Application of Data Analytics in Healthcare

Healthcare
May 5, 2023

 

Decisions in the healthcare industry tend to have a substantial effect on patients' lives as well as the population at large. Making data analytics one of the most important tools in healthcare systems. It enables healthcare professionals to make better, accurate, more informed and fast decisions about patient care.


It can be used in a variety of ways in healthcare, including tracking and predicting patient outcomes, identifying potential areas of improvement in healthcare and more.

In this blog we will through light on how data analytics solutions in healthcare becomes an important part.

What is Data Analytics in healthcare?

 

Before diving deep into data analytics importance in healthcare ecosystem. Let’s first understand what is Data Analytics. Data analytics in healthcare is the process of analyzing healthcare data to improve patient care and outcomes. It can be used to identify safety risks, patterns, and areas for improvement. Healthcare data analytics can also help in predicting future health needs and trends.
 
There are many different ways to gather and examine healthcare data. Electronic Health Records (EHR) integration is one of the popular methods. EHRs are digital health records for patients that can be used to track patient outcomes and much more.
 
Another popular method for healthcare data analysis is CDSS (Clinical Decision Support System) which is a computerized system that helps healthcare professionals make better and more informed decisions.

 

Types of Data Analytics 

 

S.N0. TYPES USAGE 
   
  1.  
Descriptive Analysis

Used to describe already happened health phenomenon

For example- the spread of a contagious virus.

  1.  
Diagnostic Analysis 

Seeks cause of an event to diagnose a treatment 

For example- Diagnose an illness based on symptoms 

  1.  
Predictive Analysis 

Explores trends and historical event to predict future possibility

For example- Forecast of seasonal diseases

  1.  
Prescriptive Analysis 

Devices/plans actions or strategy for predicted future outcomes 

For example- Determine patient at risk based on his previous health history and demographics. 

 

Advantages of Data Analytics in Healthcare

 

The use of data analytics in healthcare offers many potential benefits. During the Covid pandemic, it was used for forecasting, demand planning, virus traceability and mapping and more. It has various benefits in healthcare ecosystem including:


1. Improved patient care:

By understanding patients' health history with data analytics. Healthcare professionals can adjust treatment plans and make more informed decisions about care.

2. Improved population health:

By inspecting population data using data analytics, healthcare firms can easily identify health trends and develop strategies to improve the health of their communities.
 

3. Better decision-making:

Data analytics can provide an understanding that helps decision-makers to make their decisions better related to care delivery and resource allocation.

 

Application of Data Analytics in Healthcare

 

 

Drug discovery

Drug discovery is a long and complex process involving many different phases, from initial screening to clinical trials. The process is often iterative, with new drugs being tested and developed all the time. However, data analytics has helped speed up the drug discovery process in medicine.  It also helps drugs get approved faster by the Food and Drug Administration and cures patients faster.

 

Diagnosis and treatment

The application of data analytics to healthcare has led to a new era of diagnosis and treatment. By analyzing huge data sets, it became easy for healthcare professionals to identify patterns and trends that were previously hidden. This has restructured the way we approach healthcare and led to better outcomes for patients.

Data analytics has also played a vital role in the evolution of new treatments for diseases. By understanding how diseases progress and which treatments are effective, we can develop more targeted and effective treatments. The application of data analytics in healthcare is a true revolution and is changing the way we care for our patients.

 

Follow-up monitoring

Data analytics have also helped doctors in treating patients at home. Postoperative complications and chronic pain are common after surgery, making it difficult for patients to attend regular routine visits. However, with the help of data analytics, doctors can easily be in touch with patients while they remain at home.

 

Hospital operations

With the help of data analytics, hospitals can increase productivity to ensure they have the resources they need,

  • Appropriate hospital beds,

  • Assign staff hours, and

  • Increase operating room utilization

 

Conclusion

 

Data analytics is becoming increasingly important in healthcare as organizations strive to improve patient care and reduce costs. By leveraging huge data sets, healthcare firms can gain valuable insights about their patients and the healthcare system as a whole. Data Analytics can help in diagnosis & treatment, drugs discovery, hospital operations, follow-ups and much more. 

 

Related Post

Healthcare
May 5, 2023

Application of Data Analytics in Healthcare

 Decisions in the healthcare industry tend to have a substantial effect on pati...
Data Analytics
Healthcare
May 23, 2023

The Future of Patient Care: Embracing Data Analytics for Continuous Improvement

IntroductionIn the era of digital transformation, data has become the lifeblood ...