It’s seems like just yesterday that we were leaving Chicago and basking in the innovation on display at HIMSS 15. Actually, since the last show was in April and now the biggest event in healthcare technology is back in its usual calendar slot, we’re ready for the second HIMSS in less than 12 months.

 

This year, the healthcare technology community is headed to Las Vegas February 29 to March 3, 2016, to see what innovation will be on the healthcare horizon in 2016 and beyond.  You should expect to see more conversations around how the patient, and their user generated data, plays into healthcare going forward. HIMMS_1.jpg

 

At Intel, we’re approaching HIMSS 16 with a critical eye on three areas that we feel are focal points for CMIOs: precision medicine, health IT and medical devices, and consumer health. All are patient-focused.

 

To learn more about these pillars, you’re invited to the Intel booth (#3032) to view the latest technology platforms that focus on the rise of patient engagement and consumer generated health data. We encourage you to stop by and take a guided tour, where you’ll see these demonstrations:

 

  • Precision Medicine: From genome sequencing to targeted treatment plan all in one day
  • Health IT and Medical Devices: Securely connecting patients, clinicians and their data for proactive healthcare wherever you are
  • Consumer Health: Engaging connections among people, their data and care community to empower health ownership

 

Outside of the Intel booth, you will find our technology in a number of HIMSS Kiosks that showcase real solutions available today:

 

  • Population Health Zone Kiosk #14099: IOT Big Cloud Analytics will share how analytics are helping to proactively improve healthcare
  • Connected Health Zone Kiosk #15208: Fujitsu will showcase a communication tool integrated EMR used at the National Cancer Center, personal health record for pregnant women and personal health records for dental solutions
  • Intel Security Kiosk and Cyber Security Challenge #9908: Come take the Security Breach Challenge and learn how to combat cybercrime through efficient breach detection and response

 

Finally, be sure to follow @IntelHealth on Twitter to keep up-to-date on all the happenings going on at the event. We’ll be live tweeting from the show floor and sharing pictures of new health IT products/services that we discover. We’ll also be giving away a Basis Peak watch every day during HIMSS through a Twitter contest so be on the lookout for how you can win.

 

HIMSS is always a great event and we are looking forward to seeing you in Las Vegas.

 

What are you most looking forward to seeing at HIMSS16? Tweet us @IntelHealth.

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I was delighted to be invited to speak at Microsoft’s Empowering Health event in Brussels, Belgium recently, which brought together some 200 thought-leaders from across the world to discuss health IT issues in a ‘Mobile First and Cloud First World’.

 

I was looking forward to hearing about how some of the more progressive countries in Europe were utilising technology to deliver more personal, productive and predictive health to its citizens so it was pleasing to hear examples from the Netherlands around patient portals and from Sweden where virtual care rooms are helping to deliver a more efficient healthcare system through patient self-diagnosis. From these very real examples of today to discussions around the future of machine learning and robotics, the narratives were underpinned by the absolute need for clinical staff to have input into the technology solution they would be asked to use as early as possible.

 

Data: One Size Does Not Fit All

Some great statistics from Tom Lawry, Director of Worldwide Health Analytics, Microsoft, generated a real buzz in the room. Tom started his presentation by stating that ‘we spend a lot of money ONCE people are sick, while most money is spent on small numbers of people who are VERY sick.’ Clearly there are a lot of areas where technology is helping to move the needle from cure to prevention while all-in-one-day genome sequencing to personalised medicine is something we are working towards here at Intel as we look ahead to 2020. I was interested to hear examples from across the world on how healthcare providers are dealing with increasingly large amounts of data. Within the European Union there are very different takes on what data is classed as secure and what is not. For providers and vendors, this requires a keen eye on the latest legislation, but it’s clear that it’s a case of one size does not necessarily fit all.

 

Digital Education of Nurses

The breakout nursing session brought together a dedicated group of nurses with a real interest in how technology can, and will, help make nursing even better. We kicked off by discussing what level of digital education nurses have today, and what they need to equip them for the future. The consensus was that more needs to be done in helping nurses be prepared for the technology they’ll be asked to use, in essence making technology a core part of the nursing curriculum from day one.

