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Intel Health & Life Sciences

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Healthcare systems are coping with an unprecedented level of change. They’re managing a new regulatory environment, a more complex healthcare ecosystem, and an ever-increasing demand for services—all while facing intense cost pressures.

 

These trends are having a dramatic impact on EMR systems and healthcare databases, which have to maintain responsiveness even as they handle more concurrent users, more data, more diverse workflows, and a wider range of application functionality.

 

As Intel prepared to introduce the Intel® Xeon® processor E7 v3 family, we worked with engineers from Epic and InterSystems to ensure system configurations that would provide robust, reliable performance. InterSystems and VMware were also launching their next-generation solutions, so the test team ran a series of performance tests pairing the Intel Xeon processor E7-8890 v3 with InterSystems Caché 2015.1 and a beta version of VMware vSphere ESXi 6.0.

                                

The results were impressive. “We saw the scalability of a single operational database server increase by 60 percent,” said Epic senior performance engineer Seth Hain. “With these gains, we expect our customers to scale further with a smaller data center footprint and lower total cost of ownership.” Those results were also more than triple the end-user database accesses per second (global references or GREFs) achieved using the Intel® Xeon® processor E7-4860 with Caché® 2011.1.

 

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These results show that your healthcare organization can use the Intel Xeon processor E7 v3 family to implement larger-scale deployments with confidence on a single, scale-up platform.

 

In addition, if you exceed the vertical scalability of a single server, you can use InterSystems Caché’s Enterprise Cache Protocol (ECP) to scale horizontally. Here again, recent benchmarks show great scalability. A paper published earlier this year reported more than a threefold increase in GREFs for horizontal scalability compared to previous-generation technologies.

 

This combination of outstanding horizontal and vertical scalability—in the cost-effective environment of the Intel® platform—is exactly what needed to meet rising demands and create a more agile, adaptable, and affordable healthcare enterprise.

                                                                              

What will these scalability advances mean for your healthcare IT decision makers and data center planners? How will they empower your organization deliver outstanding patient care and enhance efficiency? I hope you’ll read the whitepapers and share your thoughts. And please keep in mind: Epic uses many factors, along with benchmarking results, to provide practical sizing guidelines, so talk to your Epic system representative as you develop your scalability roadmap.

 

Read the whitepaper about vertical scalability with the Intel Xeon processor E7 v3.

 

Read the whitepaper about horizontal scalability  with Intel Xeon processors.

 

Join and participate in the Intel Health and Life Sciences Community

 

Follow us on Twitter: @IntelHealth, @IntelITCenter, @InterSystems, @vmwareHIT

 

Steve Leibforth is a Strategic Relationship Manager at Intel Corporation

The health and well-being of any workforce has a direct impact on worker productivity, efficiency and happiness, all critical components of any successful organization. With this in mind, Intel has developed a next-generation healthcare program, called Connected Care, which includes an integrated delivery system based on a patient-centered medical home (PCMH) approach to care.

The shift to value-based compensation and team-based care is driving the need for improved collaboration and patient data sharing between a growing number of providers and medical systems. While we’ve successfully introduced the Connected Care program in smaller locations, bringing it to Oregon and the larger Portland Metropolitan area presented us with a common healthcare IT challenge, interoperability. Shah.PNG

 

Advanced Interoperability Delivers Better Experiences for Clinicians, Patients

 

Intel is using industry standards to address these challenges, geared towards advancing interoperability in healthcare. The ability to quickly share clinical information between on-site Health for Life Center Clinics and delivery system partners (DSPs) enables:

 

  • Efficient and seamless experiences for members
  • Informed decision-making by clinicians
  • Improved patient safety
  • Increased provider efficiency
  • Reduced waste in the delivery of healthcare, by avoiding redundant testing

 

These improvements will help us make the Institute for Healthcare Improvement’s (IHI’s) Triple Aim a reality, by improving the patient experience (quality and satisfaction), the health of populations, and reducing the per-capita cost of health care.

 

Kaiser and Providence Part of Intel’s Connected Care Program

 

Intel’s Connected Care program is offering Intel employees and their dependents two new options in Oregon. Kaiser Permanente Connected Care and Providence Health & Services Connected Care have both been designed to meet the following requirements of Intel and their employees:

 

  • “Optimize my time” – member and provider have more quality interactions
  • “Don’t make me do your work” – no longer rely on members to provide medical history
  • “Respect my financial health” - lower incidence of dropped hand-offs/errors
  • “Seamless member and provider experience” - based on bi-directional flow of clinical data

 

Now that we have eliminated the interoperability barrier, we can enable strong coordination between providers at Health For Life Centers (on-campus clinics at Intel), and the Kaiser and Providence network providers, enabling the ability to quickly share vital electronic health records (EHRs) between varying systems used by each organization.

 

In our efforts to deliver optimal care to every Intel employee, we sought solutions that would ensure all providers serving Intel Connected Care members are able to see an up-to-date patient health record, with accurate medications, allergies, problem lists and other key health data, every time a Connected Care member needs care.

 

Learn More: Advancing Interoperability in Healthcare

 

What questions do you have?

