All About Data Science In Healthcare: Detailed (2021)

Introduction

Data Science applications are everywhere in our regular life. Every sector is revolutionizing Data Science applications, including Healthcare, IT, Media, Entertainment, and many others. Today, healthcare industries are utilizing the power of Data Science successfully, and today we are going to disclose the use of Data Science in Healthcare. Here we will discuss the importance of Data Science in Health care, its benefits, Data Scientists’ role, and applications of Data Science.

1. Why is data important in Healthcare?
2. What does a Data Scientist do in Healthcare?
3. Data Science Benefits for Healthcare System
4. Role of Data Scientist
5. How do I become a Healthcare Data Scientist?
6. Applications or Data Science Use Cases in Healthcare
7. Future of data science in Healthcare

1. Why is data important in Healthcare?

Data is an imperative aspect of every industry and organization. Due to the internet, around 2TB of data is being generated by the users every day. This data includes several types of forms that may be either structured or unstructured. 

Here, the Healthcare sector’s important data includes stress level, heart rate, sugar level, brain activities, blood pressure, and many more. Now there are several latest and advanced technologies to handle such a large amount of data and Data Science is one of them. It can help in monitoring a patient’s health through recorded data. 

The Healthcare professionals or the Doctor can identify the disease symptoms at a very early stage. Many advances and latest tools can also help Doctors to monitor the health of the patients remotely. However, earlier, the Doctors were not able to monitor the patients’ health condition in real time.

Nowadays, with the help of Data Science and Machine Learning applications, Doctors can get real-time information about the patients’ health condition through their wearable devices. Based on this information, the Doctors can send the junior doctors, nurses, or assistants to the patient’s home. 

Not only the Doctors can provide immediate assistance and treatment to the patients, but they can also install several required equipment and devices for the patient’s diagnosis. These devices can collect heart rate, body temperature, blood pressure, etc., information through updates and notification of mobile applications on the top of Data Science. 

This is how health care professionals can use data to treat patients.

2. What does a Data Scientist do in Healthcare?

Healthcare professionals and service providers are competing furiously with the IT vendors to get machine learning experts and data scientists. They are continuously looking for expert data scientists with common programming language knowledge to leverage their data assets.

In the Healthcare industry, the majority of data is unstructured, and it is difficult to access and analyze heterogeneous data. Data Science professionals or data scientists can easily analyze data and take out meaningful and relevant information through unstructured data that can be extremely helpful for Healthcare professionals. 

Data Science in Healthcare is a creative and inherently collaborative field, and the scientists work within an interdisciplinary team environment. They know various tools and techniques to extract raw data. Having a huge amount of data may not be sufficient; to make it meaningful, Healthcare professionals need to extract relevant information from this data, and Data Science professionals are those that help them in this regard.

3. Data Science Benefits for Healthcare System

Data science in healthcareis an essential part and aspect that has transformed the industry. Many facilities and processes have been advanced due to Data Science tools and techniques. It has boosted the speed of treatment and diagnosis. As a result, the workflow of the healthcare system gets enhanced. The real benefits of Data Science in Healthcare include:

• To provide on-time and proper treatment
• To reduce waiting time for treating the patients
• To handle emergency condition effectively
• To smoothen the healthcare workflow
• To reduce failure risk while treating any patient

For Healthcare systems collecting and analyzing data is an important aspect. It can provide them insights into people’s health conditions. They can detect several types of diseases timely by using AI-enabled machines that can provide them with accurate and timely results.

For Healthcare systems, Data Science can help it in providing timely and improved treatment to the patients. Moreover, the death rate can be reduced, and deadly diseases can also be predicted in advance. Not only this even it can help in making better health policies for the management system and public healthcare systems.

4. Role of Data Scientist

Healthcare policies and facilities get advanced. It helps in boosting the productivity of the Healthcare professionals. Data science in healthcare plays an important role in implementing Data Science techniques into the Healthcare system. Data Scientists can extract meaningful information from the given data and help in making predictive models. 

For the Healthcare industry, the major responsibilities of data science professionals include:

• To collect patient’s data or information
• To analyze the hospital’s need or requirement
• To structure and sort data that can be used by the healthcare professionals
• To perform data analytics with the help of several tools
• To implement several algorithms to extract insights from the raw or unstructured data
• To build predictive models with the help of the development teams

It can be said that Data Scientists help Healthcare professionals in providing them the information that can be used by them to treat the patients effectively.

