10 Applications of Big Data in Healthcare and Life Sciences

by | Feb 9, 2022 | Healthcare, Life Sciences

Analytic reports of big data in healthcare with a stethoscope, pen, and glasses lying on top

Big data in healthcare and life sciences is necessary for every aspect of the industry such as diagnosing diseases, sharing information with patients, and filing health insurance claims. However, that vast amount of data is more than a simple software platform can handle. That’s why software designed for extensive information is necessary for collecting, storing, retrieving, and analyzing when using big data in your organization.

In this article, we will look at ten applications for big data that you collect and store in the healthcare industry.

Key Takeaways:
  • Big data is information that comes in a high volume, at an incredible velocity, and with many varieties.
  • Healthcare uses big data to improve the patient’s experience through more diverse treatment and monitoring options.
  • Big data also allows healthcare facilities, insurance companies, and life science organizations to share relevant data.

What is Big Data in Healthcare?

Big data is the large amounts of information professionals collect and store that is too complex for traditional technologies to handle. It is defined by its volume, velocity, and variety. Volume refers to the amount of data, velocity is the speed at which information is acquired, and variety is the many different data types.

 Here are several big data examples that are common in the healthcare and life science industries:

  • Hospital records
  • Patient medical records
  • Medical examination results
  • Research data

 

Video: How Big Data Helps Healthcare

Why is Big Data Important to Healthcare?

Big data is essential to healthcare because it helps professionals improve their services and save resources. It also allows hospitals and medical professionals to understand their patients and offer more accurate treatments.

One of the most revolutionizing benefits of big data in healthcare is preventing diseases rather than curing patients, which is far more effective, simple, and cost-effective.

Here are four ways healthcare professionals can analyze big data and use it practically in their facilities.

Four types of healthcare analytics.
Image source: Maryville University

10 Uses of Big Data in Healthcare and Life Sciences

Here are ten ways professionals can use big data in healthcare and life sciences.

1. Improve Hospital Efficiency

Data allows health professionals to streamline their hospital processes and improve overall efficiency by analyzing patterns and forecasting future events. For example, healthcare facilities can staff their rooms based on patient trends and peak times like during the flu season.

Hospitals can also improve their supply chain management by recording supply usage and analyzing future supply needs.

2. Address Healthcare Challenges

Big data analytics can show patterns in people’s behavior and help facilities find solutions to common challenges. For instance, certain geographic locations might be more prone to a specific disease. A hospital can expand into those areas to address those problems and improve the population’s quality of life.

3. Identify Potential Risks

Predictive analytics in healthcare uses data to identify potential risk factors in patients and prevent diseases before they occur. Medical personnel will also use it to detect early signs of a preexisting condition before noticeable symptoms arise.

For example, primary care physicians might send a patient with a high BMI, family history, and high blood pressure for extra diabetes testing.

According to one survey, 60% of healthcare executives adopted predictive analytics. Of those, 42% have seen greater patient satisfaction, and 39% have cut costs by preventing diseases and treating them before they become costly procedures.

4. Develop Cures

When healthcare facilities collect and analyze data on treatments, they can compare results to identify the best treatment plans. Data also helps facilities reduce errors, develop new therapies, and provide accurate diagnoses for the most efficient treatment.

5. Collect and Share Health Records

Electronic health records are digital patient records. They give real-time updates on a patient’s health, including:

  • Medical history
  • Health diagnosis
  • Current medications
  • Treatment plans
  • Immunization records
  • Known allergies
  • Radiology images
  • Test results

This information allows patients to stay informed about their health and make educated decisions. It also gives them vital information when reaching out to their health insurance company.

6. Unify Medical Facilities

Big data allows doctors and medical professionals to manage a patient’s journey and share patient information between facilities to unify the patient’s experience and help doctors make a more accurate diagnosis. For instance, doctors can now send over data electronically instead of patients repeating information to each provider or redoing tests.

7. Increase Patient Involvement

Today’s technology allows patients to be more engaged in their treatment through convenient at-home tracking and real-time altering. For example, diabetes patients can use a continuous glucose monitor (CGM) to track their sugar levels continually. Many CGM systems will track patterns of sugar spikes and alert the patient to potential problems. The patient’s doctor can receive the data from this device to stay updated on their health and adjust their treatment plans accordingly.

8. Use Alternative Treatment Methods

Thanks to big data, in-house doctor visits are no longer the only option for patients. Now technology can use big data to offer patients alternative treatment and care options. Some examples are telemedicine, telehealth, and procedures performed by robots.

Below you can see some of the most common trends in telehealth as it rises in popularity.

 

Telehealth services patients are willing to use.
Image source: SingleCare

Telemedicine saves doctors’ time and reduces the costs for patients. One study found the average trip to the emergency room was $1,734, the average doctor visit was $149, and the average telemedicine visit was $79.

9. Train Medical Professionals

Research shows that only 18% of residents and medical students said their education adequately prepared them for new technologies. Meanwhile, 44% said their education was not very helpful. Therefore, many medical professionals are shifting their education to spend more time learning how to use technology and interpret big data.

10. Secure Data

Data breaches are rampant in healthcare and account for 30% of significant data breaches. Additionally, there have been more than 2,100 reported healthcare data breaches since 2009. However, data can protect other data by monitoring network traffic, identifying changes in patterns, and alerting security to suspicious behavior.

Manage Big Data Through One Convenient Platform

Proper management and analysis of big data in life science and healthcare through high-end computing systems is necessary to find relevant information, compare findings, and use the results to make essential changes in your organization.

 

Contact us to learn about our platform for managing and updating provider data in healthcare.

 

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