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2 posts categorized "Healthcare"

October 07, 2013

Big Data is a Big Deal in Healthcare

Sharon Terry, President and Chief Executive Officer of Genetic Alliance, asserts, "I find myself becoming increasingly optimistic that we are approaching a tipping point for the consumer movement in health." ["Big Data Is Good for Your Health," Forbes, 1 July 2013] Her optimism is fueled by the fact that supermarkets can provide personalized offers to their customers based on loyalty card and point of sale data. If supermarkets can get personal, Terry believes that healthcare providers certainly should be able to provide personalized service as well. If there is one area where personalization is desirable, healthcare is that sector. Terry insists that personalized healthcare "is a movement that will enable consumers to be more active participants in their own health, gain more personalized care and contribute to the acceleration of clinical research and the quest to ameliorate disease."

Another reason for optimism is that an enormous amount of data already exists in the healthcare sector and that mountain of data grows each day. The following infographic provided by Healthcare IT Connect provides a good overview of the Big Data big picture in the healthcare sector. ["Big Data is a Big Deal," by Zach Urbina, 15 May 2013]

Infographic-BIG-DATA and healthcare

Two things really stood out for me in that infographic. First, 80% of healthcare data is unstructured. That means that natural language processing is essential if any real insights are going to be obtained from the data. Second, I thought that the "6 ways that Big Data can transform healthcare" were particularly enlightening. I suspect that Terry agrees that Big Data will transform healthcare in all those ways. She notes that the healthcare sector has "a great deal of work to be done to catch up to [its] counterparts in the retail industry, but just as advances in online, mobile and social technology forever changed the face of shopping, those technologies, combined with breakthroughs in genetic and molecular science, are fueling unprecedented change in healthcare." Tibco analysts report, "Healthcare organizations are increasingly embracing big data to bolster the quality of care while reducing costs, according to a recent survey of senior level executives." ["Big Data Analytics: The Prescription for Better Patient Care," Trends and Outliers, 27 August 2013] Let's take a closer look at how Big Data can transform healthcare, starting with research.

Support Research: Genomics and Beyond

Dr. Bonnie Feldman writes, "Genomics is making headlines in both academia and the celebrity world. With intense media coverage of Angelina Jolie’s recent double mastectomy after genetic tests revealed that she was predisposed to breast cancer, genetic testing and genomics have been propelled to the front of many more minds. In this new data field, companies are approaching the collection, analysis, and turning of data into usable information from a variety of angles." ["Genomics and the Role of Big Data in Personalizing the Healthcare Experience," The Doctor Weighs In, 14 September 2013] For those unfamiliar with the field of genomics, Feldman explains:

"Genomics is the study of the complete genetic material (genome) of organisms. The field includes sequencing, mapping, and analyzing a wide range of RNA and DNA codes, from viruses and mitochondria to many species across the kingdoms of life. Most pertinent here are intensive efforts to determine the entire DNA sequence of many individual humans in order to map and analyze individual genes and alleles as well as their interactions. The primary goal that drives these efforts is to understand the genetic basis of heritable traits, and especially to understand how genes work in order to prevent or cure diseases. The amount of data being produced by sequencing, mapping, and analyzing genomes propels genomics into the realm of Big Data. Genomics produces huge volumes of data; each human genome has 20,000-25,000 genes comprised of 3 million base pairs. This amounts to 100 gigabytes of data, equivalent to 102,400 photos. Sequencing multiple human genomes would quickly add up to hundreds of petabytes of data, and the data created by analysis of gene interactions multiplies those further."

Feldman goes on to explain that the Holy Grail of medicine is to provide individualized treatments for patients. Perhaps the most transformative result of genomic research will be the prediction and treatment of diseases before they actually affect a patient. Feldman explains:

"Personal genomics – understanding each individual's genome – is a necessary foundation for predictive medicine, which draws on a patient's genetic data to determine the most appropriate treatments. Medicine should accommodate people of different shapes and sizes. By combining sequenced genomic data with other medical data, physicians and researchers can get a better picture of disease in an individual. The vision is that treatments will reflect an individual's illness, and not be a one treatment fits all, as is too often true today."

