Top 5 Recent Innovations in Big Data Which Have Greatly Revolutionized the Healthcare Industry

A Brief History

Since the end of the twentieth century, the digitization of information has brought forth a new wave of innovation in healthcare research and services. Big data in healthcare is generated from a vast multitude of sources: medical imaging, electronic health records, payer records, wearable and medical devices, pharmaceutical research, clinical trials, and genomic sequencing — just to name a few.

The integration of big data in healthcare has opened up new research horizons for rare diseases and cancer. And as hospitals and clinics have begun to adopt new technologies driven by big data, they have been able to reduce healthcare costs and pave the way for personalized medicine.

Below are five especially important innovations that have helped revolutionize the healthcare industry in recent years.

Digging Deeper

Big Data Algorithms and Next Generation Sequencing Software

Thanks to exponentially reduced costs of sequencing the human genome, next generation sequencing (NGS) has emerged as a powerful tool for genomic research. NGS produces massive datasets that require the use of big data algorithms for analysis. With the availability of user-friendly next generation sequencing software, both experienced bioinformaticians and bench scientists are able to make sense of big data and draw meaningful conclusions.

NGS is in many ways foundational for many innovations in healthcare, from precision medicine to the study of rare diseases. Whether it is sequencing microorganisms, or creating drought-resistant plants, or identifying genetic variants that are likely to cause autism, researchers rely on next generation sequencing software to map, filter, and analyze expansive datasets with accuracy and speed.

Big Data and the Diagnosis and Treatment of Rare Diseases and Cancer

One of the toughest challenges in the healthcare industry is the design of drugs for rare diseases. Nearly 80 per cent of all rare diseases are hereditary, and their treatment is especially complicated due to a lack of information about the molecular mechanisms of diseases and their response to specific treatments. Using big data algorithms, researchers have been able to identify driver mutations and create targeted therapies to treat these diseases.

Researchers have also been able to use big datasets to predict the success of specific therapies based on patients’ genetic information. For example, a computational algorithm developed by researchers at the University of Hawaii Cancer Research Center identified small sets of genes that accurately predicted the results of chemotherapy on cancer patients. Applied at a larger scale, genetics-driven treatment decisions can improve patient outcomes significantly.

Big Data and Molecular Mechanisms of Cancer

Over the years, researchers have sought the cure for several types of cancers; however, in many cases, the molecular mechanisms of two cancers of the same tissue or organ are different. Big data has enabled the collation of large volumes of data on cancer types, underlying mutations, available treatments and therapies, response to therapies, clinical trials, and much more. Using dynamic computing algorithms, this can potentially enable the perfect stratification of cancer. In addition, publicly available data on libraries like The Cancer Genome Atlas (TCGA), ENCODE, and the Human Genome Project have enabled the progress of personalized care for the millions battling cancer. Genomic sequencing and analysis of cancer tissue against targeted sequences from databases has helped reveal treatment targets and improve prognoses for many patients.

Big Data and 3D Models for Surgeries

Outside of big data genomics, 3D design is another important and promising application of big data within healthcare. The Boston Children’s Hospital has used big data, AI, and 3D design technology to create hyper-realistic models of patients’ organs.

Data shows that detailed and long operations bear a higher risk. Utilizing patient data and information on their conditions, researchers created exact replicas of the patient’s organs for practice. Introducing 3D models before surgeons enter the operating theater can reduce the risks involved in complicated surgeries. Practice makes the surgeries go more smoothly and decreases the chances of encountering unwarranted challenges during the procedure.

Big Data and Decreased Healthcare Costs

In the near future, big data could save Americans over $450 billion per year, according to a survey by McKinsey & Co. Physicians are already able to predict relapses of certain conditions, optimize the outcome of treatments, and reduce the frequency of readmissions. Parkland Hospitals in Dallas, for example, has reduced 30-day readmission rates for heart failure patients by 31%. That translates to savings of $500,000 for Parkland Hospitals. Without big data and AI, there is an overload of information on common and rare diseases. Big data helps address and make sense of information in a way that can help healthcare professionals make better treatment decisions, providing the link between the pieces of the puzzle that completes the picture.

Innovations in big data, from the application of predictive analytics in disease prognosis and treatment, to the use of next generation sequencing software and machine learning to find rare genetic diseases, has helped the healthcare industry offer precise and personalized treatment to the patients. Processing large volumes of highly varied data has finally become a reality for laboratories that handle large amounts of information on a regular basis. This has improved the outcome of complex surgeries and reduced the cost of treatment across several fields of medicine.

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Historical Evidence

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The featured image in this article, a photograph by Ernie Branson of a doctor sitting at his office desk accessing PDQ on his IBM computer, has been released into the public domain worldwide by its author, Ernie Branson (Photographer). This image is a work of the National Institutes of Health, part of the United States Department of Health and Human Services. As a work of the U.S. federal government, the image is in the public domain. This image was released by the National Cancer Institute, an agency part of the National Institutes of Health, with the ID 2282 (image) (next)

Top 5 Recent Innovations in Big Data Which Have Greatly Revolutionized the Healthcare Industry