Clinical evaluation of IDAS II, a new electronic device enabling drug adherence monitoring

Objective: The goal of this study was to evaluate clinically the acceptability of the IDAS II (Intelligent Drug Administration System), a new electronic device that enables drug adherence monitoring. Methods: IDAS II was compared to another electronic monitor, the Medication Event Monitoring System (MEMS) in a randomised two-way cross-over study involving 24 hypertensive patients treated with irbesartan. Patients used each device for 2months. The main parameter of evaluation was the patients' opinion on both devices. Rates of adherence and blood pressure were also assessed. Results: Most patients considered both devices to be reliable reminders (IDAS II: 75%;MEMS: 84%, p = ns). Ten patients (42%) preferred the MEMS, while 11 (46%) preferred the IDAS II; three (12%) expressed no preference. Patients found the MEMS device easier to use than the IDAS device (p < 0.001) but appreciated the IDAS blister packs better than the MEMS bulk packaging (p < 0.01). Over the 4-month period, the median "taking adherence” was excellent (99.2%) and comparable with both devices. However, the regularity of drug intake timing was higher with the IDAS II (p < 0.01). Conclusion: IDAS II, a new electronic device enabling drug adherence monitoring without reconditioning of the drugs appears to be a well-accepted device. Overall, practicability and acceptability of the IDAS II and the MEMS device were similar. Thus, IDAS II could be a useful tool for the management of long-term therapie

eHealth profile of patients with diabetes.

BACKGROUND Digital health technology can be useful to improve the health of patients with diabetes and to support patient-centered care and self-management. In this cross-sectional study, we described the eHealth profile of patients with diabetes, based on their use of digital health technology, and its association with sociodemographic characteristics. METHODS We used data from the "Qualité Diabète Valais" cohort study, conducted in one region of Switzerland (Canton Valais) since 2019. Participants with type 1 or type 2 diabetes completed questionnaires on sociodemographic characteristics and on the use of digital health technology. We defined eHealth profiles based on three features, i.e., ownership or use of (1) internet-connected devices (smartphone, tablet, or computer), (2) mHealth applications, and (3) connected health tools (activity sensor, smart weight scale, or connected blood glucose meter). We assessed the association between sociodemographic characteristics and participants' eHealth profiles using stratified analyses and logistic regression models. RESULTS Some 398 participants (38% women) with a mean age of 65 years (min: 25, max: 92) were included. The vast majority (94%) were Swiss citizens or bi-national and 68% were economically inactive; 14% had a primary level education, 51% a secondary level, and 32% a tertiary level. Some 75% of participants had type 2 diabetes. Some 90% of the participants owned internet-connected devices, 43% used mHealth applications, and 44% owned a connected health tool. Older age and a lower educational level were associated with lower odds of all features of the eHealth profile. To a lesser extent, having type 2 diabetes or not being a Swiss citizen were also associated with a lower use of digital health technology. There was no association with sex. CONCLUSION While most participants owned internet-connected devices, only about half of them used mHealth applications or owned connected health tools. Older participants and those with a lower educational level were less likely to use digital health technology. eHealth implementation strategies need to consider these sociodemographic patterns among patients with diabetes

A systems approach towards remote health-monitoring in older adults: Introducing a zero-interaction digital exhaust.

Using connected sensing devices to remotely monitor health is a promising way to help transition healthcare from a rather reactive to a more precision medicine oriented proactive approach, which could be particularly relevant in the face of rapid population ageing and the challenges it poses to healthcare systems. Sensor derived digital measures of health, such as digital biomarkers or digital clinical outcome assessments, may be used to monitor health status or the risk of adverse events like falls. Current research around such digital measures has largely focused on exploring the use of few individual measures obtained through mobile devices. However, especially for long-term applications in older adults, this choice of technology may not be ideal and could further add to the digital divide. Moreover, large-scale systems biology approaches, like genomics, have already proven beneficial in precision medicine, making it plausible that the same could also hold for remote-health monitoring. In this context, we introduce and describe a zero-interaction digital exhaust: a set of 1268 digital measures that cover large parts of a person's activity, behavior and physiology. Making this approach more inclusive of older adults, we base this set entirely on contactless, zero-interaction sensing technologies. Applying the resulting digital exhaust to real-world data, we then demonstrate the possibility to create multiple ageing relevant digital clinical outcome assessments. Paired with modern machine learning, we find these assessments to be surprisingly powerful and often on-par with mobile approaches. Lastly, we highlight the possibility to discover novel digital biomarkers based on this large-scale approach

Immunosuppressive therapy after solid-organ transplantation: does the INTERMED identify patients at risk of poor adherence?

Lack of adherence to medication is a trigger of graft rejection in solid-organ transplant (SOT) recipients. This exploratory study aimed to assess whether a biopsychosocial evaluation using the INTERMED instrument before transplantation could identify SOT recipients at risk of suboptimal post-transplantation adherence to immunosuppressant drugs. We hypothesized that complex patients (INTERMED&gt;20) might have lower medication adherence than noncomplex patients (INTERMED≤20). Each patient eligible for transplantation at the University Hospital of Lausanne, Switzerland, has to undergo a pre-transplantation psychiatric evaluation. In this context the patient was asked to participate in our study. The INTERMED was completed pre-transplantation, and adherence to immunosuppressive medication was monitored post-transplantation by electronic monitors for 12 months. The main outcome measure was the implementation and persistence to two calcineurin inhibitors, cyclosporine and tacrolimus, according to the dichotomized INTERMED score (&gt;20 or ≤20). Among the 50 SOT recipients who completed the INTERMED, 32 entered the study. The complex (N=11) and noncomplex patients (N=21) were similar in terms of age, sex and transplanted organ. Implementation was 94.2% in noncomplex patients versus 87.8% in complex patients (non-significant p-value). Five patients were lost to follow-up: one was non-persistent, and four refused electronic monitoring. Of the four patients who refused monitoring, two were complex and withdrew early, and two were noncomplex and withdrew later in the study. Patients identified as complex pre-transplant by the INTERMED tended to deviate from their immunosuppressant regimen, but the findings were not statistically significant. Larger studies are needed to evaluate this association further, as well as the appropriateness of using a nonspecific biopsychosocial instrument such as INTERMED in highly morbid patients who have complex social and psychological characteristics