IoT Healthcare: Big Data and IoT Can Solve Some Difficult Medical Problems


Big data analytics and the Internet of Things (IoT) can help solve some of the most challenging medical problems that we are currently facing as a society. Like any industry, the medical field can benefit from more efficiency introduced by big data analytics and IoT. For physicians, the two technologies would ensure that patients are treated faster and with more accuracy.

In this regard, the physicians can access refined data faster and apply it in real time. With such tools, it would have a chain of effects such as more patient service, less medical mistakes, faster recovery times, fewer misdiagnoses, less fatalities and an overall healthier society. Overall, physicians would only worry about the condition of the devices in use. 

Using IoT and big data analytics would make it possible for doctors to reach important milestones in medical areas that have often presented serious challenges. These include genetic data sequencing, comparative diagnosis across a worldwide spectrum and cross-examination of response to treatment across millions of data records collected from all over the world.

Real Time Diagnostics
The IoT can be used to solve some convenience problems in our medical fields since it allows the medical practitioners to focus on other pressing issues that cannot be handled by machines. IoT can create and sustain knowledge networks among interconnected devices with fully-functional feedback and looping systems that allow various adjustments to be made with minimal input from the physician. 

For instance, IoT can be used to monitor a patient’s condition if the necessary devices are interconnected and capable of sharing accurate real time data and triggering the correct corrective measures. IoT could potentially allow a physician to afford more time to take care of other patients. Diagnosis is one of the most time-consuming activities that most general physicians need to undertake. 

With IoT, the doctor is free to handle more patients while IoT takes care of monitoring the patients that are already under treatment. As is common with such scenarios, the doctor only needs to monitor the patient’s condition via a representative such as a nurse to prevent malfunction and potential harm to a patient.

Home Monitors
Unlike IoT, big data collects information from people’s behaviors and directs the correct feedback to the system. The integration of big data in homes was traditionally known as automation as depicted in devices such as thermostats and smart bathrooms. Patients suffering from acute illnesses may require to monitoring by physicians or other caretakers for extended periods of time.

In most cases, these patients will be accommodated in special centers due to the burden. With IoT, it is possible to provide such care at home using big data analytics wearables such as proximity sensors and blood pressure monitors. The information does not necessarily need to be transmitted over to the doctor. Instead, it can be collected on a cloud and compared with the patient’s diagnosis.

The cloud can push special notifications to the physician in case of a health anomaly. This can save a lot of time and potentially lead to better health prospects, as ailments will be arrested before they can present a serious health issue to the patient. In the future, these technologies can be extended to non-patients. Big data analytics software can be hooked up to biometric monitors and installed in people’s homes. 

The devices can then monitor various aspects of the home occupants such as breathing rate, walking, speech patterns, and other biometrically identifiable developments. By comparing such data with known diagnosis, the devices can warn the home occupier of potential health calamities that they may be unaware. This would combat ailments that typically present no noticeable symptoms until it is too late such as cancer. 

Quicker Services
Some services such as arthritis treatment can really benefit from IoT and Big Data in terms of bringing down the costs. According to projections, IoT and Big Data can lower various costs significantly in the long term. The most obvious is the management expenses which typically emanate from clerical routine tasks such as file maintenance and time-consuming multiple diagnoses. Some estimates point out that it is possible to save up to $300 billion in health care management around the world. 

It should be noted that these estimates are highly conservative since there are numerous chain events linked to healthcare management. For instance, treating arthritis requires regular diagnosis throughout the program that means that there is need for regular traveling and accommodation expenses. This is not to mention the opportunity costs incurred by the patient in missed workdays and other beneficial efforts. 

With the integration of big data and IoT, the patient will make fewer but necessary trips for their appointments. Moreover, the physician will be expecting the patient when they travel and will have most of the diagnosis long before the patient arrives, again, this will lead to saved time. 

Big data and IoT are complementary in that the two allow technologies allow devices to accept critical data, compress it and decode its meaning. IoT may directly adjust various phenomena based on the analyzed data. On the other hand, big data may require some more extensive human intervention.

In medical care, the implementation of the two technologies presents a unique opportunity to save on costs incurred in tough medical problems, intercept symptoms early, and recommend treatment based on the data collected by the devices. Real time diagnostics, home monitors, and quicker medical services are some of the most important breakthroughs introduced by IoT and big data.

About the Author: After obtaining his medical practitioner’s license from the University of Michigan, Isaac Christiansen immediately started his own private practice. After 20 years, Isaac is still practicing but has since integrated holistic and alternative medicine into his treatment options.

Edited by Ken Briodagh
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