Data Science & Healthcare

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Health Care & Data Science

Healthcare industry generates tremendous amount of data every day. EHRs, wearables, billing and more continue to generate data relentlessly. It is a great opportunity for health care providers to take required action on insights and provide better health care to the patients. Data Science is the helping them unlock the potential of data. In conjunction with AI and ML, Data Science is enabling healthcare companies to achieve operational excellence across all disciplines, from computerizing medical records to drug discovery and genetic disease exploration. And this is just the beginning.

Healthcare and data science are often linked through finances as the industry attempts to reduce its expenses with the help of large amounts of data. Data science and medicine are rapidly developing, and it is important that they advance together. However, the success of data science depends on a deep understanding of how it might be used, the process it could potentially fit into, and a relationship with the clinicians who will be using it. While the accuracy of your predictive model is important, it’s just as important to know how it will be used and that it will be used effectively.

Why Data Science cannot be ignored?
  • Optimised Cost of Drug Discovery: Drug development is a complex and costly affair. Significant amount of research, testing, time and money investment goes into introducing a new drug. Sometimes the costs can be as high as $2.6 billion to introduce a new drug. Data Science uses advanced mathematical algorithms to create simulation of how the drugs would interact with body proteins and predict the rate of success. It can also provide insights into genetic issues arising out of specific drugs and diseases.
  • Wearables enable Self Health Management: Personal wearables are cool accessory and more. They record important health readings like heart rate, blood pressure, sleep pattern, pulse etc. In elders’ wearables are of great significance. The family members and medical staff remain updated real time. Data Science deduces all the data collected from the wearables and enable action on preventive healthcare.
  • Improved Diagnostics: Though we are in best times in terms of technological advancements however diagnostics in 21st century is far from being perfect. BBC story in 2018 revealed that approximately 40,000 to 80,000 deaths occurred in USA due to wrong diagnosis. Data Science helps analyst apply deep learning techniques to process extensive clinical and lab reports to conduct a quicker and more precise diagnosis.
Challenges
  • Healthcare Data Hard to Access: Dr. Robert Mittendorf explains that for Data Science to really make effective presence in healthcare, it needs to have access to large volume of data. However, access to large amount of relevant data is restricted due to privacy issues, records identification concerns and HIPAA.
  • Constructing Medical Solutions is taking longer time than expected: “We implemented our first EMR systems 8 years ago hoping it would improve efficiencies. We are now on our fourth system and remain disappointed. Right now, it is more of a hassle than a time saver. It has actually disrupted the doctor – patient relationship by forcing a screen between the two,” Dr. Jose I Almeida.
  • Ethical Issues: In case of Data Science giving a wrong diagnosis, who would be responsible? Who is to be blamed if a smart algorithm makes an error and comes up with false prediction? These questions need to be answered and regulated before Data Science is made mainstream in healthcare.

Era of Human - Data Science

Exciting times in healthcare for sure. In a world where humans now have bionic eyes and pills from 3D printing, the entire healthcare industry is experiencing a revolution of sorts. Data Science is the key to answer the most fundamental question in healthcare: How do we know what works? Deepened understanding of diseases and averages brings new treatments to patients faster. The time for Human – Data Science has arrived.

Even with greatest technologies and most robust data, domain expertise is the critical link. Expertise to deal with complexity and lack of uniformity of human data to capture, link and visualize is the key to success. However, such talent is not easy to find, especially in a healthcare sector.

Advantages of an upskilled Workforce

Healthcare companies are upskilling their current workers as they know the existing systems and have complete know how of the internal processes. It is hence easier for them to implement emerging Data Science techniques to achieve the healthcare firms’ objective.

How Can SkillUp Technologies help you leverage Data Science?

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