Feasibility of Using a Smart Phone Application for Self-titration of Insulin on Glycemic Control in Patients With T2DM
Condition: Diabetes Mellitus
Study type: Interventional

Summary: 
      The primary aim of this study is to investigate the feasibility of using a patient-centered
      smart phone application for insulin self-titration on glycemic control. Over a 18-month
      period, suboptimally controlled type 2 diabetes mellitus (T2DM) on oral antidiabetic agents,
      thus requiring insulin treatment patients, will be recruited from the Singapore General
      Hospital (SGH). Patients randomized to the intervention group will be instructed to
      self-adjust their insulin dose using a smart phone application designed to guide
      self-titration; patients randomized to the control group will receive the usual clinical
      care. The primary outcome measure is change in glycated hemoglobin level (HbA1c), 6 months
      post-enrollment. The investigators hypothesize that using a smart phone application for
      insulin self-titration is effective in improving glycemic control in T2DM patients compared
      with usual care.
    

Detailed description: 
      Background:

      Many patients with type 2 diabetes mellitus (T2DM) require insulin therapy after suboptimal
      glycemic control with oral antidiabetic agents. Initiating insulin therapy and adjusting
      dosage is vital in improving clinical outcomes among patients with diabetes. However, timely
      and appropriate dosage titration is challenging for many patients. Doctors also contend with
      many patients lacking the confidence to self-titrate insulin. Hence, reinforcing patients'
      self-empowerment is important in diabetes management. Developing tools that facilitate dosage
      adjustment of insulin may have substantial benefits to glycemic control.

      Objectives:

      The overall aim of this study is to investigate the feasibility of using a patient-centered
      smart phone application for insulin self-titration to improve glycemic control relative to
      usual care in patients with T2DM. The specific aim of the study is to determine the technical
      and clinical feasibility of a patient-centered smart phone application for insulin
      self-titration on glycemic control (HbA1c) of suboptimally controlled patients with T2DM who
      are starting insulin treatment.

      Study Design:

      This 24-week study is a randomized controlled trial that will involve participants recruited
      from Singapore General Hospital, a 1500-bed tertiary care hospital. The target population
      will consist of insulin naive patients with T2DM (30-70 years old) with suboptimal glycemic
      control (HbA1c ≥ 7.5%) while on oral antidiabetic agents.

      Sample Size:

      Eighty patients will be recruited in the study and randomized into either the intervention or
      control group in equal numbers (n=40) within strata defined by provider (i.e., within each of
      the five doctors). Patients will be nested within providers, and randomization within each
      provider will be performed in blocks of 4 subjects: 2 for the intervention and 2 for the
      control.

      Subject Selection:

      Eligible patients will be recruited over a 18-month period from the Singapore General
      Hospital. All patients newly initiated on insulin therapy will receive standard diabetes
      education from Diabetes Nurse Educators (DNEs). The research coordinator and doctors will
      work closely with the DNEs to identify eligible patients for this study. When a patient is
      eligible to participate in the study, the research coordinator will provide a study
      information brochure and explain the study design to the patient. Investigators will obtain
      an informed consent from patients prior to randomization.

      Intervention:

      Use of a smart phone application in self-titration of insulin

      Primary Outcome Variable:

      Difference in change in glycemic control (HbA1c) between the intervention and the control
      group

      Procedures:

      Recruited patients will receive once-daily injections of insulin detemir, a long-acting
      insulin, to be given at bedtime. The physicians are free to keep patients on all oral
      antidiabetic agents, except for thiazolidinediones. All recruited patients will receive free
      glucometers and test strips.

      Statistical Analysis:

      The primary analysis will be a comparison of mean reduction in HbA1c at 24 weeks
      post-randomization in the treatment and control groups in the context of a linear
      mixed-effects model with random effects for patients and doctors. The study is randomized, so
      baseline features and potential confounders should be approximately balanced between the
      treatment and control groups. However, the sample size is small (80 patients in total) so the
      mixed-effects model will be adjusted for covariates selected using forward stepwise variable
      selection with the AIC criterion. Potential covariates include age, gender, whether the
      patient themselves has a smart-phone, and treatment satisfaction.

      The mixed-effects model allows all non-missing data to be used in the analysis without
      imputation. However, for the estimate of the difference in reduction in HbA1c to be unbiased,
      it is required that the distribution of the data missingness conditional on the variables in
      the model and the observed data does not depend on the values of the missing data, so that
      the data is missing-at-random.This is a common and a reasonable assumption. However, it is
      possible that the analysis of attrition will indicate that additional covariates need to be
      included in the mixed-effects model. With the aim of developing a tailored analysis plan for
      a definitive study, a few additional models for comparison of mean reduction in HbA1c will
      also be considered. For example, a linear mixed-effects model with random slope and intercept
      for each patient and doctor which incorporates the intermediate HbA1c measurements for each
      patient will also be fit. It is unknown a priori whether such a model will have reduced power
      because of patients attaining equilibrium titration at different times or if such a model
      will have increased power because it uses more observations albeit on the same group of
      patients. Depending on the rate of attrition and whether attrition is related to covariates,
      a propensity score for missingness may be developed and models fit which are adjusted for or
      stratified by this score.

      The primary examination of efficacy will be through a linear mixed-effects model with random
      effects for each doctor and patient, under the assumption that the distribution of
      missingness conditional on the covariates and observed data does not depend on the missing
      data values. However, the investigators will examine several analyses for appropriateness
      including simple comparisons of the reductions in HbA1c between the treatment and control
      groups under last-observation-carried-forward, which is expected to be fairly conservative,
      and worst-observation-carried-forward, which is expected to be extremely conservative. What
      these methods lack in rigor may be offset by their simplicity.
    

Intervention name(s): Smart phone application
Intervention type(s): Device
Intervention description(s): The smart phone application (Diabetes Pal), will guide patients on self-titration of insulin. Patients will be required to key in the CBG readings into the application. Up-titration of insulin dose will be carried out once every 3 days and the recommended insulin dose will be based on the mean of 3 CBG readings and a pre-specified titration algorithm. The process of using the insulin self-titration application will continue until the patient has reached the target pre-breakfast CBG.
Allocation: Randomized
Intervention model: Parallel Assignment
Masking: None (Open Label)
Primary purpose: Health Services Research