Top 10 Big Data Solutions in Healthcare 
Data & Analytics Healthcare
Top 10 Big Data Solutions in Healthcare 
Top 10 Big Data Solutions in Healthcare 
Data & Analytics Healthcare

Top 10 Big Data Solutions in Healthcare 

The healthcare industry has seen a lot of technological advancements in recent years—from telemedicine to medical imagery, nanotechnology, 3D printing, artificial intelligence, and lots more. Now big data solutions are revolutionizing the industry. 

The evidence can be found in the numbers. For instance, as of 2021, approximately 78% and 96% of all office-based physicians and non-federal acute care hospitals respectively implemented a certified EHR ( a significant source of big data in the healthcare sector). 

But what is big data in healthcare? 

Big data is any large amount of data that has been collated digitally and can be analyzed to provide insights and improve decision-making.  


In the healthcare industry, this data is collated from a variety of medical sources, including electronic health records, clinical trials, genomic data, wearable devices, and patient portals. This data can be analyzed to help in hospital administration and improving patient care. 

Big data analytics is so important in providing improved care delivery and long-term solutions that global spending in this area is expected to reach $105.73 billion by 2030 – an increase of 13.85% from 2022 figures.  

In this article, we will explain the use of big data in healthcare and the role these applications play in improving the quality of life for patients. 

An Implementation Process of How Big Data is Used in Healthcare 


Seeing how big data is increasingly becoming a key part of healthcare, how do you go about implementing a big data strategy in your organization? 

There are a few key steps you need to take: 

  • Define your goals. What do you want to achieve with big data? 
  • Collect the right data. You need to have the right data sets to achieve your goals. 

Note that you also need to have the proper infrastructure in place to collate and support big data. This means having the hardware, software, and personnel necessary to store, process, and analyze large data sets.  

  • Analyze the data. This is where you start to see the patterns and trends in the data. 
  • Next, you need to have data-driven decision-making processes in place. This means using data to inform decisions about everything from patient care to business operations.  
  • And finally, you need to have a plan for how you will implement the changes you’ve decided on thanks to the insight gained from big data analysis. 

Big data is a big opportunity for healthcare. But it’s also a big challenge. Implementing a strategy for the use of big data in healthcare is not something that can be done overnight. You will likely need the services of a healthcare software development company to get things done right. 

What are the Benefits of Big Data Analytics in Healthcare? 

The benefits of big data analytics in healthcare are many. Some of the top ones are: 

Reduced Cost 

The biggest benefit of big data analytics in healthcare is that it can reduce the cost of healthcare by a large margin. One study estimates $300 billion per year. 

Big data analytics can help hospitals identify patterns in patient information that can be used to predict which patients will need more treatment or are at risk for medical error – which could also lower costs.  

This type of predictive analysis would also allow hospitals to adjust their staffing levels so resources aren’t wasted on unnecessary tests or procedures. 

Reduced Medical Error 

Big data solutions can reduce medical errors by identifying potential issues with treatments or treatments themselves before they occur. Machine learning algorithms help identify potential risks associated with prescribed medications so that doctors can make informed decisions about prescribing them or not in certain cases. 

This type of analysis could prevent additional trauma from being caused by poor treatment decisions — and could even save lives in the process. 

Informed Decision Making Around Diagnosis and Treatment 

Big data analytics can also benefit patients by informing physicians about how best to treat their conditions based on the information they have available through their patient records — including genetic testing results and other health history information — allowing them to make more informed decisions about treatment options based on their patient’s individual needs 

Advancement in the Health Sector.  

Big data analytics leads to advancements in medicine and health that were never possible before such as precision medicine, personalized medicine, and telemedicine/ telehealth services. 

Some of the Big Data Solutions/ Applications in Healthcare  

The impact of big data in healthcare is far-reaching. It helps to solve a lot of problems that would have been impossible in the past. Some of these solutions and applications are: 


Patient Prediction for Improved Staffing 

One major problem hospital administrators/ shift managers face is determining how many people should be on duty at a given period or risk running up unnecessary labor costs.  

Big data analytics solves this problem by using predictive modeling to identify patients who are at risk of falling and being injured.  

According to an Intel study, four hospitals in the Assistance Publique-Hôpitaux de Paris are predicting how many patients will be at each facility on a daily and hourly basis based on a variety of data sources including years’ worth of hospital admission records. 

This information can help hospital administrators better assess staffing requirements during peak times. 