 

Prashant Shah is a Healthcare Architect with Intel Health & Life Sciences

When I used to work for the UK National Health Service, I encouraged doctors and nurses to use mobile devices. But that was 15 years ago, and the devices available only had about two hours of battery life and weighed a ton. In other words, my IT colleagues and I were a bit overly optimistic about the mobile devices of the time being up to the task of supporting clinicians’ needs.

 

So it’s great to be able to stand up in front of health professionals today and genuinely say that we now have a number of clinical-grade devices available. They come in all shapes and sizes. Many can be sanitized and can be dropped without damaging them. And they often have a long battery life that lasts the length of a clinician’s shift. The work Intel has done over the last few years on improving device power usage and efficiency has helped drive the advancements in clinical-grade devices.

 

It is very clear that each role in health has different needs. And as you can see from the following real-world examples, today’s clinical-grade devices are up to the task whatever the role.

 

Wit-Gele Kruis nurses are using Windows 8 Dell Venue 11 Pro tablets to help them provide better care to elderly patients at home. The Belgian home-nursing organization selected the tablets based on feedback from the nurses who would be using them. “We opted for Dell mainly because of better battery life compared to the old devices,” says Marie-Jeanne Vandormael, Quality Manager, Inspection Service, at Wit-Gele Kruis, Limburg. “The new Dell tablets last at least two days without needing a charge. Our old devices lasted just four hours. Also, the Dell tablets are lightweight and sit nicely in the hand, and they have a built-in electronic ID smartcard reader, which we use daily to confirm our visits.”

 

In northern California, Dr. Brian Keeffe, a cardiologist at Marin General Hospital loves that he can use the Microsoft Surface Pro 3 as either a tablet or a desktop computer depending on where he is and the task at hand (watch video below).

 

 

When he’s with patients, Dr. Keeffe uses it in its tablet form. “With my Surface, I am able to investigate all of the clinical data available to me while sitting face-to-face with my patients and maintaining eye contact,” says Dr. Keeffe.

 

And when he wants to use his Surface Pro 3 as a desktop computer, Dr. Keeffe pops it into the Surface docking station, so he can be connected to multiple monitors, keyboards, mice, and other peripherals. ”In this setup, I can do all of my charting, voice recognition, and administrative work during the day on the Surface,” explains Dr. Keeffe.

 

These are just two examples of the wide range of devices on the market today that meet the needs of different roles in health. So if you’re an IT professional recommending mobile devices to your clinicians, unlike me 15 years ago, you can look them in the eye and tell them you have a number of great clinical-grade options to show them.

 

Gareth Hall is Director, Mobility and Devices, WW Health at Microsoft

The National Health IT (NHIT) Collaborative for the Underserved kicked off their Spring Summit with a briefing at the White House in April to commemorate the 30-year anniversary of the Heckler Report.

 

This landmark task force report, published in 1985 by then-DHHS Secretary Margaret Heckler, first introduced the country to the documented health disparities that our racial and ethnic minority populations were facing. MJ blog.jpg

 

While we have made progress since, recent advances in technology have provided us with a unique opportunity to introduce real change, right now. To help carry this momentum, I participated in a lively panel discussion with industry leaders at the Summit, “Moving the Needle” for innovation success, where we discussed key action items that will help us deliver an effective and efficient healthcare ecosystem:

 

• Engage consumers to participate and manage their own health and wellness through education.

• Work with providers serving multicultural communities to increase Health IT adoption and their participation in programs that support delivery of high quality, cost effective care.

• Deliver effective educational, training and placement programs that can prepare members of multicultural communities for Health IT related careers.

• Establish and implement policies that support individual and community health empowerment and promote system transformation.

• Identify priority areas where gaps exist regarding the ability to use innovative health technologies to address disparities and plan actionable next steps.

 

Reactive approach to healthcare costly for payers and providers

Managing the complex health needs of the underserved has long been labor intensive and costly for both patients and clinicians. The lack of health coverage and other complications have traditionally presented significant challenges for a large portion of this population.

 

While the Affordable Care Act (ACA) now makes healthcare financially feasible for millions of newly insured individuals, a troubling trend may persist among some members of underserved communities who continue to only seek care after experiencing an acute health emergency, making their visits extremely costly to payers and providers. These visits usually require several medications, frequent monitoring of vitals, and lifestyle changes in diet and exercise.

 

They also typically require people who may live with instability in multiple aspects of life, to schedule and adhere to ongoing medical appointments and diagnostic tests. This isn’t an effective, realistic, or affordable approach to health and wellness, for payers, providers or consumers. But it can be addressed through raised awareness regarding the impact of health decisions and improved access to healthy options.

 

Organized data critical for effective education and outreach

Access to accurate and organized data is key when we talk about making personalized healthcare a reality. Actionable data is driving today’s cutting-edge research, leading to improvements in preventative health and wellness, as well as life-saving treatments.

 

Edge devices, like wearables, biosensors, and other consumer devices, can gather large amounts of data from various segments of the population, correlating behaviors related to diet and exercise. With end-to-end edge management systems, researchers and clinicians can have real-time access to locally filtered actionable data, helping them make accurate and educated discoveries on population behavior with amazing levels of insight.

 

Understanding where individual and population health trends are headed in advance will enable providers to customize their education and outreach services, saving time and resources from being wasted on programs with little to no impact. With electronic health records (EHR), clinicians can access a patient’s history on secure mobile devices, tracking analyzed data that impacts wellness plans and treatments.