5. How do I become a Healthcare Data Scientist?

Data Scientist does not include a single domain or similar profile for every industry. For all areas of Healthcare, the position of Data Scientists may require different skills. This is why if you are trying to be a Data Scientist, then rather than developing any particular skill, just try to develop and find broad functional skills and then develop your skills as per your interest.

Your course curriculum should be in the way so that it can provide you core skills to pursue your preferred focus. Similarly, if you want to be a Data Scientist for the Healthcare system, then you should have a strong academic background.

It has been noticed that around 73% of Data Scientists have a graduate degree, and it would be great if you will have a master’s degree. Here is a brief description of the required skills for this profession:

• Complete Graduate Degree

It is good for the Data Science profession to complete a graduate degree in IT, maths, physics, or computer science. If you begin and complete your academic career perfectly, then you can be a perfect Data Scientist.

• Master’s Degree

However, a master’s degree is not necessary, but if you complete your master’s, it will be good for your future prospects.

• Some Extra Skills

As per many skilled professionals for Healthcare Data Scientist jobs commonly required skills include Statistics, Machine Learning, Programming language R, Python, and storytelling. Some other common skills include communication skills, soft skills, and some technical background.

6. Applications or Data Science Use Cases in Healthcare

There are several application areas of Data Science in the Healthcare sector. We are going to discuss a few of them:

• Medical Image Analysis

The Healthcare sector is using advanced technology to improve its services. Data science contributes a lot to this field of Healthcare and improves its various aspects, and one of them is medical image analysis. 

Data science helps in analyzing medical images that include CT scan, X-ray, MRI, Sonography, and many more. Doctors have to analyze these images properly to get insights and give better treatment to the patients. Data science in healthcare techniques helps to analyze the image and extract relevant and useful information from the images.

Deep Learning models are created in this way that they can diagnose 26 skin related diseases with 97% accuracy. The Deep Neural Network, Data Science, and Machine Learning help in performing the diagnosis successfully. Some common data science algorithms used for medical image analysis include image processing algorithms, anomaly detection algorithms, and descriptive image recognition algorithms.

• Predictive Analytics in Healthcare

Information is one of the imperative factors for every sector, including Healthcare. Lack of incomplete, unstructured, or less information may lead to wrong or irrelevant treatment for the patient. Thus the information or data of the patient must be collected efficiently. Patient’s data may include blood pressure, sugar level, body temperature, and many more. 

After collecting data, Doctors must also analyze the patient’s data and identify the pattern and correlation in it. By this, the Doctors can identify the disease’s symptoms, stage of the diseases, and many other relevant and meaningful information.

Predictive analytics models are built on the top of this most popular field of Data Science. This helps make some predictions for the patients’ condition and make proper strategies to treat the patients. 

Some benefits of predictive analysis for the healthcare system include faster treatment of the patients, managed and successful treatment of chronic diseases, predicting the future medical condition of the patient, faster documentation, and predicting preventive measures and their condition.

We can say that the Data Science application in Healthcare is a form of predictive analysis that is of greater use for professionals.

• Drug Research

Every day many new issues or diseases are arising in the human body. This may be due to lack of hygienic food, pollution, physical illness, or anxiety. It has been a challenge for medical professionals to find the vaccine or drug for the disease even in a shorter duration. 

The researchers have to find the drug by understanding the character of the disease. They have to find the formula and perform the research and tests. 

With the help of Data Science applications, the researchers can easily and quickly analyze tons of data. Data of millions of test cases can now be analyzed within weeks or months. Thus the effective vaccine or medicine can be launched within a year. Data Science and Machine 

Learning both contribute a lot and can make this possible. 

7. Future of data science in Healthcare

There have been many improvements done in the healthcare sector, but still, some more applications and improvements are required in the future like:

• Digitalization
• Technological Inclusion
• Reduced Cost of Treatment
• Need to be able to handle huge amount of patient’s information

Data science tools and technologies are working for these requirements and have made many improvements as well. Data science is doing wonders in many real-life areas and contributing a lot. There will be much assistance available for doctors and patients through this revolution of data science in the future.

Conclusion

Data science projects have many applications in the healthcare system. Doctors and patients are leveraging the power of this technology. The Healthcare system has the imperative role of data scientists, and you should have properly qualified for this profession. Healthcare professionals are improving their services through such advanced technology. You can also build your career in this field by upskilling with Jigsaw Academy’s robust and comprehensive Data Science courses.

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