IoT has bridged the gap between healthcare facilities, doctors, and patients by enabling them to connect remotely. With AI increasingly getting adopted in connected healthcare solutions, it helps doctors and patients in making more accurate and informed decisions.
With intense competition and awareness, healthcare providers are focusing on innovative solutions and technologies to provide advanced functionalities, even while finding ways to reduce the overall cost of the device. According to MarketsandMarkets, the overall IoT healthcare market is estimated to grow from USD 41.22 billion in 2017 to USD 158.07 billion by 2022, at a CAGR of 30.8% between 2017 and 2022. Health awareness, evolution of technology and the increase in deployment of connected devices in healthcare are the key drivers for this growth. To gain higher market share, medical device manufacturing companies are evaluating options to offer low cost innovative solutions to their customers with an end goal to be one of the below:
Capturing and analyzing medical data is going to be an important aspect of a successful IoT implementation. The increase in connected devices will also lead to an exponential increase in data. IDC expects that by 2025 there will be 41.6 billion connected IoT devices or “things,” generating more than 79 zettabytes (ZB) of data. In healthcare organizations, where laws regulate protected health information (PHI), it is critical to understand the implications of cloud adoption for privacy, security, and regulatory compliance. These organizations need to be careful and adhere to the guidelines in solution design and cloud deployment operations.
In order to cater to these requirements, Microsoft has recently announced availability of a new Microsoft® Azure™ Security and Compliance Blueprint. It has been rapidly adopted by organizations of all sizes around the world, across many industries.
The Azure IoT platform will benefit healthcare organizations by connecting and controlling devices remotely. The platform will provide connectivity to ensure real-time health data collection, available on the cloud is properly structured and labelled for quick analysis to provide meaningful insights. Healthcare organizations have realized the potential of AI (Artificial Intelligence) and ML (machine learning) capabilities that can be effective in streamlining medical treatment and hospital operations. At times, AI / ML adoption is difficult due to lack of technical experts.
To eliminate this problem, Microsoft had launched Azure healthcare AI blueprint in 2018. The Azure Security and Compliance Blueprint – HIPAA/HITRUST Health Data and AI enables deployment of platform-as-a-solution to demonstrate how to securely capture, transmit, store, and analyze health data as per industry compliance requirements. It provides tools and building blocks to help deploy secure, multi-tier cloud environment that can handle and process medical data as per Health Insurance Portability and Accountability Act (HIPAA), and Health Information Trust Alliance (HITRUST).
In addition to data sensing, remote monitoring and control, predictive analytics, and machine learning are rapidly becoming the most-hyped topics in healthcare analytics. However, accurate predictions are useful only if it results into actions. Many healthcare providers are adopting Azure Machine Learning Studio to leverage business intelligence tools and analytics to review predictions made on the sample data. This blueprint provides a flexible foundation for customers to adjust to their specific requirements, developing new Azure Machine learning experiments to solve both clinical and operational use case scenarios. It provides an environment to develop or customize machine-learning models that are trained by the rich data sets to implement predictors. These predictions are interpreted by healthcare providers to prescribe appropriate intervention measures. Here are a few examples:
Prediction and prevention goes together. With the help of predictive analytics, healthcare providers can identify individuals with higher risks of developing chronic conditions in the early stages to provide early treatment and avoid any long-term health risks.
Admitted patients can have a number of potential threats to their wellbeing. Data analytics can provide alerts based on patient’s vitals that may assist in preventing any future deterioration.
Based on medical data, organizations can flag individuals who are more likely to cause harm to themselves. They can track these individuals and if required provide proactive mental healthcare when they need to avoid serious events, including suicide.
Predictive tools can help in forecasting medication and hospital supplies consumption to reduce variation and gain insights on ordering patterns and supply utilization.
eInfochips is a Microsoft Gold Cloud Productivity Partner and a Windows and Device Partner. We provide customized IoT solutions to enterprises and help clients in implementing a highly scalable, reliable, and cost-efficient infrastructure with custom solutions for IoT on the Microsoft Azure platform. Microsoft Azure enables the convergence of intelligent cloud and edge by providing AI, Machine learning, and analytics capabilities on the edge. At the same time, leveraging our in-depth domain and process (IEC 60601 – 1/2/6, IEC 62304, 510K, ISO 13485) expertise, we have developed connected solutions for imaging, diagnostics, home care, remote monitoring and telemedicine.