Improved Drug Prescription Process 

The application of big data analytics in healthcare can improve the efficiency of drug prescription processes by identifying potential adverse events that may occur during a patient’s treatment with a particular medication or combination of medications.  

This information can be used by doctors to make more informed decisions about which drugs are best suited for their patients as well as to predict the possibility of drug addiction or misuse. 

Self-Harm & Suicide Prevention 

According to WHO data, one person commits suicide every forty seconds in different parts of the world. Additionally, 17% of people will self-harm at some point in their lives. While these numbers are alarming, big data analytics can help in these areas.  

Healthcare organizations can use big data analysis to help identify patients at risk of suicide and self-harm and create the necessary personalized intervention to help.  

One big data in healthcare case study in the area of suicide prevention was conducted by Mental Health Research Network and led by Kaiser Permanente researchers. Using EHR information and questionnaire data, they can accurately identify individuals with an elevated risk of suicide attempts. 

Supply Chain Management 

One of the largest challenges facing healthcare organizations is managing their supply chain, which involves managing multiple suppliers, and the flow of materials throughout the supply chain.  

The ability to track all these elements and integrate them into a single database helps organizations optimize their supply chain processes. 

In addition, it is possible to use big data analytics to predict demand for certain products based on historical patterns, allowing organizations to plan for shortages or surpluses. 

Improve Telemedicine 

Telemedicine saves patients and their family members time and money by eliminating unnecessary travel. But for telemedicine to work, it relies on health informatics, which involves data acquisition, data storage, data display, and processing, as well as data transfer. Not surprisingly, the basis of health informatics can be found in technologies such as big data and cloud computing. 

Risk & Disease Management 

Traditionally, healthcare management has been a reactive process — one that responds to the occurrence of a disease or injury. Big data solutions now make it possible to proactively manage risks and prevent future adverse events using predictive models.  

Healthcare institutions can provide accurate preventative care by analyzing information such as symptoms, frequency of medical visits, and medication type, among others. This ultimately reduces the number of hospital admissions. 

Enhanced Medical Imaging 

One of the best application of big data analytics in healthcare example is in the area of medical imaging. Big data allows physicians to make more informed decisions about patient care in less time. 

By applying advanced analytics techniques such as machine learning algorithms and neural networks to medical imaging, converting millions of images and pixels to data radiologists can use, it is possible to improve diagnosis and treatment options for patients with a wide range of conditions leading to better outcomes 

Predictive Analytics in Healthcare 

Predictive analytics is becoming an integral component of modern healthcare due to its ability to identify patterns in patient behaviors and data. 

Thanks to big data application in healthcare, organizations are now able to use predictive analytics to deliver improved clinical prediction, resource acquisition, and allocation, patient engagement, more tailored and effective patient care, early medical interventions, seamless hospital administration, and lower healthcare costs.  

Reduce Fraud and Enhance Security 

Analytics tools can help to reduce fraud in healthcare, including in the processing of insurance claims. This will lead to a decrease in healthcare budget waste, lower healthcare costs, and better patient outcomes.  

Another application of big data in healthcare is in the area of security as it helps organizations identify threats and vulnerabilities earlier than they would otherwise be able to do on their own. Healthcare organizations that can detect a cyber-attack in real-time and respond quickly enough to stop it can prevent a financial loss of about $10.1 million

To Manage and Track Diseases 

Data analytics can be very instrumental in tracking and managing diseases. For example, data analytics tremendously helped health in tracking the spread of COVID in real-time. Data from medical records and individual human behaviors were able to show how fast it evolved under different situations, as well as the impact it had on different world economies. 

The insight from the data gotten played a huge role in helping to subdue the spread of the virus and create vaccines to help mitigate its effects.  

End Note 

There you have it. The top 10 big data solutions for healthcare. 

As you can see from the examples of big data in healthcare covered in this article, there is so much big data analytics can do to improve healthcare service delivery. If you are looking to make big data work for your organization, you are on the right page. 

Symphony Solutions has a proven track record of helping the healthcare sector with solutions optimized for big data.  

Contact us today to see how we can help you. 

Yevhen Tanchik
About the Author

Yevhen Tanchik

Lead Data Engineer
Yevhen Tanchik excels in delivering valuable insights to businesses through advanced analysis and visualization techniques. With expertise in utilizing visualization software, Yevhen guides analysis, extracts meaningful implications, and synthesizes complex data into clear and impactful communications. His role as a lead data engineer allows him to leverage his skills to provide data-driven solutions that drive business success and empower organizations to make informed decisions.
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