While healthcare has historically been sluggish to adopt technology, the industry is about to observe significant developments over the next few years. The digital health market is anticipated to reach $206 billion by the end of 2020. Leading organizations are now redefining themselves with digital alteration, applied to their main operative areas with a customer-centric procedure.
Trend #1: Telemedicine
Progression in telemedicine is one of the most significant causes of rapid change in the Indian healthcare arrangement. In a large country where access to providers is confined, telemedicine is increasingly convincing to be transformative. Telemedicine is improving diagnosing and treatment by executing it easier for patients to get access to experts, too. The availability of electronic documents has also made it easier to forward records to specialists. In rural areas, this can mean the disparity between having and not having expert input into a case.
Data exchange platforms are converting what we think of as online healthcare. While the current video chat platforms that control the sector serve immense expectations, tele-health services can do a lot more. For example, hospitals have been able to decrease readmission rates by giving real-time monitoring of cases outside the office. Thanks to the advent of wearable devices, it’s common for remote monitoring practices to now be included in post-discharge plans for patients.
Trend #2: The Internet of Medical Things (IoMT)
Various devices and mobile apps have come to play a significant role in tracing and limiting chronic sicknesses for many patients and their physicians. By connecting IoT growth with telemedicine and tele-health technologies, a new Internet of Medical Things (IoMT) has risen. This method includes the use of a number of wearable, including ECG and EKG monitors. Many other popular medical analyses can also be taken, such as glucose level, skin temperature, and blood pressure readings.
Providing consistent and efficient interaction with numerous medical IoT devices is one of the biggest challenges that the sector faces. Manufacturers still regularly utilize their own proprietary protocols for talking to devices, and this can present problems, especially when trying to collect large amounts of data by servers. Connectivity concerns are also still prevalent, as the set of data by microcontrollers and smartphones can be obstructed by a number of circumstances in the surrounding environment. Buffering methods on local microcontrollers need to grow more robust in order to avoid losses.
Trend #3: Cloud computing in healthcare
A variety of public, private and hybrid cloud-based platforms are available for the distribution of large files. Healthcare organizations are working to address the need to build out, run and support infrastructure for record-keeping requirements. Here cloud computing becomes an appealing choice for digital technology in healthcare.
Patients and healthcare providers both tend to get better access to documents over cloud-based solutions, and they make the consultation process more comfortable. These telemedicine applications, though, place a higher demand for synchronized and asynchronous messaging systems. The desire to integrate video for live consultations also creates pressure to deploy WAN connections that are speedy, secure and stable.
Cloud computing is another example of such a “grey zone”. In a cloud environment, every step of the method needs to be judiciously controlled. When talking with cloud hosting providers, businesses need to be clear about what their demands are. Numerous providers have emerged that now specifically cater to the requirements of organizations with compliance needs.
Trend #4: Artificial Intelligence (AI) in healthcare
This is one of the nascent healthcare technology trends. Developing Artificial Intelligence (AI) machines—that can concoct information and grant decision-making data in a manner similar to what a human does—has given rise to an entirely new sector of innovative health technologies. AI applications can develop the pace and accuracy of the determination process.
FDA has recently approved the first AI-based diagnostic device, an arrangement that looks for eye disease by studying photos of the retina. High-quality photographs are uploaded, and the algorithm then continues to check for potential indications of diabetic retinopathy. The dysfunction was correctly identified by the software in 87% of events, and it accurately identified individuals without the condition 90% of the time.
Trend #5: Data Science and predictive analytics
Working with a case who has a chronic disease can create a great deal of data, but learning and compressing all the accessible data into something actionable can be a hurdle. Improvements in data science and predictive analytics, however, have made it possible for professionals to look for deeper insights. A doctor can, for example, feed data gleaned from ancestry and family histories into AI-based systems to come up with a statistically grounded profile and to diagnose problems faster.
Rich data can be obtained from sources about the surrounding environment, allowing specialists to recognize and discuss problems that are endemic to families, regions, trades and other population clusters. Data can also be scanned and interpreted to improve efficiency within a healthcare organization. Subjects who are at heightened risk for re-admission may, for example, be treated for more prolonged periods during their initial admissions in order to enhance long-term care. Data derived from studies of patients can also be used to predict which individuals might be at higher risk of negative outcomes.
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