 

Quality measures for prevention, risk factor screening, and chronic disease management are then identified and evaluated to provide support for practice interventions and outreach initiatives. Along with edge and embedded devices, they can play a key role in promoting self-management and self-empowerment through better communication with clinical staff.

 

Gathering data from the underserved population

Providers who treat underserved populations and vulnerable citizens often have less access to EHRs and other technologies that help them collect, sort and analyze data from patients. Another factor is that these clinics, hospitals and community centers are often reacting to crisis, instead of preventative outreach and education. This places greater strain on staff, patients and resources, while straining budgets that are partly limited by payer reimbursement.

 

So the big question is, “how do we leverage the power of data within complex populations that are often consumed by competing real-world priorities?”

 

It starts with education, outreach, and improved access to healthier lifestyle options. It continues by equipping clinics, hospitals and resource centers in underserved communities with the latest Health IT devices, wearables, software and services. As innovators it is our job to craft and articulate a value proposition that is so compelling, payers will realize that an initial investment in innovation, while potentially costly, will reduce expenditures significantly in the long run.

 

By educating and empowering all consumers to more actively participate in the management of their own wellness, the need for costly procedures, medications and repeated visits will go down, saving time and resources for payer and provider – while delivering a better “quality of life” for everyone.

I have just spent the better part of two weeks involved in the training of a new 50-strong sales team. Most of the team were experienced sales people but very inexperienced in pharmaceutical sales. They had a proven record in B2B sales, but only 30 percent of the team had previously sold pharmaceutical or medical device products to health care professionals (HCPs). Clearly, after the logistical and bureaucratic aspects of the training had been completed, most of the time was spent training the team on the medical background, disease state, product specifics and treatment landscape/competitor products.

 

Preparing the team for all eventualities and every possible question/objection they may get from HCPs was key to making sure that on the day of product launch they would be competent to go out into their new territories and speak with any potential customer. With particular reference to this product it was equally important for the team to be in a position to speak with doctor, nurse and pharmacist.

 

The last part of the training was to certify each of the sales professionals and make sure that they not only delivered the key messages but that they could also answer most of the questions HCPs would fire at them. In order to do this the sales professionals were allowed 10 minutes to deliver their presentation to trainers, managers and medical personal. The assessors were randomly assigned questions/objections to be addressed during the presentation.

 

The question remains, “does this really prepare the sales person for that first interaction with a doctor or other HCP?” Experience tells us that most HCPs are busy people and they allow little or no time for pharmaceutical sales professionals in their working day. The 90 seconds that a sales professional gets with most of their potential customers is not a pre-fixed amount. Remember, doctors are used to getting the information they need to make clinical decisions by asking the questions they need answers to in order to make a decision that will beneficially affect their patient(s). So, starting the interaction with an open question is quite simply the worst thing to do, as most doctors will take this opportunity to back out and say they do not have time.

 

The trick is to get the doctor to ask the first question (that is what they spend their lives doing and they are good at it) and within the first 10-15 seconds. Making a statement that shows you understand their needs and have something beneficial to tell them is the way you will get “mental access.” Once the doctor is engaged in a discussion, the 90-second call will quickly extend to 3+ minutes. Gaining “mental access” is showing the doctor that you have a solution to a problem they have in their clinical practice and that you have the necessary evidence to support your key message/solution. This has to be done in a way that the doctor will see a potential benefit for, most importantly, their patients. In order to do this the sales professional needs to really understand the clinical practice of the person that they are seeing (i.e. done their pre-call planning) and have the materials available to instantly support their message/solution.

 

The digital visual aid is singularly the best means of providing this supporting information/data, as whatever direction the sales professional needs to go in should be accessible in 1-2 touches of the screen. Knowing how to navigate through the digital sales aid is essential as this is where the HCP is engaged or finding a reason to move on.

 

What questions do you have? Agree or disagree?

As physicians, we're taught to practice evidence-based medicine where the evidence comes primarily from trade journals that document double blind, randomized control trials. Or, perhaps we turn to society meetings, problem-based learning discussions (PBLD), or peer group discussion forums. We are dedicated to finding ways to improve patient outcomes and experience, yet we miss huge opportunities every day.

 

We are lost in a sea of data, left to debate continuous process improvement with ‘gut feelings’ and opinions. We do the ‘best we can’ because we lack the ability to glean meaningful perspective from our daily actions. As an anesthesiologist, I know there's a wonderful opportunity for analytics to make a difference in our surgical patients’ experience, and I can only imagine there are similar opportunities in other specialties.int_brand_879_LabDocTblt_5600_cmyk._lowresjpg.jpg

 

Here are three undeniable reasons analytics should matter to every physician:

 

Secure Compensation

Quality compliance is here to stay, and it’s only becoming more onerous. In 2015, the CMS-mandated Physician Quality Reporting System (PQRS) finally transitioned from bonus payments to 2 percent penalties. It also raised the reporting requirements from 3 metrics to 9 metrics across 3 domains, including 2 outcome measures.

