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4 Ways Big Data Is Used in Healthcare

Big data is helping every industry become more efficient and productive with respect to the way in which data is collected and analyzed – and healthcare is no exception.

Not only is the worldwide spend on IT infrastructure, including data centers, projected to total $4.4 trillion in 2022, but the sheer volume of healthcare data is growing at an exceptional rate. The volume of health data exceeded 2,000 exabytes in 2020 and a recent IDC study estimates that it will continue to grow year-over-year a 48% rate. 

The internet is at our fingertips and patients are increasingly turning to self-diagnosis as a 24/7 alternative to hospital waiting times and lengthy appointment booking processes. Telehealth statistics show that the use of virtual care is 38 times higher than before the COVID-19 pandemic, leaving the healthcare industry no choice but to further integrate technology and data analysis into daily hospital life.

With the relationship between data and healthcare set to become even more significant in the near future, we examine just a few of the ways in which big data can be used in healthcare:

1.  Staffing

For our first example of big data in healthcare, we will look at one classic problem that any shift manager faces: how many people do I put on staff at any given period? If you put on too many workers, you run the risk of having unnecessary labor costs add up. With too few workers, you can have poor customer service outcomes – which can be fatal for patients in that industry. Staffing and operations. Healthcare analytics can use big data to forecast patient admissions trends at specific times of the day and schedule the right number of staff during peak or slow periods. Big data is helping to solve this problem, at least at a few hospitals in France. A white paper by Intel details how four hospitals that are part of the Assistance Publique-Hôpitaux de Paris have been using data from a variety of sources to come up with daily and hourly predictions of how many patients are expected to be at each facility.

2. Electronic Health Records

Electronic Health Records (EHRs) are the most widespread application of big data in medicine. Every person has their own digital record which includes demographics, medical history, allergies, laboratory test results, etc. Records are shared via secure information systems and are available for providers from both the public and private sectors. EHRs can also trigger warnings and reminders when a patient should get a new lab test or track prescriptions to see if he or she has been following doctors’ orders. Kaiser Permanente is leading the way in the U.S. and could provide a model for the EU to follow. They’ve fully implemented a system called HealthConnect® that shares data across all their facilities and makes it easier to use EHRs.

3. Real-Time Alerts

Other examples of data analytics in healthcare share one crucial functionality – real-time alerting. In hospitals, Clinical Decision Support (CDS) software analyzes medical data on the spot, providing health practitioners with advice as they make prescriptive decisions. For example, if a patient’s blood pressure increases alarmingly, the system will send a live alert to the doctor who will then take action to reach the patient and administer measures to lower the pressure. Another example is that of Propeller Health (formerly Asthmapolis), which created inhalers with GPS-enabled trackers to identify asthma trends both on an individual level and looking at larger populations. This data is being used in conjunction with data from the CDC to develop better treatment plans for asthmatics.

4. Smart Device

Many consumers – and hence, potential patients – already have an interest in smart devices that record every step they take, their heart rates, sleeping habits, etc., on a permanent basis. All this vital information can be coupled with other trackable data to identify potential health risks lurking. Chronic insomnia and an elevated heart rate can signal a risk for future heart disease for instance. Another way to do so comes with new wearables under development, tracking specific health trends, and relaying them to the cloud where physicians can monitor them. Patients suffering from asthma or blood pressure could benefit from it, become a bit more independent and reduce unnecessary visits to the doctor.

With decades of expertise in the design and manufacture of network solutions, AFL has the capabilities and infrastructure to support evolving healthcare networks, from network design to a full connectivity solution.