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Role of Data Science In Modern Healthcare

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Last Updated on: August 12, 2022

Healthcare is one of those industries that always experience positive growth. This growth is mainly in sheer quantity and may not be on the quality side.

This is especially true for developing countries like India, which houses a large population base. With the increases in the demand, the industry grows, however leaving the quality and standards lagging behind a bit.

The rapid increase in technology could fix this gap in the sector growth and its quality. This is where modern data science methods come into play.

This article discusses this very topic and would also highlight the possible future that the relationship between data science and the healthcare sector would hold.

Why Do We Use Data Science in Healthcare?

Did you know that the human body can generate as much as 2 TB of data on a daily basis? In fact, almost 30% of the data volume in the world is accounted for by the healthcare industry, including Electronic Health Records (EHR), clinical reports, prescriptions, investigations, etc. In earlier times, all this data had to be sorted, analysed and stored manually, which was not just hugely time-consuming and expensive, but also led to the risk of human error.

Data science has come to the rescue, easing the collection, storage, structuring, analysis and reporting of health care data. Today, it is proving invaluable in providing doctors, scientists, pharmaceutical companies, hospitals, etc. with important insights that can improve health care delivery and even the prevention of diseases.

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Benefits of Data Science in Healthcare

Data science is helping in advancing medical science, while also boosting the accuracy of diagnosis. Data science is also fulfilling an important role in health care by helping develop more effective drugs and other treatments. Some of the other major benefits include:

  • Reducing the risk of treatment failure
  • Ensuring timely treatment delivery
  • Easing workflows in health care systems
  • Preventing unnecessary delays in handling emergencies
  • Reducing patients’ waiting time

The Role of a Data Scientist in Healthcare

The primary role of a data scientist in the field of health care is to apply various techniques, such as statistics and probability, data visualisation, AI, machine learning, etc., to elicit insights from the data. So, their responsibilities include:

  • Collection of patient data
  • Analysing the data to provide actionable insights
  • Analysing hospital needs to support data-driven decision-making
  • Sorting and structuring data for later use
  • Data analytics, with the use of various tools
  • Using algorithms on data to elicit insights
  • Developing predictive models in collaboration with development teams

Role of Data Science in Healthcare

Data science has found applications in multiple areas of health care. The most prominent applications are:

Medical Imaging Analysis

Traditionally, doctors need to manually examine X-Rays, MRI images and CT scans to identify anomalies. This can be difficult when there are microscopic irregularities. Data science can easily analyse these images and scans to find even the minutest deformities to ensure accurate diagnoses. It can also help with various image processing techniques, such as image recognition with the use of Support Vector Machines, edge detection, image enhancement and reconstruction, etc.

Drug Discovery

The pharmaceutical industry relies on data to create better medication. Manual drug discovery is complicated, time-consuming and very expensive. However, data science and machine learning have revolutionised the process, offering key insights to pharma companies and enhancing the success rate. Even the collection of historical data to support the process of drug development has improved due to the use of data science.

Patient Health Monitoring

Data scientists have developed wearable devices that collect a wide range of data, such as heart rate, blood glucose levels, sleep patterns and brain activity. This data is then analysed with the help of machine learning and any changes in the health indicators can help doctors predict or diagnose disorders. The health of chronically ill patients can be tracked even while they are at home.

Predictive Analytics

Data science has proved its value for predictive analysis in a variety of industries, and healthcare is no different. Here, historical data is used to find patterns and make accurate predictions. The role of data science in this aspect of healthcare is to find correlations and associations of symptoms, habits and diseases to make predictions. This can then help enhance patient care and the management of chronic ailments. It can also improve the efficiency of pharmaceutical logistics and supply chains.

Genomics

Data science has also found application in this area of health care for the sequencing and analysis of genomes. In fact, the entire process has become much faster and more cost-effective due to data science. Genomics is helping find connections between genes and the health of an individual, while also providing insights into the impact of drugs on specific genetic issues.

Virtual Assistance

Data science has made it possible to provide support for patients 24/7. Patients can input their symptoms and gain insights regarding potential diseases. Those suffering from conditions like Alzheimer’s Disease and other brain disorders can receive support with their daily tasks. In fact, Stanford University has created a chatbot that offers therapy for people suffering from depression.

If you too would like to make a difference in the delivery of healthcare, enrol in one of the data science courses offered by GeekLurn, in partnership with Nasscom and IBM. These courses are focused on making you career-ready through training by industry experts, personalised mentorship and much more.

Key Data Science Skillsets For Healthcare Domain

  • Medical Coding Classification Systems
  • Dimensionality Reduction
  • Natural Language Processing (NLP)

IBM Watson – A Special Mention

Watson is IBM’s supercomputer which uses Artificial Intelligence (AI) and advanced analytical algorithms. It answers questions thrown at it by anyone. It is named after the founder of IBM, Thomas J Watson.

Healthcare has been the primary focus of IBM. They continuously keep updating their Watson technology with the latest changes in the healthcare sector. In India, the popular healthcare brand, Apollo, recently adopted IBM’s Watson for its Oncology and Genomics. The IBM cognitive computing platforms help doctors make informed and personalised decisions on cancer care.

Future of Data Science in Healthcare

Now that Data Science has made enough inroads into the healthcare stream, it could now look to find ways to cure the currently incurable ones namely AIDS, Cancer, and other serious chronic diseases.

Though there are concrete protection and safety nets in place, they don’t seem to be effective all the time. Advancements could be made in this area as well.

Rural areas are still in need of good medical services. Data Science could help reduce the overall cost incurred so that medical services could be offered to these areas at a much lower price.

Rapid improvements in the delivery of healthcare are being fuelled by technological advancements and increasing digitalisation. Further improvement can be driven by the ability to reduce treatment duration and costs, as well as the ability to handle large populations of patients.

Data science can play an important role in taking health care into the future through its various applications. It can help wade through the huge volumes of data to give actionable insights that lead to doctors being able to provide more personalised care, while enhancing the accuracy of diagnosis and treatment. In fact, with the help of data analytics, early diagnosis can lead to a better prognosis for a wide range of ailments.

In short, data science and its applications in health care can take the industry to new heights, while giving the common man access to cutting-edge treatments.

Conclusion

The applications of data science in the healthcare sector elevate its standard manifold. With the healthcare industry evolving and growing exponentially, the onus is on them to make it balance with the quality of service provided.

With the level of technology available to the industries and to laymen, the ideal movement of healthcare should be to reduce the cost of their services thereby moving to a world where healthcare would be either free of cost or at very minimum cost. This would ensure the eradication of a lot of life-threatening diseases from the face of the planet.

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Working as a Content Specialist & is an SEO blogger. Along with this, he also enjoys philosophy and poetry. He is talented enough to forge great ideas into brilliant and engaging stories that can dazzle the audience to the point of selling his writings at fat prices.

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SBS Dayaabaran

Working as a Content Specialist & is an SEO blogger. Along with this, he also enjoys philosophy and poetry. He is talented enough to forge great ideas into brilliant and engaging stories that can dazzle the audience to the point of selling his writings at fat prices.
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