 

Unfortunately, in the absence of the right technology, compliance is too often considered just another costly burden. We’re relegated to either rely on unresponsive 3rd party vendors to update our software or else we’re forced to hire additional human resources to ‘count beans’. More frustratingly, we rarely see these efforts translate into meaningful change for the patients we serve. We arrive at the erroneous conclusion that these efforts only increase costs while offering no tangible benefits.

 

What if our technology was flexible enough to keep up with changing regulations while also making us faster and more intelligent at our jobs?  How would this change our perception of regulatory requirements? Thankfully such solutions exist, and with our input they can and should be adopted.

 

Gain Control

It’s too easy for providers to limit themselves to the “practice of medicine” – diagnosing and treating patients – and disengage from the management of our individual practices. We do ourselves a disservice because, as physicians, we have a significant advantage when it comes to interpreting the ever-increasing government regulations and applying them to our patients’ needs. There is often latitude in this interpretation, which ultimately gives rise to incorrect assumptions and unnecessary work. When we assume the responsibility for setting the definitions, we gain control over the metrics and consequently influence their interpretations.

 

By engaging in our analytics, we’re equipped to speak more convincingly with administration, we gain independence from poor implementations, and we gain freedom from added inefficiencies. We lose the all-too-common “victim perspective”, and we return to a position of influence in how and why we practice the way we do. Through analytics, we are better positioned to improve our patients’ experiences, and that can be incredibly gratifying.

 

Transform Your Industry

This ability to leverage real-time analytics has already transformed other industries. In retail, the best companies deliver exceptional service because their sales representatives know exactly who we are, what we’ve purchased, how we’ve paid, when we’ve paid, etc. Because they know our individual preferences at the point of sale, they deliver first-class customer service. Consider the example of Target, who used predictive analytics to identify which customers were pregnant simply from analyzing their transactional data, thus allowing them to intelligently advertise to a compelling market segment.

 

Imagine leveraging this same capability within the realm of surgical services. What if we could deliver individualized patient education at the time it’s needed. For example, a text message the evening before surgery reading, “It’s now time to stop eating.” Or, an automated message when the patient arrives to the surgical facility, stating, “Here’s a map to the registration desk”. There are plenty of opportunities to leverage mobility and connectivity to deliver personalized care throughout the surgical experience. Further, by analyzing the data generated during the course of that surgical experience, what if we could predict who was likely to be dissatisfied before they even complained. Could we automatically alert guest relations for a service recovery before the patient is discharged? There’s no doubt - of course, we can! We just need appropriate management of our surrounding data.

 

Conclusion

Through analytics we have the ability to secure our compensation, gain more control of our practices, and transform our industry by improving outcomes, improving the patient experience, and reducing costs.

 

When we’re equipped with analytical capabilities that are real-time, interactive, individualized, and mobile, we've implemented a framework with truly transformative power. We've enabled a dramatic reduction in the turnaround time for continuous process improvement. As regulatory requirements continue to increase in complexity, we have the opportunity to either work smarter using more intelligent tools or else surrender to an unfriendly future. Fellow practitioners, I much prefer the former.

 

What questions do you have? What’s your view of analytics?

As we celebrate Nurses Week across the world, I wanted to highlight the impact of telehealth on the changing nature of nursing and healthcare more generally.

 

But before I do that we must recognise that for all of the technological advancements, the priority for nurses is to provide the best patient care. And telehealth is helping nurses to do just that. With ageing populations across most developed nations putting additional stress on healthcare systems there is an increasing need to free up costly hospital beds and nurses time by monitoring and managing patients remotely.

 

From blood pressure to fall sensors, telehealth is enabling nurses to provide better care by being able to work more efficiently and be better informed about a patient’s condition. Recent research (see infographic below) suggests that telehealth will increase tenfold from 2013 to 2018 and with advances around the ‘Internet of Things’ bringing enhanced levels of connected care, I see nurses being able to do a great job even better in the future.

 

 

telehealthInfographic 6.jpg

 

If you haven’t noticed lately, we’re seeing an increase in demand for analytics driven by health reform. However, for many organizations, the culture needs to change in order to fully embrace analytics as part of the standard practice of care. Many will agree that there is too much information for clinicians to rely only on training and experience as they treat patients rather than leverage insights from analytics for clinical decision support. Providers who embrace analytics will be best positioned to improve patient care from the perspective of decreased cost, improved efficiency and enhanced patient experience.


In my role at Intel, I’m often asked where “big data” capabilities can apply to healthcare. One of the areas that always top my list are the clinical records. Roughly 70 percent of the electronic health record (EHR) includes clinically relevant information that is unstructured or in free form notes, meaning potentially critical pieces of information are not easily accessible to providers. There are many tools that can use sophisticated natural language processing techniques to pull out the clinically relevant information however, the culture has to be ready to accept those kinds of solutions and use them effectively.

 

Overcoming challenges

Personalized medicine analytics is a combination of data bits coming from multiple data sources and each comes with its own unique set of challenges. There is the payer side, the clinical side, the biology, life sciences and genomics side and finally, the patient side and the work that we’ve been doing is in all of these areas. We look at big data and health and life sciences as the aggregation of all of these different data sources and address the challenge of how this content will be generated, moved, stored, curated and analyzed. 