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The move towards distributed care generated some fantastic thoughts on how technology can help nurses working in the community - read my recent blog for more thoughts on that. We all agreed that access to healthcare is changing, it has to if we are to meet the demands of an ageing population. For example, millennials don’t necessarily think that they need to see a medical practitioner in a hospital setting or a doctor’s surgery, they are happy to call a clinician on the phone or sit in a kiosk for a virtual consultation, the priority being quick and easy access.

 

Nurses Actively Championing Technology

I was particularly impressed by a new app showcased by Odense University Hospital called Talk2Care – in short, it enables patients in ICU to ‘talk’ to nurses using an icon-based dashboard on a mobile device. This new way for patients to communicate, who would in some cases only be able to nod or shake their head, has been invaluable not only for nurses but the patient’s family too. What really pleased me was that nurses were actively championing this technology, encouraging patients to utilise it to help nurses deliver a better care experience.

 

We closed with thoughts on how taking care into the community was being revolutionized by technology. We’ve got some great examples of the role Intel is playing in the advance towards more distributed care, from the use of Intel IoT Gateways to help the elderly live more independent lives at home through to the KU Wellness car which empowers nurses to take advanced care into the community using mobile devices.

 

Virtual Reality Nursing

After a short break we returned to the main auditorium where I was pleased to be on stage with nurses from across the world. The future of the workforce was discussed in some detail, particularly around how the nursing and the wider healthcare community will manage the anticipated future global shortage of nurses. Technology will go some way to alleviating this shortfall through improved workflows but I like to think in a more visionary way, perhaps we will see the use of avatars, virtual reality and (thinking of discussions earlier in the day) robots. What’s clear is that nursing is changing in response to the move to distributed care, we need to skill not only nurses but other caregivers too, i.e. families, to make better use of the technology that is available today and tomorrow.

 

In December, Centers for Medicare & Medicaid Services (CMS) announced final rules of Meaningful Use 3 (MU3)—the third and final iteration of the Meaningful Use Program. The principal goal of this incentive program is to ensure that electronic health records are being used by providers in a way that improves quality of care (e.g., used for e-prescribing, or for submission of clinical quality measures). MU requires providers to meet these criteria in order to receive incentive payments and avoid downward reimbursement adjustments.

 

As part of MU3, eligible providers will be required to integrate Patient Generated Health Data (PGHD) with clinical data in the EHR for at least 5 percent of the patient population. PGHD includes any data that is generated outside of the clinical setting. Examples include data captured by a device such as a smart phone, or self-reported data (e.g., diet, functional status, emotion well-being) that is manually recorded by the patient. The patient both captures and transfers that data to the provider.

 

Inclusion of PGHD in this third and final phase of Meaningful Use is exciting for several reasons  

First, this new rule has potential to incentivize providers to invest in the technology and infrastructure (e.g., data storage and security) that will support the integration and use of this data, which to date has not been systematically incorporated into routine patient care.

 

Second, this new rule coincides with the rapidly growing wearable device market and consumer use of these devices that allows patients to capture their own health data outside of the clinic or hospital setting. Integrating these data points with clinical data and allowing providers to use these data at the point of care will contribute to patient engagement, patient activation, and self-management.

 

Third, at the policy level, this is likely to drive interoperability and data security standards, which could have broader and positive implications for other types of healthcare data and analytics.

 

How should providers prepare?

This new ruling will go into effect in 2018, thus giving providers time to make changes to current EMRs and technology that will support the use of the transfer, use, and storage of this data.

 

At Intel, we are working to advance these goals through data security efforts, big data analytics, data storage capabilities, and wearable devices that promote and support PGHD.

 

One such initiative within Intel Health & Life Sciences involves Big Cloud Analytics and its COVALENCE Health Analytics Platform. The COVALENCE Health Analytics Platform is powered by Intel Xeon processor-based servers in the cloud, which ensures a secure, reliable, and scalable infrastructure. Big Cloud Analytics utilizes the Basis Peak watch, which provides 24x7 real-time heart rate monitoring, and supplies metrics for sleep patterns, steps taken, skin temperature, and perspiration. It collects readings on 50 biometric data points every 60 seconds and syncs the data security with the Basis Cloud.  This allows insurance providers, healthcare institutions, and employers to securely use wearable device data to engage patients with event-triggered personalized messaging.

