In this video from the 2013 HPC User Forum, Darren Schulte from Apixio presents: Knowledge-driven Outcomes for Healthcare.
Apixio delivers actionable insights from textual, scanned, and coded data for optimal risk management, population management, and revenue.”
Download the slides (PDF) or check out the HPC User Forum Video Gallery.
Electronic health records (EHRs) were supposed to revolutionize healthcare, saving up to up to $81 billion a year through innovative new efficiencies and the collection of massive amounts of data that could be used to help prevent as well as cure diseases.
Well, it hasn’t happened. Writing in Computerworld, Lucas Mearian reports that EHRs have become more of a hindrance than a help.
He quotes Dr. Robert Walker, director of health innovation for the U.S. Army Surgeon General, who said in an interview, “The electronic medical record has become an impediment versus something that was going to streamline your day. It took the focus away from the patient and put it all on the computer. People are clicking boxes and turning their backs to patients. It’s all about jamming data into this thing.”
But despite EHR’s shortcomings, the fact is that the program is gathering great quantities of invaluable clinical data and storing it in data warehouses. Researchers can access and analyze this data using powerful Big Data engines like Hadoop.
That’s the real renaissance that’s going to happen in health care,” Walker said. “With big data, what happens in a doctor’s office is going to be vastly different from what we see today. The top five or 10 things that people die from in America are life-style induced. That’s absurd. Maybe instead of vital signs, I’m just going to look at what you buy in a grocery store.”
Mearian cites several areas that are already reflecting the promise of improved health care with the help of Big Data analytics. For example, advanced drug therapies are being developed through the study of genomics – a.k.a. personalized medicine. Or there is the free open source software called i2b2 informatics that has been developed by Dr. Isaac S Kohane, a professor of pediatrics and health sciences technology at Harvard Medical School & Children’s Hospital. The software is being used by more than 100 academic health centers around the world to identify genetic predictors for diseases and harmful drugs.
Dr. Walker believes the real game changer in medicine will be an engaged patient, one who will enter his or her own data through the use of mobile devices,” Mearian reports. “And that data can include not just medical information, but also lifestyle updates involving diet and exercise. By having a full picture of a patient’s lifestyle, doctors are better equipped to help patients avoid the onset of chronic illnesses. Then, once the data is in an EHR, big data analytics engines could offer physicians information about patients who may need to adjust their caloric intake, level of activity or the amount of sleep they get.
Walker comments: “The answer to the obesity problem is not the operating table, but the dinner table, and that’s where we need to get to. In this country, we’re putting billions of dollars into healthcare and our life expectancies are less than in countries that spend a fraction of what we do. We’re really doing disease care and not healthcare today.”
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On Tuesday, April 2, President Obama announced a research initiative that has the ambitious goal of “revolutionizing our understanding of the human brain,” according to a White House press release.
Know as BRAIN (Brain Research through Advancing Innovative Neurotechnologies), the initiative is being launched in FY 2014 with an initial budget of about $100 million, a modest amount given the project’s goals.
In short, BRAIN is designed to help researchers find “…new ways to treat, cure, and even prevent brain disorders, such as Alzheimer’s disease, epilepsy, and traumatic brain injury.” Included is support for new technologies that will allow researchers to produce dynamic pictures of the brain that show how individual brain cells and complex neural circuits interact in real time.
This is a foray into Big Data. The initiative will let researchers amass and analyze the data needed to “…explore how the brain records, processes, uses, stores, and retrieves vast quantities of information, and shed light on the complex links between brain function and behavior.”
Among the many public and private organizations involved in the effort are the National Institutes of Health (NIH), the Defense Advanced Research Projects Agency (DARPA), and the National Science Foundation (NSF). NSF in particular is leading the charge in applying the technologies and techniques of Big Data to the initiative.
The National Science Foundation will play an important role in the BRAIN Initiative because of its ability to support research that spans biology, the physical sciences, engineering, computer science, and the social and behavioral sciences,” according to the White House release. “The National Science Foundation intends to support approximately $20 million in FY 2014 in research that will advance this initiative, such as the development of molecular-scale probes that can sense and record the activity of neural networks; advances in ‘Big Data’ that are necessary to analyze the huge amounts of information that will be generated, and increased understanding of how thoughts, emotions, actions, and memories are represented in the brain.”
