A predictive analytics approach to connected health can help identify patients who are at high risk of non-adherence to medication regimens and reduce unnecessary interventions. The results of this type of analytics can be used to tailor patient interventions. This will improve adherence rates and attention to medications. The next step will be to develop predictive analytics applications that use these types of data. For now, this will involve creating a predictive analytics model based on big data and artificial intelligence.
An e-health platform can be a key component of a connected health program. By extending care team outreach, this technology will reduce the risk of error, reduce waste, and streamline workflows. In a connected home care setting, for instance, the care team will be able to monitor patients’ health status in real time, allowing them to make better-informed decisions. These models can also help prevent re-admissions to hospitals.
An upcoming study from Partners Telemedicine is analyzing data from a technology readiness survey of diabetes patients. The researchers are examining whether consumers are willing to adopt technology to share their health information remotely with their physicians. The results of this study suggest that consumers are open to adopting connected health technologies. It’s important to remember that the goal of connected health is to keep clinicians connected to their patients. For example, connected health technologies can provide feedback and incentives to motivate patients to use healthy behaviors. Visit here me: thedolive Touch here visit now: topwebs