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Biomedical

Modified on

21 Mar 2023 08:15 pm

The Use of Big Data in Healthcare and How it can be Used to Improve Medical Outcomes and Develop New Treatments

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Skill-Lync

Remember when a person’s medical data had to be recorded pen to paper, vast amounts of data just sat there in a home draw or cabinet in a hospital? This data can not be searched or referenced. After the digital revolution, the healthcare industry has evolved, The healthcare sector produces up to 30% of the world's data. By 2025, that percentage will have increased to 36%, marking a sizable increase as health-related data production outpaces that of other significant industries. In this blog, we will explore the latest trends and innovations in medical informatics and how they can help shape the future of healthcare. 

Introduction 

Big data in the healthcare industry refers to the massive amounts of data produced using digital technology to collect patient records and monitor hospital performance that would otherwise be too large and complex for conventional technologies. Big data can be used to improve,

  • Medical outcomes
  • Reduce costs
  • Increase efficiency

Big data can be used to identify trends in patient health and to identify potential problems before they become serious. Healthcare providers can identify areas where they can be improved by reducing wait times or improving communication between providers and patients.

How can Big Data Improve Medical Outcomes?

With the help of big data, healthcare professionals gain insights into patient health and behavior, enabling them to make more informed decisions about treatments and care. 

By analyzing large datasets of patient data, researchers can identify potential treatments and develop new drugs. For example,

  • With Electronic Health Records (EHRs), every person has a digital profile with information about their background health history, such as

1) Allergies

2) Medical test results

3) Prescribed medications

Records are accessible to providers from the public and private sectors and are shared via secure information systems. EHRs can also provide alerts and reminders when a patient needs a fresh round of lab work, or they can monitor medications to check on compliance with doctors' orders.

Benefits of Big Data in Healthcare

  • Big Data can help improve patient care by providing more accurate diagnoses and treatments. 
  • It can help reduce healthcare costs by providing better insights into the effectiveness of treatments and identifying potential cost savings.
  • Big Data can identify potential health risks and provide insights into disease progression.
  • It can improve healthcare service efficiency by providing more accurate and timely information to healthcare providers.

Challenges of Big Data in Healthcare

  • Amount of data 

The sheer amount of data generated in the healthcare industry can be overwhelming and difficult to manage and analyze. The data is often stored in different formats and systems, making it difficult to integrate and analyze. 

  • Privacy and security

Healthcare data is highly sensitive and must be protected from unauthorized access. Healthcare organizations must ensure that they have the proper security measures to protect patient data. 

  • Infrastructure

Finally, healthcare organizations must have the necessary infrastructure to store and analyze large amounts of data. This can be expensive and time-consuming, and it requires specialized expertise. 

Developing New Treatments with Big Data

Big data has allowed medical professionals to gain insights and make previously impossible decisions. By analyzing large sets of data, medical professionals can identify patterns and trends that can be used to improve patient outcomes and develop new treatments. 

  • It can also identify potential drug interactions, enabling medical professionals to decide which drugs to prescribe.
  • Big data can also identify genetic disease markers, helping develop personalized treatments for specific conditions. By analyzing large sets of genetic data, medical professionals can identify genetic markers that can be used to develop new treatments or predict the effectiveness of existing treatments. 

Unsurprisingly, this trend has permeated the pharmaceutical sector, promising to maximize drug value and raise prescribing standards. 

  • A third-party company that oversees the management of medication coverage for customers that offer health insurance policies. 
  • The US-based business gathered information from 83 million patients, ranging from the patient's clinical and behavioral traits, such as picking up a prescription, to Tweets directed against the business. 
  • Express Scripts may forecast critical events using this data, such as who is most likely to develop an addiction to a certain medicine or who is not following the recommended course of treatment. 
  • If that occurs, the company offers individualized interventions and support immediately to ensure clients follow their recommended course of therapy.

Conclusion 

The future of big data in healthcare is bright. The applications of big data in the healthcare sector demonstrate how the life-saving capabilities of medical analytics have seen greater growth. To learn more about similar topics, Skill-Lync is here to help you. Check out the courses such as Post Graduate Program in Medical Technology and Data Analytics and Data Science by Skill-Lync. Talk with our experts now and book your free demo sessions!


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Navin Baskar


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Skill-Lync

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