Terry puts it this way, "With access to more information than ever, consumers can take control of their healthcare in ways never before imagined." Elizabeth Rudd notes, "Health issues are increasingly monitored and recorded electronically creating large amounts of data about an individual's health in the process." ["Big Data- About You," Innovation Management.se, 13 February 2013] Although medical personnel prescribe the use of some of those devices, increasingly individuals are buying equipment to monitor themselves. They are part of group known as the Quantified Self movement. Wikipedia explains the movement this way:

"The Quantified Self[ is a movement to incorporate technology into data acquisition on aspects of a person's daily life in terms of inputs (e.g., food consumed, quality of surrounding air), states (e.g., mood, arousal, blood oxygen levels), and performance (mental and physical). Such self-monitoring and self-sensing, which combines wearable sensors (EEG, ECG, video, etc.) and wearable computing, is also known as lifelogging. Other names for using self-tracking data to improve daily functioning are 'self-tracking', 'auto-analytics', 'body hacking' and 'self-quantifying'."

As the healthcare sector aligns itself better in the Big Data era, all of these devices are likely to become part of the Internet of Things (a massive network that will involve machine-to-machine (M2M) communication). Members of the Quantified Self movement are likely to share their collected data with their primary physician, whose cognitive computing system will automatically track a patient's vital data and alert the physician if something worrisome arises. This kind of M2M monitoring will benefit both the healthy and sick. Terry concludes that each passing day "brings us one day closer to a time when our healthcare is as personalized as our commerce, which will empower all of us to participate more actively in our own health."

Tibco analysts note that, in addition to personalized healthcare, Big Data is transforming healthcare in other ways. "Data analytics," they write, "are being used for revenue cycle management, resource utilization, fraud and abuse prevention, population health management, and quality improvement." The infographic above claims that billions of dollars can be saved by leveraging Big Data analytics. With healthcare costs being a major concern in the U.S., such savings would be a blessing. That's why Big Data is such a big deal in the healthcare sector.

September 10, 2013

Healthcare is Forecast to Get Even More Personal

Current debates about healthcare cover topics ranging from how to rein in costs to how to make it more personalized. With the emergence of Big Data analytic tools that can rapidly sequence DNA, test hypotheses, discover new relations, uncover fraud, and so forth, the healthcare sector sits on the cusp of a new era. Exactly where the road will lead remains unclear. What is clear, however, is that Big Data analytics hold the potential of making healthcare much more personal. This is particularly true when it comes to developing treatments for disease. Before this can happen, however, there needs to be more secure data sharing.

In an earlier post entitled Big Data and Better Health, I cited an article by Becky Graebe in which she notes that "four distinct big data pools exist in the US health care domain." Those pools are:

  • Personalized medicine clearPharmaceutical R&D data
  • Clinical data
  • Activity (claims) and cost data
  • Patient behavior and sentiment data

Graebe reports "there is very little overlap in ownership and integration of these pools, though that will be critical in making big strides with big data in health care. ["What is the future of big data in health care?," SAS Voices, 6 May 2013] Even if data integration occurs slowly, Hellmuth Broda believes that strides will be made in personalized medicines and treatments. ["Personalized Medicine and Big Data," Pondering Technology, 30 July 2013] He writes:

"While many doomsayers describe the Pharmaceutical industry as one where the golden days are over and where more and more enterprises are bound to be falling off the 'Patent Cliff' or get lost in space, many rather visionary companies have ignited their rocket boosters and are catapulting themselves onto firm ground again. This rocket booster consists of treatments for rare diseases and Personalized Medicine. The two chambered booster combines especially targeted diagnostics with targeted therapies and utilises cloud services alongside with Big Data analytics. This new method of transport brings with it new demands on research, clinical trials, production, logistics, information systems and the overall business model."

To achieve maximum benefit from Big Data analytics, Broda agrees with Graebe that more integration and cooperation needs to occur. He also lists a number of challenges facing the pharmaceutical industry. He continues:

"These challenges and more importantly how Pharma companies tackle them, are shaping the future of the industry, with some key trends already emerging:

  • To solve complex tasks, 'coopetition' with other companies will become the norm
  • The journey towards Personalized Medicine
  • Race to Biologics
  • Pairing of drugs with their accompanying diagnostics
  • Stricter regulations on compliance
  • New demands on privacy and security
  • Big Data approaches yielding new insight into drug action correlations

"These challenges put new demands on governance, processes, business models and the information systems, which will build the foundation for these new endeavours. New trends in technology adaptation will support and enable these objectives."

