The modern world is powered by data. Data as information can provide insights and innovative solutions that would be otherwise impossible. In healthcare, the many applications of data make data mining a useful and lucrative practice.
Data mining is the process of sorting through large sets of data to categorize it and draw patterns and relationships. In healthcare, this can mean better treatments and ultimately more lives saved.
But how has data mining advanced with recent world events like the COVID-19 pandemic? How is data mining being used in healthcare?
Here’s what you should know.
Advancements in Data Mining
Data has enabled the digital transformation of the healthcare sector. In the wake of COVID-19, patients are looking for safe, remote treatment options that can rival traditional care in terms of quality. Data makes this possible.
By pooling de-identified patient data, care providers can look for patterns in symptoms, risk factors, demographics, and more. As a result, patient privacy is retained while a better understanding of health issues is created.
This requires using the right tools and data mining processes, however. Advancements in data mining are making this easier all the time, with new tools and practices that harness, categorize, and analyze healthcare data. Care professionals can then more successfully apply the generated insights to adaptive care.
Here are some of the data mining advancements transforming healthcare today:
- Database and data mining integration. Care facilities are experiencing success by tightly coupling data mining procedures with the databases on which they are stored. This keeps the process simple and seamless, allowing for greater visibility and protections over a cohesive system.
- Biological data mining. Our ability to examine and categorize biological information means we can now qualify it as data. Everything from DNA microarrays, protein sequences, and disease pathways can be stored as part of an electronic health record. This means care providers and researchers have unprecedented looks into the ways the body works.
- Information security in data mining. As long as information exists in a network, it can be hacked or attacked. Such events produce their own data, however. Information security alongside healthcare data helps inform smarter systems. Developments in artificial intelligence and machine learning allow for such systems, which learn better prevention techniques the more data is fed into them.
These advancements and trends in data mining can benefit the healthcare industry, but how are they being applied in modern care solutions? From telehealth to preventative care, healthcare providers are doing a lot with the developments in data mining.
Data Mining Applications in Healthcare
These trends in data mining processes have enormous implications for effective healthcare solutions. With the right data, care professionals can more expertly and correctly diagnose illnesses, personalize treatments to a patient, and provide care even at a distance.
Data mining in healthcare often comes in the form of MRI imaging or X-ray scanning to create a database of information. With immense amounts of information at their disposal, care professionals can then apply the data in three distinctive ways. These are:
- Descriptive — analysis of data sets used to explain healthcare trends
- Predictive — data used to model likely outcomes based on historical information and relevant factors
- Prescriptive — solutions generated from modeled outcomes meant to improve a process
By applying descriptive, predictive, and prescriptive data solutions to healthcare problems, outcomes can be broadly improved and patient data better secured. Since one of the biggest problems in the healthcare data mining process right now is the IT risk that comes with storing valuable data, even healthcare cybersecurity stands to benefit from the right data applications.
One of the most relevant applications of data mining procedures in healthcare today is through telemedicine. The COVID-19 pandemic saw the use of telemedicine increase by as much as 50% in the beginning months alone, with its continued popularity unlikely to diminish anytime soon.
Telemedicine both relies on and gathers data. Without cloud data storage systems for healthcare records, telemedicine providers would have extreme difficulty in managing patients remotely while maintaining records and securing their privacy. Advancements in data mining make possible all the important benefits of telemedicine, such as broader accessibility and quality care.
For example, new processes in storing and de-identifying electronic health records (EHRs) allow care professionals to safely connect symptoms to risk factors and demographics. They can then pair patient history to such a model to have better insight into who needs preventative care and reach out for appointment setting where needed.
Telemedicine means broader access to preventative care, which can have a real impact on the life-saving potential of treatment. Even the process of integrating this data on a cloud database can generate valuable security data, helping analysts construct models of cybersecurity threats to better prevent them in the future.
In short, data mining powers a limitless variety of healthcare solutions, all of which can lead to a future of better care practices.
Finding Data-Driven Care Solutions
In the wake of the coronavirus pandemic, sweeping healthcare assistance is vital. The pandemic has impacted healthcare IT through the shift to increased virtual systems and the subsequent threats that come along with these systems. However, big data through connected networks of care can produce incredible awareness of problems and solutions alike.
Building these networks, using them to generate health solutions, and protecting them through AI and machine learning are all possible through data mining. Advancements in the process mean this data is safer than ever. Care facilities that integrate data mining now and innovative for the future will be prepared to offer better care from anywhere.