In a story in Information Week posted the same day, senior editor J. Nicholas Hoover, writes, “On a conference call with reporters after the President’s announcement, National Institutes of Health director Francis Collins said that the brain-mapping initiative might eventually require the handling of yottabytes of data. A yottabyte is equal to a billion petabytes.”
That’s Big Data at its mind-boggling best.
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In the midst of all the ballyhoo surrounding Big Data and how it’s going to “transform how we live, work, and think” (a borrowing from the subtitle of the excellent book Big Data by Viktor Mayer-Schönberger and Kenneth Cukier), it’s encouraging to hear about applications that are actually living up to all the hype.
Case in point: Rip Empson writing in TechCrunch this week chronicles the rise of Bina Technologies, a Silicon Valley startup that makes it possible to analyze genomic data that until now, because of sheer volume, has been gathering digital dust.
The cost of genomic sequencing has been dropping, reports Empson, and we are well on the way to the $1000 genome and a new era of personalized medicine. Bina plans to be part of that era.
Although still in startup mode, Bina has already fielded a number of Big Data-based applications. For example, the company is working with the Medical Center of Wisconsin to implement whole genome sequencing for newborns in the Center’s neonatal intensive care unit. And back in the Valley, the Stanford Genetics Department is using the Bina platform to analyze several hundred whole human genomes in less than five hours, a task that normally takes several days.
Bina is poised to become a significant player in the $15 billion genomic research industry.
In this RichReport video, Narges Bani Asadi presents: Bina – Accelerating Data-Driven Healthcare.
Founded in 2011 by a group of Ph.Ds, big data junkies and bioinformaticians from Stanford and University of California Berkeley, Bina picks up and analyzes this genomic data that has been, until now, almost unusable,” comments Empson. “Through Bina, research universities, pharmaceutical companies and clinicians can get access to data that focuses on the rare variants in our genetics — in other words, those that cause our predispositions to cancer, newborn disorders, down syndrome, sickle cell, and so on.
Through the ability to better parse and make use of this data, the idea is that these downstream players can then facilitate significant improvements in patient care, treatment and, really, basic understanding of how the body works via insights at the molecular level.”
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In this special guest feature, Anchita Magan from [x]cube DATA writes that the element of quality has to be considered in quantifiable data.
Significance of Big Data
The entire cosmos has been turned into an aggregated ocean of Data – structured or unstructured, systematic or unsystematic, useful or useless. This zillion of roughly organized data is needed to be stored, arranged and analyzed so that it can be brought to use by the business houses to evaluate the dimensions of their success as well as their bottlenecks. Whether a CEO or a COO, a Marketing manager or an operations head, an HR Employee or an IT engineer, they all make use of big data analysis for decision making. But the valid question that arises is ‘which attribute of big data is more important – Quality or Quantity?’
Importance of Quantity and Relevance of Quality
The term’ big’ itself is closely related with quantity. But extracting qualitative and fruitful data out of the bulk is the important task which is needed to be accomplished for sustainable growth, effective utilization of resources and to answer the present and foreseeable challenges. Experts says that we analyze only one percent of Data and hence can tap only 1 percent of its potential. But through systematic data analysis of the rest 99% of data, a revolution can be brought in all the sectors of business era – be it retail, healthcare, telecom, financial services or IT.
But it is also observed that without valid evaluation, collecting hoards of data won’t provide the necessary insights into the business.
Application of Big Data in Health Care Industry with reference to Quality and Quantity
With the boom in Internet and communication technology, big data analysis has gained a lot of significance at the vast global stage. It generate insights on the business performance as a whole by evaluating both the internal and external data collected worldwide.
According to a report by McKinsey five areas with maximum big data potential are health care, retail sector, manufacturing industry, public sector and personal location data.
Taking healthcare industry into consideration, which is currently facing major challenges making their services affordable and accessible to all sections of the society and to the remotest of locations. It has been observed that there is an extensive use of health information and health care data which is processed and analyzed to plan, determine and administer the quality of health services and scientific research for major breakthroughs in the fields of diagnosis and medication. The government as well as private organizations provide multiple statistical reports which throw light on the administrative data regarding the expenditure, consumption and utilization of health services, keeping in account the patient’s records, lab records, number of hospitals, bed utilization rates, out-patient visits, occupancy rates, human resources, etc.