 

Biometric sensor data gathered from the device is also transmitted to the cloud or on premise data storage and aggregated in the COVALENCE Health Analytics Platform. This platform transforms data into business intelligence and predictive analytics. It then generates wellness scores, bio-identity scores, and many others. Insights based on analysis of the data points and trends provide an early indication of potential health issues or lack of progress toward health goals.

 

PGHD as part of routine care: opportunities and challenges

While PGHD will substantially increase the number of data points that can inform healthcare and lead to new insights, we recognize that operationalizing the transmission and use of PGHD will not happen instantly, nor effortlessly. Many questions remain as to how this data will be most effectively used by providers and patients. For example, what is relevant data?  How should providers communicate this to patients so that the appropriate data can be collected and transferred? How much data will providers want and need to obtain in order to make this data useful for patient care? How often will providers want to see this data? How might this influx of data affect staff or clinic workflows? From a user experience perspective, how will this data be best displayed so that providers and patients alike can act upon it? Perhaps further research, particularly ethnographic research that takes into account both the clinician and patient perspective, is needed if we are to use this data in way that translates to better patient outcomes.

One of the most promising areas of innovation and transformation in healthcare today is the move to distributed care, achieved through the creation of patient-centered networks of intelligent, connected devices that span across the home, workplace, community and the mobile spaces in between. Data capture and analysis, and communication between the patient and their care team can all be enhanced and harnessed to deliver more effective healthcare to more people at lower cost.

 

Connected Care, Everywhere

In the home, this will be driven by new types of consumer medical devices and smart-home connectivity and features. In the workplace and the community, new mobile devices and services including kiosks will be available. And for persistent real-time data and connectivity, new purpose-built and general purpose devices will fill in critical gaps.

 

Community Care Impact

In the home, sensors are transforming the way we care for the elderly, helping them stay more independent and spend longer at home, thus improving general well-being and reducing costs to the provider. Mimocare’s sensor solution is a great example of just how the Internet of Things can help us move the focus towards prevention rather than cure.

 

For community nurses this kind of distributed care is a win-win, they’re alerted (remotely) to patients showing abnormal signs earlier which enables a more speedy intervention and appropriate care is delivered more quickly, while also reducing the need for unnecessary monitoring visits too.

 

Patient-Centered Connectivity

I’d highly recommend reading a recent blog on the use of the Intel® RealSense™ 3D Camera by GPC too, which can help clinicians in a hospital setting make better-informed decisions in the area of wound care management. It’s an exciting development as wound care management accounts for a high-spend by most care providers, for example,  in the UK the NHS spends some £3 billion per year in this area.

 

RealSense™ is available across a range of mobile devices today so I see a future where patients are able to play a greater role in their wound care management in the home setting by recording the healing progress of wounds using the 3D camera and sharing the results with clinicians. This is undoubtedly more convenient for patients and more efficient for clinicians and providers.

 

Balancing the Demands of Modern Healthcare

These patient-centered networks of intelligent, connected devices generate significant volumes of data which can be analyzed by healthcare providers to help balance the demands of an ageing population with increased pressure on costs.  Patient preference to stay - and be clinically managed - at home is driving this shift to distributed care. The tools are available today, so let’s embrace a more connected vision of healthcare where we deliver even better care to patients.

 

 

Joan is speaking on the 'Technology empowering nurses with mobility, collaboration and communication' panel at Microsoft's EU Innovation Empowering Health event in Brussels, Belgium on 01/26/16

Technology can solve complex healthcare problems, whether that be analysing large volumes of genomic data or allowing a specialist to see a 3D image of a beating heart, but sometimes we often overlook the simple, day-to-day tasks where technology is having meaningful impact for patients and healthcare professionals today.

 

Providing Efficiency in Clinician’s Workflow

I’m seeing a lot of interest and excitement here in China around the Internet of Things in healthcare. Sensors are increasingly being used to not only provide more efficiency in a clinician’s workflow in a hospital setting but also to help those patients who require care in the home to live more independent lives.