The goal is to take advantage of the sophisticated analytics and sophisticated technology capabilities and merge those with the changes to workflow on the healthcare side and the life sciences side and pull those two areas together to deliver care specific to an individual.  This is very different from treating a large cohort of all diabetes patients or all breast cancer patients in exactly the same way. 

Personalized medicine is really two different perspectives. First, is on the genomics side, where you include as an attribute to the patient care pathway the genome of that patient, comparing it against a reference genome to determine what is different about the patient as an individual or how their tumor genome differs from their normal DNA. Second, there’s the population health aspect to personalization; really understanding all of the data that is available in patient records whether it be structured or unstructured data and then developing care plans specific to that individual.  For example, micro segmenting a population taking into account comorbidities and socio-economic factors with the help of advanced analytic tools.

 

Safety opportunities

There was a recent article in the Journal of Patient Safety[1] that stated that there may be more than 400,000 premature deaths per year that are preventable in a hospital setting. Furthermore, 10-20 times more than that statistic cause serious harm but don’t result in death.  For example, big data and analytics are being used to help identify and diagnose sepsis earlier so that it can be treated more effectively and be less costly for the payer and provider.


A great example of using wearables to better understand disease progression is the work that Intel is conducting in partnership with the Michael J. Fox Foundation for Parkinson’s research (see video above). Individuals wearing specialized devices will be tracked around the clock; observations will be recorded 300 times a second and all information will be stored in the cloud. What this means for researchers is that they will go from evaluating a few data points per month to observing 1 gigabyte of data every day.

 

By analyzing the existing data that is available, adding wearables, improving the velocity in analyzing data, there are a lot of opportunities to improve patient safety using some of these tools. 

What questions about clinical analytics do you have? How are you using data in your practice or organization?
 


[1] James, John T. PhD. “A New, Evidence-based Estimate of Patient Harms Associated with Hospital Care.” Journal of Patient Safety (2013): http://journals.lww.com/journalpatientsafety/Fulltext/2013/09000/A_New,_Evidence_based_Estimate_of_Patient_Harms.2.aspx

 

Today marks the start of Nurses Week so here at Intel we want to celebrate, with you, what we consider to be the real superheroes of healthcare by saying #ThankYouNurses. Throughout the next seven days we’ll be bringing you some fantastic blogs which demonstrate our appreciation for nurses while highlighting how technology is helping to deliver best-ever patient care.

 

I want you to help us to say thank you to nurses across the world by tweeting your appreciation using the hashtag #ThankYouNurses throughout the week. If you have received some fantastic care from a nurse or want to highlight the work of a great colleague I’d love to help you say thanks by sharing your stories on Twitter – so tag a nurse, @intelhealth and say #ThankYouNurses with us.

 

As a nurse practitioner I’ve seen up close how technology is truly revolutionising nursing through enhanced mobility, whether that be having access to the latest medical records when visiting a patient at home or helping a patient to understand their condition better by displaying an injury on a tablet at the bedside in a hospital. 

 

We are also working with Microsoft in Health to highlight all that nurses do at www.microsoft.com/nurses so please check out some of the great nursing stories there too. Nurses Week ends on a high with International Nurses Day on May 12th so let’s keep the conversation going throughout the week.

 

I very much look forward to sharing our collective appreciation for nurses with you.

President Obama recently unveiled the Precision Medicine Initiative — a bold new enterprise to revolutionize medicine and generate the scientific evidence needed to move the concept of precision medicine into every day clinical practice. The million-dollar question, or multi-million-dollar question, is how do we make this mainstream?

 

The emerging platform will be this amalgamation of data from payers, clinics, EHRs, images, laboratories, contract research organizations, pharma, and an analytics tool to make sense of all this data. Then to accelerate innovation and foster collaboration, we need tools to make all this valuable data we have amassed public for clinicians, researchers and bioinformatics specialists to practice their art.

 

Partnering with the Multiple Myeloma Research Foundation (MMRF), GenoSpace is leveraging Intel® AES-NI technology to deliver high-performance encryption to ensure the security and privacy of patient data and needed analytics MMRF requires to further its mission of  accelerating the pace of treating and curing multiple myeloma and changing the paradigm of how all cancer research is conducted.

 

The GenoSpace architecture is hosted on Amazon Web Services (AWS) which provides flexibility and scalability for it developers and customers. To ensure the utmost security for this public cloud implementation, GenoSpace takes a ground-up approach to encryption. Its solutions gather all of the data that will be subject to analysis and layer encryption on top of that to safeguard the confidentiality of sensitive healthcare data stored on AWS or data that travels over the Internet. This adds an important extra measure of protection to AWS built-in security features.

 

Recently, GenoSpace evaluated the benefits of Intel® Advanced Encryption Standard New Instructions (Intel® AESNI), a silicon-based instruction set that accelerates encryption on Intel® Xeon® processors, which GenoSpace uses to process data. Meeting its customers’ performance and usability demands was a key objective for GenoSpace, given the amount of encryption and decryption that occurs when its software is used for analytics. To determine how the query response time of its population analytics application would be affected by encryption and by the hardware encryption acceleration that Intel® AES-NI provides, GenoSpace ran a series of tests focused on measuring the performance aspects of encrypting and decrypting stored data.

 

The key findings of this test revealed that Intel® AES-NI-enhanced encryption had a markedly positive influence on the performance of the GenoSpace Population Analytics application.

