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Background: Numerous diabetes-management systems and programs for improving glycemic control to meet guideline targets have been proposed, using IT technology. But all of them allow only limited—or no—real-time interaction between patients and the system in terms of system response to patient input; few studies have effectively assessed the systems’ usability and feasibility to determine how well patients understand and can adopt the technology involved. Method: DialBetics is composed of 4 modules: (1) data transmission module, (2) evaluation module, (3) communication module, and (4) dietary evaluation module. A 3-month randomized study was designed to assess the safety and usability of a remote health-data monitoring system, and especially its impact on modifying patient lifestyles to improve diabetes self-management and, thus, clinical outcomes. Fifty-four type 2 diabetes patients were randomly divided into 2 groups, 27 in the DialBetics group and 27 in the non-DialBetics control group. Results: HbA1c and fasting blood sugar (FBS) values declined significantly in the DialBetics group: HbA1c decreased an average of 0.4% (from 7.1 ± 1.0% to 6.7 ± 0.7%) compared with an average increase of 0.1% in the non-DialBetics group (from 7.0 ± 0.9% to 7.1 ± 1.1%) ( P = .015); The DialBetics group FBS decreased an average of 5.5 mg/dl compared with a non-DialBetics group average increase of 16.9 mg/dl ( P = .019). BMI improvement—although not statistically significant because of the small sample size—was greater in the DialBetics group. Conclusions: DialBetics was shown to be a feasible and an effective tool for improving HbA1c by providing patients with real-time support based on their measurements and inputs.

Self-management is a key component of diabetes therapy.1 We developed a real-time partially automated interactive system—DialBetics—to achieve diabetes self-management. This is the first system combining information technology and natural language processing (NLP) that performs real-time automated text communication with patients, increasing their convenience while minimizing health care providers’ workload and cost.2 A pilot study was conducted to assess the safety, usability, and impact of remote health-data monitoring on patient hemoglobin A1c (HbA1c) outcomes and the effect of home blood pressure monitoring as a way of managing the complications related to diabetes.3 DialBetics comprises three modules: Data transmission—patients’ blood glucose, blood pressure, body weight, and pedometer counts are measured at home and sent to the server twice a day. Evaluation—data are automatically evaluated following the Japan Diabetes Society (JDS) guideline’s targeted values—optimally, blood sugar 10,000. It determines if each reading satisfies guideline requirements then sends results to each patient’s smartphone. Abnormal readings—defined as blood sugar >400 mg/dl or 220 mm Hg—are reported as “Dr. Call,” meaning a physician will check the data and interact with the patient if necessary. Communication (a) patients’ voice/text messages about meals and exercise are sent to the server; (b) messages by voice are converted to text and matched with text in the system’s database; (c) advice on lifestyle modification, matched to the patients’ input about diet and exercise, is returned to each patient (Figure 1). Figure 1 An overview of DialBetics. For (b) and (c), the NLP-based disambiguate system allows our system to choose database words with high agreement rates for the patients’ input.4 Eleven patients who had been diagnosed with type 2 diabetes more than 5 years ago were recruited from a university hospital for a 1 month pilot study (age 61.9 ± 8.7 years, body mass index 24.6 ± 4.5 kg/m2, and HbA1c 6.79 ± 0.58%). To be eligible, patients had to be free of any severe complications—serum creatinine below 1.5 mg/dl, no proliferative retinopathy—and had to be able to exercise. Eligible patients gave consent, and the study was approved by the Institutional Review Board. DialBetics was found accurate and safe in data transmission, evaluation, and text communication for patients whose HbA1c was around 7%. All subjects were satisfied with it and were enthusiastic about receiving real-time advice on lifestyle modification. Mean HbA1c significantly decreased 0.26% after 1 month (HbA1c 6.53 ± 0.84%, p = .02). The message processing success rate was 73.6%, which can be improved by expanding the database. Notably, it showed eight patients that their mean blood pressures did not meet the JDS goal for hypertension therapy. Because no readings were defined as “Dr. Call,” a physician’s time was not required. The study suggested that not only blood glucose monitoring but also home blood pressure monitoring might improve care of diabetes by revealing uncontrolled blood pressure, which was frequently overlooked in regular hospital visits. We plan to validate these study findings in the larger randomized controlled trial with a longer duration (in progress).