How Big Data Impacts the Healthcare Industry

Researches found out that worldwide big data in the healthcare market is going to reach $34.27 billion by 2022. Due to the fact that the healthcare industry creates a huge amount of information, big data analytics may improve the quality of services and the entire healthcare ecosystem.

Many countries invest in that improvements, especially North America with revenue of $3.74 billion in 2014 from the big data analytics integration. One of the key industries applying big data analytics in Europe is Automotive. Besides, Africa and the Middle East are working on their big data investments as well.

How Healthcare Industry Can Use Big Data

#1 Eliminate medication errors

Medication errors caused by the human factors may have tremendous results. Each industry struggles to have 100% accuracy in daily operations but the healthcare area is aimed to solve serious problems and medical employees can’t let themselves to make even the smallest mistake. Big data helps not to end up with the wrong medication and treat patients better. More meaningful decision based on existing data is one more benefit to empower the doctors.

For example, an Israeli startup MedAware has applied this technology. The experimentations have shown that this software may save for the healthcare industry up to $21 billion per year.

#2 Decrease hospital costs and wait times

Big data has captured the attention of physicians all over the world. A few hospitals in Paris uses it to predict how many patients they may expect each month. Also, scientists apply machine learning to capture the most accurate algorithms that can predict admissions trends.

The new sensor devices can be applied by the patients anywhere in order to monitor their state and help them avoid hospitalization. For hospitalized people, medical professionals may use predictive analytics to improve and decrease readmissions. Parkland Hospital in Dallas Texas applies advanced analytics to recognize high-risk patients and help them to overcome diseases. As a result, this hospital has reduced 30-day readmissions and got savings of more than $500,000 each year.

Big data analytics helps medicians to gather and analyze a lot of healthcare data to gain useful insights. Big data cloud platforms bring new cost-effective solutions when healthcare professionals may reach structured data. McKinsey & Company’s report found out that big data may save Americans $450 billion each year.

When doctors may easily capture needed data, it brings quicker time to treatment and helps to cut the expenses as well. Big data analytics tools allow to speed up processes by taking into account unique factors such as demographics and lifestyle choices.

#3 Improve the quality of services

Predictive analytics helps to bring more accurate results. Moreover, algorithms may deliver personalized treatment based on existing information. Personalization includes matching medicines to a person’s genetic makeup and developing them based on various factors such as environment and lifestyle. It will be overwhelming for the people and easy for the system to absorb a huge amount of information and analyze it.

Besides, the patient’s data will not be analyzed in isolation. It will be treated alongside other cases that allow to create patterns for better analysis. So, doctors get valuable predictive modeling with data how patients with the same conditions can be cured.

Apple and IBM have developed a big data health platform to explore new insights from biometric data and real-time activity. The users may track health-related data and a system will suggest appropriate treatment for them. Besides, these medical advices will be based on the person’s habits, age, past conditions, etc.

The main goal of such platform and healthcare devices is allowing busy people to get professional consultation on the go or at home. The information captured from smart devices allow doctors to keep in touch with their patients, track their state and set an automated reminder to take medicines. According to the MapR Guide to Big Data in Healthcare, healthcare IoT expenses will reach $120 billion within the next few years.

The oncologists apply Watson to capture the needed facts from the electronic health record and recognize areas that require doctor’s attention. Then, the medical professionals match the person to the treatment or review the suggested cure. This match is high-quality because Watson IBM applied the best practices to bring sophisticated results.

#4 Get security on board

Adoption of big data in healthcare significantly enhances patient privacy and security concerns. The main reason it’s because their information is stored in data centers with different levels of security. Moreover, the data came from diverse places that bring additional risks. Despite the ways in which new technologies may be used for wrong goals, a cloud-based solution that applied big data helps to add needed security for HIPAA compliance that is unique to the healthcare industry. Also, it is a cost-effective solution and we need to learn to take advantage of the innovations to stay sync with the modern world.

Many companies gain a hybrid approach to their data storage strategy with flexibility features. However, keep in mind to make sure that all systems may cooperate and share data with other segments of the company.

A lack of control can let frauds to hack the system. It means huge losses for the company and it’s much cheaper to prevent it. In this case, perimeter-based security is applied for the protection of big data.

Today’s digital jungle is overwhelming for the people. Big data is a new way to overcome existing challenges in the global medicine such as low budget and overloaded medical professionals. Big data helps to free up staff while improving the level of services. When doctors have all the needed information in one place, it’s possible to achieve great personalization and bring treatment that fits the specific person.

Moreover, patients get real-time advice according to the wearable devices that capture data about their states. It helps medicians prevent readmissions, predict future admissions and prepare the hospitals.