 

  1. Provider library choice significantly impacts results. The choice of encryption provider library and AES mode had the largest impact on performance. While Bouncy Castle showed no appreciable improvement with respect to Intel® AES-NI, the NSS library with Intel® AES-NI enabled performed more than 78% faster than Bouncy Castle and is the obvious choice for encryption. For decryption, NSS was approximately 96 percent faster than Bouncy Castle and 90 percent faster than SunJCE. With respect to AES modes, ECB, which is the simplest algorithm, outperformed other modes. However, because ECB is less secure than the other modes, and given the sensitivity of healthcare data, it is generally not appropriate for healthcare applications. For best performance and security, test results implied that the combination of CBC and the NSS provider library should be used, as it has the shortest routine time.
  2. Intel® AES-NI significantly decreases the impact of increasing key length. Typically, increasing the length of the AES encryption key (which functions much like a password) to strengthen security also increases encryption/decryption time. As key length increases, one expects a near linear increase in encrypt/decrypt times. But the study showed that by using NSS with Intel® AES-NI, the impact of doubling key length was reduced twenty-fold.
  3. The benefits of Intel® AES-NI increase with the size of data sets. In Phase 2 of the study, where sample genomic data was used, GenoSpace found that enabling Intel® AES-NI improves request times by nearly 9 percent. In fact as the size of the data sets scales up, there are even greater performance gains—an almost 14 percent improvement.
  4. Intel® AES-NI had less impact on the application’s overall performance. GenoSpace concluded that with Intel® AES-NI, encryption can scale more efficiently than other operations, such as data serialization, sorting, and filtering.

 

Intel® AES-NI-enhanced encryption significantly enhances the performance and usability of the GenoSpace Population Analytics offering, which, in turn, results in increased user productivity and satisfaction with the overall solution. Enabling high-performance and secure solutions paves the way for healthcare organizations to embrace the use of genetic population analytics to significantly increase the effectiveness of research, healthcare, and disease treatment options.

 

While healthcare workers and researchers put these tools to work, they can be confident that Intel® AES-NI accelerated and hardened encryption can help mitigate serious security breaches.

 

What questions about encryption do you have?

Can your data platform keep up with rising demands?

 

That’s an important question given the way changes in the healthcare ecosystem are causing the volume of concurrent database requests to soar. As your healthcare enterprise grows and you have more users needing access to vital data, how can you scale your health record databases in an efficient and cost-effective way? Decarolus.jpg

 

InterSystems recently introduced a major new release of Caché and worked with performance engineers from Epic to put it to the test. The test engineers found that InterSystems Caché 2015.1 with Enterprise Cache Protocol (ECP) technology on the Intel® Xeon® processor E7 v2 family achieved nearly 22 million global references per second (GREFs) while maintaining excellent response times.

 

That’s more than triple the load levels they achieved using Caché 2013.1 on the Intel® Xeon® processor E5 family. And it’s excellent news for Epic users who want a robust, affordable solution for scalable, data-intensive computing.

 

Intel, InterSystems, and Epic have created a short whitepaper describing these tests. I hope you’ll check it out. It provides a nice look at a small slice of the work Epic does to ensure reliable, productive experiences for the users of its electronic medical records software. Scalability tests such as these are just one part of Epic’s comprehensive approach to sizing systems, which includes a whole range of additional factors.

 

These test results also show that InterSystems’ work to take advantage of modern multi-core architectures is paying off with significant advances in ultra-high-performance database technology. Gartner identifies InterSystems as a Leader in its Magic Quadrant for Operational Database Management Systems,[1] and Caché 2015.1 should only solidify its position as a leader in SQL/NoSQL data platform computing.

                                                                    

Intel’s roadmap shows that the next generation of the Intel Xeon processor E7 family is just around the corner. I’ll be very interested to see what further performance and scalability improvements the new platform can provide for Epic and Caché. Stay tuned!

 

Read the whitepaper.

 

Join & participate in the Intel Health and Life Sciences Community: https://communities.intel.com/community/itpeernetwork/healthcare

 

Follow us on Twitter: @InterSystems, @IntelHealth, @IntelITCenter

 

Learn more about the technologies

 

Peter Decoulos is a Strategic Relationship Manager at Intel Corporation

 


[1] InterSystems Recognized As a Leader in Gartner Magic Quadrant for Operational DBMS, October 16, 2014. http://www.intersystems.com/our-products/cache/intersystems-recognized-leader-gartner-magic-quadrant-operational-dbms/

Recently I’ve travelled to Oxford in UK, Athens in Greece and Antalya in Turkey for a series of roundtables on the subject of genomics. While there were different audiences across the three events, the themes discussed had a lot in common and I’d like to share some of these with you in this blog.

 

The event in Oxford, GenofutureUK15, was a roundtable hosted by the Life Sciences team here at Intel and bought academics from a range of European research institutions together to discuss the future of genomics. I’m happy to say that the future is looking very bright indeed as we heard of many examples of some fantastic research currently being undertaken.

 

Speeding up Sequencing

What really resonated through all of the events though was that the technical challenges we’re facing in genomics are not insurmountable. On the contrary, we’re making great progress when it comes to the decreasing time taken to sequence genomes. As just one example, I’d highly recommend looking at this example from our partners at Dell – using Intel® Xeon® processers it has been possible to improve the efficiency and speed of paediatric cancer treatments.