 

A great example in development that I’d like to share is the Intel Edison-based uSleepCare intelligent bed which is able to record a patient’s vital signs such as rate and depth of breathing, heart-rate and HRV without the need for nurse intervention. Movement sensors also help to identify where there may be cause for concern over pressure ulcers or patients may fall out of their bed for example, which may prolong a hospital stay.

 

Early Identification of Abnormalities

The sensors not only collect data but also use WiFi to transmit that data seamlessly to a cloud platform for analysis which can then be used in a variety of meaningful ways. The most obvious and pressing data use demand is for early identification of abnormalities which can alert nursing staff to the need for human intervention, thus reducing the requirements to have nurses ‘doing the rounds’ which is resource-intensive and costly for providers.

 

Additionally the archive of data helps clinicians tackle chronic diseases at the patient level, spotting trends where patients may having a worsening or improving condition. This is particularly valuable as devices such as the UsleepCare intelligent bed become available in a homecare setting. Imagine a community nurse being able to prioritise visits to those patients who are showing abnormal signs as recorded by IoT sensors via alerts, all on a mobile device in real-time. This is truly mobile healthcare, delivering the right care where it is needed and when it is needed, with the right information at their fingertips.

 

Data Collection Bring Efficiencies

And as this sensor technology becomes more prevalent in both the hospital and homecare setting, the data becomes increasingly useful at a population level too. It will assist providers in spotting trends which will in turn help them to become more efficient and allocate resources where appropriate.

 

All of which ultimately benefits the patient, particularly those with chronic conditions. They will perhaps spend less time in hospital with an improved level of care and be able to spend more time at home, with the confidence that their condition is being monitored by a healthcare professional 24/7.

 

The Internet of Things is having a rapidly transformative effect on healthcare. Investment by providers in sensor technology such as the Intel Edison-based USleepCare intelligent bed is helping to drive efficiency-savings while also having a meaningful impact on patient care. In China we’re already pushing forward with implementation in this area and I look forward to sharing the results in the future.

 

Read Part I: Transforming Healthcare with Patient-Generated Data

Read Part II: How Wearables are Impacting Healthcare

Read Part III: Challenges of User-Generated Data

Read Part IV: Wearables for Tracking Employee Movement

 

This blog series has been about how wearables have become more than a passing trend and are truly changing the way people and organizations think about managing health. I hear from many companies and customers who want to understand how the wearables market is impacting patient care as well as some of the changes taking place with providers, insurers, and employers. So far, I've shared some of their questions and my responses. The final question in this series is:

 

What kinds of organizational and cultural changes are driven by patient-generated data?

 

There is definitely a cultural shift, and you get different adoption and excitement on a clinician-by-clinician basis. It is still early days.Some clinicians are championing patient-generated data while others aren’t buying into its significance.

Where I hope Intel can play a role both near term and going forward is with predictive analytics and using streaming wearable data to help inform predictive models and make them more accurate. As I mentioned in earlier posts, we want to make it easier for health systems and clinicians to adopt a data-driven approach, enabling better allocation of limited resources and, ultimately, improving patient outcomes.

 

I am most excited about the ability to monitor patients and members continuously rather than periodically, moving from episodic to real time. That’s the game changer. And it’s enabled by technologies with the combination of very low power consumption, very small form factor or package, and the ability to send sensor data (either directly or via the ubiquitous smartphone) to the cloud or to backend information systems.

 

As wearables become more pervasive it will be exciting to see the industry move beyond consumer-based wearable devices that were developed for fitness purposes to devices with more sophisticated sensing capabilities targeted for healthcare use cases. I feel these devices will have a significant impact on reducing costs and improving outcomes by monitoring conditions and patients 24x7.

 

What questions about wearables do you have?

As much of the developed world faces the burden of escalating healthcare costs, ageing populations, and increased incidence of chronic diseases, countries and localities are experimenting with innovative approaches to address these challenges.

