If you want to find out how big data is helping to make the world a better place, there’s no better example than the uses being found for it in healthcare.
The last number of decades has seen exponential growth in the amount of data we generate in pretty much everything we do, as well as our ability to use technology to analyze and understand it. The intersection of these trends is what we call “big data” and it is helping companies in every industry to become more efficient and productive.
Healthcare is no different. Beyond reducing costs and cutting down on spending, big data in healthcare is being used to predict epidemics, cure disease, improve quality of life and avoid preventable deaths. With the help of big data, the goal is to understand as much about a patient as possible, as early in their life as possible – hopefully picking up warning signs of serious illness at an early enough stage that treatment is far more simple (and less expensive) than if it had not been spotted until later.
In the healthcare industry, various sources for big data include hospital records, medical records of patients, results of medical examinations, and IoT devices. Biomedical research also generates a significant portion of big data relevant to public healthcare. This data requires proper management and analysis in order to derive meaningful information. Otherwise, seeking solution by analyzing big data quickly becomes comparable to finding a needle in the haystack. An efficient management, analysis, and interpretation of big data can change the game by opening new avenues for modern healthcare.
Prevention is better than cure
Modern medicine grows and improves year in and year out, but the implementation of big data has helped doctors to advance the care they can provide every single day. The information from the data generated and analyzed across the world allows doctors to make better-informed decisions on treatments for their patients. Even if the illness is rare, the vast amount of information can help doctors narrow-down on a diagnosis and treat accordingly.
The application of big data in healthcare allows doctors to predict health risk, plan further procedures for the patients’ betterment and even prevent another patient from going down the same road. Having access to ever-growing databases of information about the state of the health of the general public will allow problems to be noticed before they occur, and new treatments to be prepared in advance.
This is leading to ground-breaking work, often by partnerships between medical and data professionals, with the potential to get an insight into the future and identify problems before they happen. One patient’s data will be observed and analyzed alongside thousands and thousands of others, highlighting issues through patterns that emerge during the comparison.
Big data analytics allows sophisticated predictive modelling to take place – a doctor will be able to assess the likely result of whichever treatment he or she is considering prescribing, backed up by the data from other patients with the same condition, genetic factors and lifestyle.
Diligence in patient care
Every doctor strives to give their patients the most consistent care possible. But with hundreds (if not thousands) of patients on their list, it's hard to keep up with that level of care.
Big data (and big data analytics) are essential to further diligence in patient care. Big data helps by reporting every single treatment, checkup, prescription or surgery each patient has ever had. From there, the doctor uses the analytics tool to sort through treatments, organize it and assign the next steps much quicker. This can help the doctors determine proper treatment processes for their patients based on the very illness or injury that they have.
More affordable healthcare
Healthcare is a very complicated industry with many barriers to progress. The cost pressure in the US system is not a new phenomenon, since healthcare expenses have been rising rapidly over the last number of decades.
Many factors contribute to the rising healthcare costs, such as expensive new diagnostic tests and treatments, administrative costs, malpractice and drug costs. Also, co-pays and deductibles have become expensive and employers are burdened to take a bigger cut of their employees’ wages to pay for insurance premiums.
According to CNBC, healthcare is the number two largest industry with forecasted revenue growth of 2.3%. Hence, healthcare is a promising area in which data can be managed and leveraged to create positive change.
Doctors are generally limited to the amount of patient history available to them and lack the vital information regarding symptoms of patients. This obstructs the treatment of patients suffering from lifelong diseases. Healthcare data analytics can address this issue by supplying doctors with the vital correlative information that can help them make better use of the electronic medical records of patient information.
With big data analytics, doctors are able to minimize the risk unsuccessful treatments with predictive data and information that can assist them in assigning the correct forms of prescriptions, surgeries or rehabilitation, to name a few.
Not only will the patients save big, but healthcare companies will too. Insights generated from big data create distinct advantages for providers, manufacturers and pharmaceutical companies:
- Providers, such as clinics and hospitals, can improve patient care by streamlining workflow processes, resulting in more time with patients and better outcomes at lower costs.
- Medical device manufacturers can create better, innovative products to solve health issues at a lower cost.
- Big pharma benefits from better research and development, resulting in more effective drugs, shorter production times and lower costs to the consumer.
Connecting the global healthcare supply chain
COVID-19 — more than any event that came before it — is shining a light on the need for supply chain visibility and access to reliable, real-time logistics data. The pandemic exposed many weaknesses in the current global supply chain.
Determining how best to connect the healthcare supply chain has always been a challenge from drug shortages to protective equipment, especially during a crisis. There have been many companies and government agencies that have worked together to ensure that we foster a clear path to connect the supply chain.
For example, government agencies such as the World Health Organization have worked together to ensure areas that have limited access can coordinate supplies. The challenges still exist around the world to ensure the global connectivity of the supply chain. Real-time, data-driven collaboration is now mission-critical. Making sure we coordinate the proper processes will be an essential plan for future policy to address future global healthcare crisis.