 

In contrast to the technical aspects of genomics, the real challenges seem to be coming from what we call ‘bench to bedside’, i.e. how does the research translate to the patient? Mainstreaming issues around information governance, jurisdiction, intellectual property, data federation and workflow were all identified as key areas which are currently challenging process and progress.

 

From Bench to Bedside

As somebody who spends a portion of my time each week working in a GP surgery, I want to be able to utilise some of the fantastic research outcomes to help deliver better healthcare to my patients. We need to move on from focusing on pockets of research and identify the low-hanging fruit to help us tackle chronic conditions, and we need to do this quickly.

 

Views were put forward around the implications of genomics transition from research to clinical use and much of this was around data storage and governance. There are clear privacy and security issues but ones for which technology already has many of the solutions.

 

Training of frontline staff to be able to understand and make use of the advances in genomics was a big talking point. It was pleasing to hear that clinicians in Germany would like more time to work with researchers and that this was something being actively addressed. The UK and France are also making strides to ensure that this training becomes embedded in the education of future hospital staff.

 

Microbiomics

Finally, the burgeoning area of microbiomics came to the fore at the three events. You may have spotted quite a lot of coverage in the news around faecal microbiota transplantation to help treat Clostridium difficile. Microbiomics throws up another considerable challenge as the collective genomes of the human microbiota contains some 8 million protein-coding genes, 360 times as many as in the human genome. That’s a ‘very’ Big Data challenge, but one we are looking forward to meeting head-on at Intel.

 

Leave your thoughts below on where you think the big challenges are around genomics. How is technology helping you to overcome the challenges you face in your research? And what do you need looking to the future to help you perform ground-breaking research?

 

Thanks to participants, contributors and organisers at Intel’s GenoFutureUK15 in Oxford, UK, Athens in Greece and HIMSS Turkey Educational Conference, in Antalya, Turkey.

 

The transition toward next-generation, high-throughput genome sequencers is creating new opportunities for researchers and clinicians. Population-wide genome studies and profile-based clinical diagnostics are becoming more common and more cost-effective. At the same time, such high-volume and time-sensitive usage models put more pressure on bioinformatics pipelines to deliver meaningful results faster and more efficiently.

 

Recently, Intel worked closely with Seven Bridges Genomics’ bioinformaticians to design the optimal genomics cluster building block for direct attachment to high-throughput, next-generation sequencers using the Intel Genomics Cluster solution. Though most use cases will involve variant calling against a known genome, more complex analyses can be performed with this system. A single 4-node building block is powerful enough to perform a full transcriptome. As demands grow, additional building blocks can easily be added to a rack to support multiple next-generation sequencers operating simultaneously.

 

Verifying Performance for Whole Genome Analysis

To help customers quantify the potential benefits of the PCSD Genomics Cluster solution, Intel and Seven Bridges Genomics ran a series of performance tests using the Seven Bridges Genomics software platform. Performance for a whole genome pipeline running on the test cluster was compared with the performance of the same software platform running on a 4-node public cloud cluster based on the previous generation Intel Xeon processor E5 v2 family.

 

The subset of the pipeline used for the performance tests includes four distinct computational phases:

 

  • Phase A: Alignment, deduplication, and sorting of the raw data reads
  • Phase B: Local realignment around Indels
  • Phase C: Base quality score recalibration
  • Phase D: Variant calling and variant quality score recalibration.

 

The results of the performance tests were impressive. The Intel Genomic Cluster solution based on the Intel® Xeon processor E5-2695 v3 family completed a whole genome pipeline in just 429 minutes versus 726 minutes for the cloud-based solution powered by the prior-generation Intel® Xeon processor E5 v2 family.

 

Based on these results, researchers and clinicians can potentially complete a whole genome analysis almost five hours sooner using the newer system. They can also use this 4-node system as a building block for constructing large, local clusters. With this strategy, they can easily scale performance to enable high utilization of multiple high-volume, next-generation sequencers.

 

For a more in-depth look at these performance tests, we will soon release a detailed abstract that will provide more detailed information about the workloads and system behavior in each phase of the analysis.

 

What questions do you have?

Security was a major area of focus at HIMSS 2015 in Chicago. From my observations, here are a few of the key takeaways from the many meetings, sessions, exhibits, and discussions in which I participated:

 

Top-of-Mind: Breaches are top-of-mind, especially cybercrime breaches such as those recently reported by Anthem and Premera. No healthcare organization wants to be the next headline, and incur the staggering business impact. Regulatory compliance is still important, but in most cases not currently the top concern.

 

Go Beyond: Regulatory compliance is necessary but not enough to sufficiently mitigate risk of breaches. To have a fighting chance at avoiding most breaches, and minimizing impact of breaches that do occur, healthcare organizations must go way beyond the minimum but sufficient for compliance with regulations. int_brand_883_PtntNrsBdsd_5600_cmyk_lowres.jpg

 

Multiple Breaches: Cybercrime breaches are just one kind of breach. There are several others, for example:


  • There are also breaches from loss or theft of mobile devices which, although often less impactful (because they often involve a subset rather than all patient records), do occur far more frequently than the cybercrime breaches that have hit the news headlines recently.

