Background: Overseeing proper insulin initiation and titration remains a challenging task in diabetes care. Recent advances in mobile technology have enabled new models of collaborative care between patients and healthcare providers (HCPs). We hypothesized that the adoption of such technology could help individuals starting basal insulin achieve better glycemic control compared with standard clinical practice.Materials and Methods: This was a 12 ± 2-week randomized controlled study with 40 individuals with type 2 diabetes who were starting basal insulin due to poor glycemic control. The control group (n = 20) received standard face-to-face care and phone follow-up as needed in a tertiary center, whereas the intervention group (n = 20) received care through the cloud-based diabetes management program where regular communications about glycemic control and insulin doses were conducted via patient self-tracking tools, shared decision-making interfaces, secure text messages, and virtual visits (audio, video, and shared screen control) instead of office visits.Results: By intention-to-treat analysis, the intervention group achieved a greater hemoglobin A1c decline compared with the control group (3.2 ± 1.5% vs. 2.0% ± 2.0%; P = 0.048). The Diabetes Treatment Satisfaction Questionnaire showed a significant improvement in the intervention group compared with the control group (an increase of 10.1 ± 11.7 vs. 2.1 ± 6.5 points; P = 0.01). HCPs spent less time with patients in the intervention group compared with those in the control group (65.9 min per subject vs. 81.6 min per subject). However, the intervention group required additional training time to use the mobile device.Conclusions: Mobile health technology could be an effective tool in sharing data, enhancing communication, and improving glycemic control while enabling collaborative decision making in diabetes care.

In this paper we address the problem of patient adherence to physical therapy using a sensor-enabled virtual reality gaming interface that motivates users to complete their exercises while collecting quantitative data. The system also allows the therapist to monitor and interact with patients remotely providing reinforcing feedback and support with the CollaboRhythm care delivery platform. The data collected with this system enables the therapist and the patient to make informed decisions about patient treatment and exercise regimens based on the patient progress. The system is capable of supporting a wide array of rehabilitation scenarios with remote collaboration. A knee replacement scenario was tested with an experimental protocol involving 16 healthy participants. The results show both quantitatively and qualitatively that patients can learn intuitively to perform their physical therapy exercises on a remote environment without further human intervention.

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