The internet of things is of significant impact with many shared benefits for all stakeholders in the health industry, ranging from the government – to practitioners and also to patients. It reduces operational costs through improved machine efficiency and timely maintenance of medical equipment in hospitals and other similar health care facilities. The experiences of patients are also enhanced through real-time health monitoring devices, anxiety easing virtual reality, and advanced and predictive clinical analytics.
By creating a virtual reality model of the actual human body part such as the human brain, abdomen, legs or breasts that a Doctor needs to treat; makes it possible to explore the most suitable treatment approach and also allow the patient to experience it as well. This approach allows surgeons to prepare for best results and also improve the experience of patients.
The volume and types of data that is made available through the application of IoT in the medical industry help to raise the potentials of healthcare professionals in transforming the way they treat patients, research cures as well as how they manage operations. This application of IoT is becoming much more relevant as a lot of healthcare professionals are now developing interests in various methods of advanced analytics such as machine learning and predictive analytics.
Predictive Clinical Analytics
This helps to examine previous data to predict future outcomes. Predictive analytics adopts diverse stochastic and machine learning approach that is time-tested even with the accumulation of new data. Based on a white paper by Intel, on Predictive Analytics in Healthcare; an instance of predictive analytics is the use of past data from the record of a hospital in combination with external sources such as weather predictions and the internet media to predicts the highest periods in patients admission so as to make adequate ready staffs.
Other forms of advanced analytics include prescriptive analytics and cognitive analytics. Prescriptive analytics leverages on predictive analytics and utilizes data management approaches such as modeling, machine learning in addition to cognitive systems. On the other hand, Cognitive analytics uses different technologies of artificial intelligence including computer-aided reasoning/logic systems, deep learning, and machine learning. Usually, it utilizes mental-like analysis based on automated decisions or amplifying human choices through the provision of comprehensive suggestions
Similarly, according to Neal Ganguly who works at JFK Health System, Edison, New Jersey; IoT could be of particular importance in the Health Industry in three main areas; namely: device integration, workflow optimization, and inventory management.
Healthcare Device Integration
Neal explained that the expectation in integrating IoT in healthcare devices is to enable providers to gather the desired data in a more automated manner and also be able to implement specific decision support rules to facilitate earlier intervention in patient’s condition in the process.
IoT facilitates the use of Radio Frequency Identification (RFID) technology through an improved system of tag devices (e.g., wristbands) and wireless infrastructures. It enables healthcare facilities to analyze the targeted data for blockages and proffer viable solutions and thus optimizing workflow.
Similarly, IoT is useful in improving inventory management in the healthcare industry both in the areas of drugs dispensing, and overall inventory control in storage houses.
Conclusively, the use of Internet of Things (IoT) in the healthcare industry creates a win-win situation, as it helps patients have access to improved treatment and at the same time, allowing health practitioners to function more effectively and efficiently.