 

  • Insider breach risks are way underappreciated, and saying they are not sufficiently mitigated would be a major understatement. This kind of breach involves a healthcare worker accidentally exposing sensitive patient information to unauthorized access. This occurs in practice if patient data is emailed in the clear, put unencrypted on a USB stick, posted to an insecure cloud, or sent via an unsecured file transfer app.

 

  • Healthcare workers are increasingly empowered with mobile devices (personal, BYOD and corporate), apps, social media, wearables, Internet of Things, etc. These enable amazing new benefits in improving patient care, and also bring major new risks. Well intentioned healthcare workers, under time and cost pressure, have more and more rope to do wonderful things for improving care, but also inadvertently trip over with accidents that can lead to breaches. Annual “scroll to the bottom and click accept” security awareness training is often ineffective, and certainly insufficient.

 

  • To improve effectiveness of security awareness training, healthcare organizations need to engage healthcare workers on an ongoing basis. Practical strategies I heard discussed at this year’s HIMSS include gamified spear phishing solutions to help organizations simulate spear phishing emails, and healthcare workers recognize and avoid them. Weekly or biweekly emails can be used to help workers understand recent healthcare security events such as breaches in peer organizations (“keeping it real” strategy), how they occurred, why it matters to the healthcare workers, the patients, and the healthcare organization, and how everyone can help.

 

  • Ultimately any organization seeking achieve a reasonable security posture and sufficient breach risk mitigation must first successfully instill a culture of “security is everyone’s job”.

 

What questions do you have? What other security takeaways did you get from HIMSS?

The idea of precision medicine is simple: When it comes to medical treatment, one size does not necessarily fit all, so it's important to consider each individual's inherent variability when determining the most appropriate treatment. This approach makes sense, but until recently it has been very difficult to achieve in practice, primarily due to lack of data and insufficient technology. However, in a recent article in the New England Journal of Medicine, Dr. Francis Collins and Dr. Harold Varmus describe the President Obama’s new Precision Medicine Initiative, saying they believe the time is right for precision medicine. The way has been paved, the authors say, by several factors: Ted Slater.jpg

 

  • The advent of important (and large) biological databases;
  • The rise of powerful methods of generating high-resolution molecular and clinical data from each patient; and
  • The availability of information technology adequate to the task of collecting and analyzing huge amounts of data to gain the insight necessary to formulate effective treatments for each individual's illness.

 

The near-term focus of the Precision Medicine Initiative is cancer, for a variety of good reasons. Cancer is a disease of the genome, and so genomics must play a large role in precision medicine. Cancer genomics will drive precision medicine by characterizing the genetic alterations present in patients' tumor DNA, and researchers have already seen significant success with associating these genomic variations with specific cancers and their treatments. The key to taking full advantage of genomics in precision medicine will be the use of state-of-the-art computing technology and software tools to synthesize, for each patient, genomic sequence data with the huge amount of contextual data (annotation) about genes, diseases, and therapies available, to derive real meaning from the data and produce the best possible outcomes for patients.

 

Big data and its associated techniques and technologies will continue to play an important role in the genomics of cancer and other diseases, as the volume of sequence data continues to rise exponentially along with the relevant annotation. As researchers at pharmaceutical companies, hospitals and contract research organizations make the high information processing demands of precision medicine more and more a part of their workflows, including next generation sequencing workflows, the need for high performance computing scalability will continue to grow. The ubiquity of genomics big data will also mean that very powerful computing technology will have to be made usable by life sciences researchers, who traditionally haven't been responsible for directly using it.

 

Fortunately, researchers requiring fast analytics will benefit from a number of advances in information technology happening at just the right time. The open-source Apache Spark™ project gives researchers an extremely powerful analytics framework right out of the box. Spark builds on Hadoop® to deliver faster time to value to virtually anyone with some basic knowledge of databases and some scripting skills. ADAM, another open-source project, from UC Berkeley's AMPLab, provides a set of data formats, APIs and a genomics processing engine that help researchers take special advantage of Spark for increased throughput. For researchers wanting to take advantage of the representational and analytical power of graphs in a scalable environment, one of Spark's key libraries is GraphX. Graphs make it easy to associate individual gene variants with gene annotation, pathways, diseases, drugs and almost any other information imaginable.

 

At the same time, Cray has combined high performance analytics and supercomputing technologies into the Intel-based Cray® Urika-XA™ extreme analytics platform, an open, flexible and cost-effective platform for running Spark. The Urika-XA system comes preintegrated with Cloudera Hadoop and Apache Spark and optimized for the architecture to save time and management burden. The platform uses fast interconnects and an innovative memory-storage hierarchy to provide a compact and powerful solution for the compute-heavy, memory-centric analytics perfect for Hadoop and Spark.

 

Collins and Varmus envision more than 1 million Americans volunteering to participate in the Precision Medicine Initiative. That's an enormous amount of data to be collected, synthesized and analyzed into the deep insights and knowledge required to dramatically improve patient outcomes. But the clock is ticking, and it's good to know that technologies like Apache Spark and Cray's Urika-XA system are there to help.

 

What questions do you have?

 

Ted Slater is a life sciences solutions architect at Cray Inc.

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