Big Data to Improve Healthcare
The COVID-19 pandemic demonstrated the importance of strong healthcare infrastructures. What happened in hospitals and health centers was recorded and helped science find solutions to save lives. In addition, as laboratories and research centers worked to help stop the spread of the virus, they also shared data.
In this post, we are going to tell you why big data is so important for the healthcare professionals who work every day to improve our quality of life and for the administrations and companies that work with them. In addition, we will show you some examples.
What Will Medicine Look Like in the Future?
In the medicine of the future, big data will be very important. Their analysis is used to better diagnose or to design more effective treatments. In this way, the medicine of the future will excel in improving the detection of diseases. And not only will the medicine of the future improve detection at an earlier stage. It will also do so by monitoring progress and acting accordingly to stop the disease or design treatment.
While the quality of life of patients is being improved, behind the scenes in the laboratories, projects are being developed to improve science. Having large amounts of data means fine-tuning projects and executing them in less time in order to have new drugs and treatments.
All this will allow the medicine of the future to be tailored to the patient and more precise, as more lifestyle, genetic or historical data is included.
The journal Nature Medicine asked several experts in 2019 what they thought the next 25 years of medical research would be like. Among the ideas, they pointed out the importance of knowing how to take advantage of the structure and predictive capacity of data in genetic programs: precision medicine, which uses information from genes to prevent or treat a disease, would improve its development. They also pointed to the need to share non-intimate data and, at the same time, to ensure the privacy of sensitive data.
The executive vice president of the Scripps Research Institute, Eric Topol, proposed that by 2045 we would have a “planetary health infrastructure” based on data accessible by as many people as possible. The infrastructure would use artificial intelligence with neural networks and could be used in real-time.
Examples of Big data in Healthcare
Big data in healthcare or big data in medicine reaches numerous departments in a healthcare center, from Human Resources (to find out how many staff are needed) to purchasing or research areas. Ingesting and analyzing the data generated in daily operations serves to draw conclusions that improve daily operations and, most interestingly, advances science and improves the health of the public.
Examples of big data in healthcare can be found in many areas:
- Patient’s medical records (if their use does not violate data protection).
- Data on center operations: patients treated, equipment used, most detected diseases…
- Medical test results
- Compilation of scientific articles and medical literature
Big Data and Healthcare Projects
If we are talking about more concrete examples of big data in healthcare, the COVID-19 pandemic gave us an example of the potential of big data to save lives. The Johns Hopkins University’s world map of contagion in the United States has been used for a lot of information and research, accompanied by some complementary data visualizations: global vaccination, US hospital capacity, etc.
But long before COVID-19, in 2008, big data showed signs of the potential it could have in the years to come. Then, Google launched its Flu Trends, a tool that until 2015 allowed predicting flu outbreaks with users’ searches and historical data on the virus in the region where the searches were made.
Beyond disease emergence and treatment, big data can also be used to manage healthcare facilities. For example, in Paris, the emergency departments of four hospitals have used analytics platforms to predict the number of patient visits and hospital admissions and make decisions accordingly.
Big Data and Healthcare at Plain Concepts
At Plain Concepts, we help many companies manage and analyze data to make it easier for them to get the most out of it. Our work covers many industries, and healthcare is no exception.
For Spanish health insurer Grupo Asisa, which covers 2.2 million policyholders with 40,000 workers, we migrated their 100+ databases, with up to 3TB of data, to Azure. The databases included 2.3 million medical records and 7.5 million annual attendances. The system runs 24 hours a day, seven days a week, and continued to do so during the migration.
The operation enabled Asisa to strengthen its cybersecurity while improving data and patient confidentiality. In addition, this operation served to make it easier for them to implement technologies such as mixed reality or blockchain in the future.
With this process, Plain Concepts optimized the use of Asisa’s structured information. It is a sample of the potential that new big data technologies have to improve the lives of patients or optimize processes in the health sector.