This structured and unstructured data can be a guiding light only when it is properly categorized, processed and analyzed to extract the fruitful insights and discarding the useless content, thus turning the quantitative data into a qualitative one. This is achieved through techniques of big data analytics which is a key to the dynamic potential capability of an organization. These big data techniques include text data mining, machine learning and statistical programming, which are backed by widely used technologies like NoSQL databases and Hadoop Framework.
These technologies of big data analysis further helps to control fraud by enabling the auditors to identify the transactions that indicate the activities of artifice or treachery and thus strengthening the anti fraud mechanism of hospitals.
Some applications of big data in healthcare are:
The best example can be Bumrungrad International hospitals which are effectively using the clinical analytics and Electronic Medical Record (EMR) to deliver better care for its patients, to analyze their needs and to enhance the patients’ satisfaction along with making their service cost effective. The hospital manages patient information utilizing an integrated hospital information system that uses digital radiology systems. A case study by Intel Corporation unveiled that Bumrungrad commissioned the development of a custom total hospital information system to service both the front office and back office, to maximize both safety and efficiency as well as to drastically reduce the potential for medication error.
Thus it is important to understand that the huge amount of big data has to be well examined, reviewed and verified to deduce the useful content; hence adding quality to the quantifiable data.
About the Author
This article was written by Anchita Magan from [x]cube DATA. [x]cube DATA provides big data solutions and services to companies across various industries that wish to harness the large data sets at their disposal and gain actionable insights from it.
Over at the New York Times, Nick Bilton writes that the story of Google Flu Trends speaks volumes about the importance of context as we enter a world of big data.
The Google site attempts to track the spread of influenza based on user searches. The problem is, Google’s algorithm looks only at the numbers, not at the context of the search results.
In today’s digitally connected world, data is everywhere: in our phones, search queries, friendships, dating profiles, cars, food, reading habits. Almost everything we touch is part of a larger data set. But the people and companies that interpret the data may fail to apply background and outside conditions to the numbers they capture. “Data inherently has all of the foibles of being human,” said Mark Hansen, director of the David and Helen Gurley Brown Institute for Media Innovation at Columbia University. “Data is not a magic force in society; it’s an extension of us.”
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In a move designed to slow the spiraling costs of U.S. healthcare, Deloitte Consulting and Intermountain Healthcare today announced an alliance that leverages Big Data and analytics to reduce costs and improve patient outcomes.
Deloitte brings to the table its informatics and professional services capabilities; Intermountain has the data. Since the 1970s, Intermountain has been using computers to amass what it describes as “one of the world’s largest and most detailed repositories of clinical and financial data coming from its 22 hospitals and 185 clinics.”
The trick, of course, is to transform all that data into meaningful insights – a job for Big Data analytics.
But the two companies are looking beyond their immediate interests and, as part of the five year deal, are planning to develop and provide health analytics insights to the entire medical community.
Health care is on the verge of realizing significant gains from big data, but it takes new tools and new approaches around collaboration to get there,” said Jason Girzadas, a principal at Deloitte. “This alliance will work to provide the health-care industry a destination center for the insights needed to change health care.” Andrew Vaz, Deloitte’s chief innovation officer adds, “We hope to accelerate the development of what the Institute of Medicine refers to as a ‘learning health-care system.’ By bringing data-driven insights to organizations managing care and developing the therapies of tomorrow, we hope to ignite innovation and promote quality, safety and value in health care.”
Transforming what many believe to be a broken U.S. Healthcare system – e.g., a third of our spending on healthcare is wasted – has been the Holy Grail for politicians and practitioners alike. So far no one has succeeded.
Can the application of analytics to massive collections of healthcare data help ease the pain? In today’s press release, Bert Zimmerli, CFO of Intermountain, issued this optimistic statement, “In addition to Deloitte’s capabilities, our organizations share a commitment to the mission of transforming health care. Together we will leverage our decades of experience and work to revolutionize the way medical insights are discovered and used to improve care.”
We fervently hope they succeed.
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