The ability to gather and analyze Big Data is the common thread that weaves it way through all of the trends identified by Broda. One of the dilemmas that will confront the healthcare sector regarding personalized medicines will be cost. Broda explains:

"Drugs will become less generic (and low-cost) and more tailored for specific demographics in the future (and more high value/high cost). There are huge benefits to this, including the fact that these drugs are harder to copy so they retain their value better for the producer and they are also more effective as they can meet more specialist needs. While the current trend is looking at groups of people, maybe based on age or ethnicity, this will evolve in the 21st Century into truly personalised drugs on an individual basis reflecting the patient's genetic predisposition."

There are good reasons why doctors and patients alike would like to see more personalized medicines. As Broda explains, "This increasing personalisation of therapy will significantly benefit patients, by both raising efficacy and reducing side-effects." While drug companies may relish the thought of developing high value/high cost drugs, that's probably not good news for the masses. If Big Data analytics can be used to bring the cost of drug development down, a win-win situation could develop. It has been proven that profits can still be made by selling products to the so-called "bottom billion" consumers if products can be produced at the right price point in the right amount. Big Data analytics should be able to help pharmaceutical companies with that challenge as well. No one benefits when pharmaceutical companies go out of business or when medicines are manufactured in unsafe conditions in poorly regulated plants. For the immediate future, however, it looks like personalized medicines are going to benefit the rich more than the poor.

Broda makes the point that "drugs and their diagnostics walk hand-in-hand." As I pointed out in my earlier post (mentioned above), Big Data and cognitive reasoning systems are playing a role in diagnostics as well as drug development. A paper from the Institute of Medicine, entitled Making the Case for Continuous Learning from Routinely Collected Data, asserts that a "a learning health system" will be beneficial in a number of ways.

"The availability and reliability of large volumes of relevant longitudinal digital data from a variety of clinical and nonclinical sources are core features of a system that learns from each care experience, a learning health system. Common clinical repositories include data from electronic health record (EHR) systems used to manage patient care and claims data necessary for billing purposes. In some cases, data sources can be linked, using either institution-specific identifiers or matching algorithms, to create disease-specific patient registries that enable research. Integration of large pools of disparate clinical data from EHRs and claims is a major function of health information exchanges, which will be increasingly important to ensure seamless management of health information across institutions. Nonclinical sources of patient information may also include data from retail sales of over-the-counter medications, dietary supplements, walking and running shoes, and personal preferences and behaviors."

Although technology is important in the healthcare sector, professionals in that field can't afford to concentrate only on technology if things are going to get better. Like other business sectors, the healthcare sector needs to keep technology, people, and processes in balance. Deanna Pogorelc reports that Dr. Kevin Fickenscher, president and CEO of the American Medical Informatics Association, made that point at a conference earlier this year. ["The problem with big data in health? Too much focus on technology instead of people/process," MedCity News, 7 May 2013] Pogorelc reports that Fickenscher told conference participants, "One of the things that has been a problem in healthcare is that we tend to spend too much time talking about the technology and not enough time talking about the people and the process. So my personal bias is that while technology is important [...] if we don't deal with the people and process, we will not solve these other issues; we won't have good change management, and we won't have good implementation, which is where the value gets created from large data."

One of the newest fields being developed that will make healthcare even more personal is nanomedicine. "Nanomedicine, refers to highly specific medical intervention at the molecular level for curing disease or repairing damaged tissues." ["Nanomedicine," Associates Degree in Nursing] The article states, "Though in its infancy, could we be looking at the future of medicine? Early clinical trials certainly look promising." The article was accompanied by the following infographic.

Nanomedicine: The Future of Medicine
Source: Nanomedicine: The Future of Medicine

It should be abundantly clear that both diagnoses and treatments for diseases are going to be more personal in the future. That should be a good thing; especially if costs can be held in check.