enrolled 180 adult
      patients with type 1 diabetes on a basal-bolus insulin regimen, with baseline HbA1c ≥8%.
      Patients were randomized to either usual quarterly follow-up, or home use of a smartphone
      recommending insulin doses with quarterly visits, or use of the smartphone with short
      teleconsultations every two weeks but no visit until endpoint (Diabeo system). Use of the
      Diabeo system yielded a 0.91% decrease in HbA1c over controls and a 0.67% decrease in HbA1c
      when used without teleconsultation. There was no difference in the frequency of hypoglycemic
      episodes or in medical time spent for hospital or telephone consultations. However, patients
      using the Diabeo system spent nearly 5 h less than patients in other groups in attending
      hospital visits [Charpentier G, 2011]. Similarly, Bujnowska-Fedak et al enrolled a total of
      100 adult patients with type 2 diabetes, divided between insulin- and non-insulin-requiring,
      in a randomized, controlled trial aimed at investigating the effects of telehome monitoring.
      The experimental group (n = 50) received an in-home wireless glucose monitor and transmitter,
      whereas the control group (n = 50) was instructed to follow the conventional arrangement.
      There was an overall reduction in HbA1c values in both experimental and control groups after
      6 months. A significant difference in HbA1c values between the groups was observed only among
      the noninsulin-requiring patients. The experimental group reported considerably less
      hyperglycemic and hypoglycemic events. The profile of the patient who benefited the most from
      telemonitoring consisted of older, more educated patients, who had acquired the disease
      relatively recently, and who spent most of the time at home. The experimental group had
      higher overall scores on quality of life measures and sense of control over diabetes
      [Bujnowska-Fedak MM, 2011]. A recent meta-analysis of 22 trials and a total of 1,657
      participants showed that mobile phone interventions for diabetes self-management reduced
      HbA1c values by a mean of 0.5% over a median of 6-month follow-up duration. Interestingly,
      type 2 diabetes patients reported significantly greater reductions in HbA1c than type 1
      diabetes patients (0.8 vs. 0.3%; P = 0.02) [Liang X, 2011]. In conclusion, telemedicine case
      management intervention and tele-home care may potentially assist in daily diabetes
      management via the establishment of an active interaction between diabetic patients and
      healthcare professionals. However, further evidence is warranted, particularly when
      considering new innovative systems with a potential for implementation of patient's
      assistance and of diabetes drug therapy remotely.

      We have recently developed a telemedicine system [Glucoonline®, 2011], which consists of a
      smartphone-connected glucometer, a software-implemented smartphone for real-time and anywhere
      BG data collection and transmission to a remote server, and a Decision Supported Software
      (DSS)-assisted server capable of performing data collection and analysis, and providing
      feed-back to the patient and the medical staff according to pre-defined specific algorithms.
      A pilot study showing the feasibility of using this system in 10 individuals with type 1
      diabetes treated with a multiple daily injection (MDI) regimen over a 3-month period has been
      already carried out [Giorgino F, data on file]. We believe that this system could be now
      utilized in a prospective randomized controlled trial to investigate its suitability to
      enable improved glucose control in insulin-treated individuals with type 1 or type 2 diabetes
      mellitus.
    

Intervention name(s): Use of software-implemented glucometer for real-time collection and transmission of measured glucose values to remote server.; Use of regular glucometer
Intervention type(s): Procedure; Procedure
Intervention description(s): Device is a smartphone-connected glucometer. The smartphone will be implemented with a software for real-time collection and transmission of measured glucose values to the remote server. Thus, the glucometer will be made "hot" for real-time and anywhere data transmission. In addition, at the time of blood glucose measuring, the patient will enter information on whether the measurement is being performed in the pre-prandial, post-prandial or absorptive periods, and will indicate which meals the measurement refers to (i.e., breakfast, lunch, dinner, snack). SMBG results will be immediately transmitted to the remote server, which will perform data collection and analysis, and provide feed-back to the patient and the medical staff according to pre-defined specific algorithms (Decision Supported Software, DSS).
Allocation: Randomized
Intervention model: Parallel Assignment
Masking: None (Open Label)
Primary purpose: Treatment
Keywords: glycated hemoglobin; hyperglycemia; hypoglycemia; insulin; self-monitoring of blood glucose; telemedicine