Big data is playing a great role in every industry. Some industries such as banking, insurance, and healthcare are generating huge volumes of data on a daily basis.
The role that big data is playing in the healthcare industry may have the greatest impact on our lives. Researchers, physicians, and hospitals are turning to a vast network of healthcare data to understand the clinical context, find new treatment options, and prevent future health issues. These are just some of the ways through which big data is being used in the healthcare industry. In this article, we will be discussing the role and the impact of big data in the healthcare industry.
Part 1: What is Big Data?
Big data is a large set of complex data, either structured or unstructured, that can be used effectively to uncover deep insights and solve business problems that couldn’t be tackled before using conventional software and analytics. Data scientists normally use artificial intelligence ETL tools and techniques to evaluate these comprehensive datasets to uncover trends and patterns which can give meaningful business insights. In the healthcare industry, big data refers to the use of predictive, prescriptive, and descriptive analytics to extract insights from healthcare data. It is expected that big data will penetrate more into the healthcare industry than any other industry like financial services, media, and manufacturing. As a matter of matter, the global healthcare big data market is expected to grow at a compound annual growth rate of 22.07% and hit about $34 billion by 2022. This is true because of the increasing investment in the workforce management tools, electronic health record systems, and management solutions such as the ones offered by HealthTECH Resources EHR consulting company.
Part 2: How is Big Data being used in the Healthtech Industry?
There are different ways to use big data in any industry. Today, the health-tech industry is leveraging big data and the associated analytics in a number of ways. The following are some of the ways through which big data is driving change in the healthcare industry:
Product Development
The process of discovering, designing, and developing new drugs and vaccines is costly and time-consuming. The following are the possible uses of big data in the health-tech industry:
- Product researchers and developers are struggling to understand huge volumes of data at their disposal.
This is a good area to apply big data, by focusing on the right data and therefore reduce the time required for product development.
- A lot of trial and error is involved in the product development process.
Big data can remove the guesswork from the equation, helping researchers and developers to deliver better and more precise products.
- Real-time data analytics can help healthcare companies to refine their products based on voluminous datasets.
Fighting Cancer
Most people in the world have been impacted by cancer either directly or indirectly, and effort is being put to find ways to combat the disease. Researchers in both the private and public sectors are putting effort to find more effective treatment options. The good news is that big data has changed how these researchers view the disease by giving access to patient information, patterns, and trends that were never before. Examples of companies that are using big data to fight cancer include Flatiron health (New York), Tempus (Chicago, Illinois), and Digital Reasoning Systems (Franklin, Tennessee).
Early Disease Detection
Early detection of diseases is a good way of achieving successful treatment. Regardless of the type of disease, screenings and other exams are a great way of staying ahead of the disease. Examples of companies that are using big data for early detection of diseases are Pieces Technologies (Dallas, Texas), PeraHealth (Charlotte, North Carolina), and Prognos (New York).
Preventive Maintenance
Big data can be used for preventive maintenance of health tech devices, medical equipment, and digital assets such as websites and apps, especially at a time when data security breaches are on the rise. Hence, big data helps healthcare organizations to reduce the general costs of ensuring that their tools are up and running.
Improving Patient Outcomes
Big data and analytics make it easy for medical practitioners and researchers to diagnose and treat diseases better. After analyzing a patient’s health data, clinicians and doctors can be able to diagnose rare diseases like Parkinson’s disease. The major advantage of using big data in the health-tech industry is its ability to significantly improve the health of patients.
Operational Efficiency
Collecting and analyzing workforce data helps healthcare organizations like hospitals and pharmaceutical companies to boost the productivity of their employees.
It can help health organizations to redesign their workflows and direct more resources where there is a need to improve operational efficiency.
Driving Innovation
Innovation is an important aspect of healthcare as it drives drug discovery, patient outcomes, healthcare quality, etc. There are many circumstances under which big data has enhanced innovation in the health-tech industry:
- Pairing patient care with predictive data analytics.
- Diagnosis and prevention of cardiovascular diseases such as heart attack.
- Development of tailored drugs and therapies for rare and complex diseases.
Big data can help to reduce the cost of healthcare.
It can also help healthcare companies to reduce data breaches, fraud, and other security problems.
Part 3: Limitations
The following are the challenges that health tech organizations face with big data:
- Lack of tech-savvy to collect, gather enough data into their data warehouses for analysis. This becomes a bigger problem if the health data is to be collected from multiple sources.
- Inability to collect health-related data in real-time which can improve the speed of drug and vaccine development as well as diagnosis of diseases.
Part 4: Use Hevo Data
Hevo Data provides its users with a simpler platform for integrating data for analysis.
It is a no-code data pipeline that can help you combine data from multiple sources.
You can use it to transfer data from multiple data sources into your data warehouse for analytics. It provides you with a consistent and reliable solution to managing data in real-time, ensuring that you always have analysis-ready data in your desired destination. Your job will be to focus on key business needs and perform insightful analysis using BI tools.
Conclusion
This is what you’ve learnt:
- You’ve learnt more about big data.
- You’ve learnt how big data is transforming the health tech industry.
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