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Table of contents
1.
Introduction
2.
Big Data Analytics (BDA)
3.
Big Data in Healthcare
4.
Examples of Healthcare Analytics in Big Data
5.
Job opportunities in Healthcare BDA
6.
Advantages of Healthcare Analytics in Big Data
7.
Challenges of Healthcare Analytics in Big Data
8.
Future of Healthcare Analytics
9.
Frequently Asked Questions
9.1.
What is Big Data Analytics?
9.2.
What is the use of BDA in medical imaging?
9.3.
Why is it difficult to implement Healthcare Analytics in big data?
10.
Conclusion 
Last Updated: Mar 27, 2024

Healthcare Analytics in Big Data

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Introduction

In today's digital age, the Healthcare industry is going through a big change because of the multiple options offered by Big data analytics. With the increasing amount of patient data, recording and finding important information from them has become more important. 

Healthcare analytics in big data

In this article, we will be discussing the relationship between Healthcare and Big Data, see some examples of Healthcare Analytics in Big Data, and finally list the respective advantages and disadvantages.

Big Data Analytics (BDA)

In today's digital world, large volumes of data are produced daily, for example, bank records, patient records in healthcare, social media records, etc. Big data refers to these large bulks of data generated from different sources at an increasing speed. This data cannot be processed or maintained with the help of conventional methods or software.

Now it is very crucial to understand the trends and find useful information from this data and to do so, we need specific advanced analytics methods. 

Big data analytics (BDA) is analyzing and fetching valuable information from big data. It involves using advanced tools and algorithms to understand the patterns and mark the trends from complex datasets.

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Big Data in Healthcare

Healthcare Analytics in Big Data can play a big role in shaping the healthcare industry. There has been a  major growth in healthcare data from medical imaging, lab tests, genetics, EHRs, etc. Big Data analytics provides multiple opportunities to Healthcare staff for growth in the industry.

By applying BDA methods, large amounts of structured, semi-structured and unstructured data can be analyzed to gain useful information and improve the treatment of patients.

Examples of Healthcare Analytics in Big Data

Applications of BDA in Healthcare

Today Big Data finds many applications in healthcare. Some of them are:

1. Healthcare analytics in Big Data is used in real-time monitoring of patients' vitals like a heartbeat, blood pressure, etc. Algorithms are used to analyze this data and generate alerts in case of any abnormal shift in the data.

2. Analysing the data patterns is helpful in the early detection of diseases. Huge volumes of patients' data, like medical history, genetic information, and lifestyle standards, can be studied to identify risk trends and take preventive actions.

3. Electronic Health Records (EHRs) are one of the most important uses of Healthcare analytics in Big Data. EHRs contain detailed patient data, including medical histories, diagnoses, medications, and lab results. By applying BDA to EHRs, healthcare staff can find patterns that cannot be identified through traditional analysis methods. This analysis can help identify disease patterns.

4. Healthcare analytics in Big Data is used to analyze computational biology for medical data. The data encoded in the DNA can be processed to identify genetic differences and drug developments. With big data analysis, understanding complex biological systems becomes easier.

5. Healthcare analytics in Big Data is used to store and study thousands of medical images. Radiologists use BDA algorithms to identify trends in pixels, which can be converted into numbers. This, in turn, helps in disease diagnosis. These algorithms remember more images than any healthcare staff.

6. Wearable devices like fitness trackers, smart watches, smart inhalers, etc., can be used to collect and analyze data about the health of the patient. This can help doctors and patients to understand the triggers and symptoms of their diseases. 

7. BDA is also useful in population health management by marking the disease trends and outbreaks in a large group of people. 

Job opportunities in Healthcare BDA

job opportunities in Healthcare BDA

Some of the job opportunities in Healthcare Big Data Analytics are:

  • Healthcare Data Analyst
  • Healthcare Data Engineer
  • Healthcare Analyst Consultant
  • Healthcare Data Statistician
  • Healthcare Informatics specialists

Advantages of Healthcare Analytics in Big Data

The advantages of Healthcare Analytics in Big Data are:

  • Healthcare analytics in big data allows improved decision-making based on data proof, thereby decreasing errors. Medical experts analyze the patterns of large amounts of data that help in more accurate diagnoses.
     
  • Healthcare analytics can make tasks more efficient, saving time and money. By analyzing the patterns of the resources used, the tasks can be run better, resulting in more happy patients.
     
  • Healthcare analytics in Big data is quite helpful in predicting the occurrence of diseases. The risk factor can be calculated by analyzing the historical records of patients, and the respective preventive steps can be taken.
     
  • Healthcare analytics in Big Data is used in research and development; by analyzing different datasets of medical tests and patient records, major scientific growth can be made in the industry.

Challenges of Healthcare Analytics in Big Data

The disadvantages of Healthcare Analytics in Big Data are:

  • The Data in the medical industry is very complex and unstructured. It consists of all kinds of data like medical records, lab tests, medical images, electronic health records, etc. Maintaining data accuracy and consistency is a big challenge here.
     
  • Data privacy and security are other problems faced in Healthcare Analytics in Big data. Healthcare data might also include certain sensitive information, including the patient's personal information, his/her medical history, etc., which should be protected against data disclosures and thefts.
     
  • A large volume of data is produced daily in the Healthcare industry, and storing this huge volume of data is another challenge. Scalable systems with increased performance are required to store this Big Data, which can be costly.
     
  • Skilled human resources having knowledge of healthcare analytics are required to process and analyze huge volumes of data. There may be a lack of such experts in the healthcare industry.

Future of Healthcare Analytics

With the increasing use of EHRs, smart wearable devices, and other digital health technologies, the amount of data produced is increasing greatly. In the near future, we can expect healthcare analytics to play a big role in personalized medicine by analyzing the patient’s datasets. Every patient would receive effective care under a customized treatment plan. Advanced analytics methods can be used to find patterns and predict the outcomes of diseases. Additionally, with Healthcare Analytics in Population Health Management, actions can be taken to prevent and control epidemics. Thus, healthcare analytics can reshape the healthcare industry by transforming patient care.

Frequently Asked Questions

What is Big Data Analytics?

Big data analytics analyzes and identifies useful information from large amounts of structured, semi-structured, and unstructured data. It involves using advanced methods and algorithms to understand the patterns in complex datasets.

What is the use of BDA in medical imaging?

Big Data analytics is used to store and study thousands of medical images. Radiologists use BDA algorithms to mark the trends in pixels, which can be converted into numbers. This, in turn, helps in disease diagnosis. These algorithms remember more images than any healthcare staff can, thus increasing their productivity.

Why is it difficult to implement Healthcare Analytics in big data?

It is difficult to have Healthcare analytics in Big Data. There can be the Data complexity problem, data privacy and security issues, storage problems, and a lack of skilled people in the healthcare industry to analyze and process large amounts of complex data.

Conclusion 

Congrats, Ninja, on making it to the finish line of this article! There is no doubt that Healthcare analytics in Big data can play a powerful role in shaping the future of healthcare. Till now, it has improved the decision-making process, which has led to better patient outcomes and has helped the healthcare industry to carry out its tasks more efficiently.

We wish this blog has helped you better understand Healthcare analytics in Big Data. Keep learning! We suggest you read some of our other articles on Big Data: 

  1. Introduction to Big Data
  2. Analytics and Big Data
  3. Big Data Analytics Example
     

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