 

In a recent visit to Greater Manchester, England, I learned of an innovative initiative recently launched that aims to use technology to create a civic partnership between NHS and social care providers. The principal goals of the initiative are to 1) improve health outcomes, 2) reduce healthcare disparities, and 3) reduce income inequality. While many nations and municipalities are working to achieve these goals, Greater Manchester’s approach to achieving these goals is multi-pronged and systematic, and will use technology in a way that will integrate social services into healthcare delivery.

 

Using Technology for Data Storage, Analysis, and Interoperability

Greater Manchester’s plan calls for the creation of “Connected Health Cities” (CHCs), which will be powered by health innovation centers. These centers will assemble the data from multiple sources. What is especially novel about these CHCs is that the collection, management, and analysis of both health and social care data will happen at a scale that until now has been impossible. Shared protocols for data analysis across the CHCs will allow for timelier and more powerful research studies, and ultimately better informed decision-making.

 

Interoperability and integration of myriad data sources will be a vital component for realizing these goals. Clinical, community, and patient-generated data will be used to inform decision-making not just among clinical providers, but also among public health policy makers, planners, social care providers, and researchers. Finally, technology will also support continuous evaluation of the program, and use of actionable measures to drive decision-making.

 

Decision Making at the Local Level

Another unique feature of this plan is that the UK will provide the locality with 6 billion pounds for Greater Manchester to use at its own discretion. Granting control of the budget to local municipalities will allow for decision making to happen at the lowest possible level.

 

The Greater Manchester Board will set strategies and priorities, but local boards will devise plans that will be tailored depending on the needs of the local environment. The budget will be used not just for healthcare, but also for social programs and public health activities. The technology and data will help to bridge health and social programs at this local level.

 

Tackling Priority Care Pathways

Greater Manchester will focus initially on optimizing four “care pathways.” One pathway will use support tools for self-care to reduce hospital admissions for patients with chronic conditions. Another will support schizophrenia patients by linking self-reported symptoms to responses from community psychiatric nurse visits. Studying the effects of the program on specific pathways will allow for evaluation and iteration to help ensure the program’s success.

 

Public and Patient Engagement

Involvement from the public and from patients is a central pillar of this devolution plan. A panel of 10 patient and public representatives will have a say in how the data is used. The program leaders believe such involvement will ensure sustainability and transparency of these CHCs, and ensure that citizens’ needs are met in this civic partnership.

 

Insights for other Countries and Cities

I am eager to observe the implementation and early results that come from this Greater Manchester initiative, as it is a test bed for the devolution of health and social care. The potential for this initiative to accelerate and scale innovation to reduce disparities and improve population health is exciting. Data will be used from multiple streams in ways that haven’t before been possible, and will be used in a way that is tailored to the local environment. With a growing body of research that highlights the impact that social determinants (e.g., housing, social services and support, access to care) have on healthcare, using technology and data to tackle these issues could help other nations and cities in their efforts to improve population health.

 

Contact Jennifer Esposito on LinkedIn

 

Dr. Robert Green is director of the Genomes2People Research Program, associate director for Research for Partners Personalized Medicine and associate professor of Medicine at Brigham and Women’s Hospital, a Harvard Medical School teaching hospital in Boston, Massachusetts. We recently sat down with him to discuss his research on personal genomics and where that research is headed in the future. DrGreen.jpg

 

Intel: How has gene sequencing evolved over the last decade?


Green: Genetic sequencing is tremendously exciting and important for the future of medicine. We have all this technology that allows us to sequence, align, and call these variants so much better than we could before. The real question is, how do you integrate that into the practice of medicine? Our research at Brigham and Women’s Hospital is zeroed in on finding out how we can implement genomic information, particularly sequencing, into the practice of medicine for adults or even for newborns.

 

Intel: Are patients interested in consumer genetic testing? If so, why?


Green: Patients want to know if they are at increased risk for particular diseases. They want to know if there are drugs they should or shouldn’t take. Some of them want to know if they are carrying recessive carrier traits that would put them at risk for having a child with a recessive disease if their partner is also carrying a copy of a mutation. A lot of people are really curious about the diseases they already have.

 

Our research helps us understand why people want services like consumer genetic testing. In part, it’s perhaps to predict future illness, but it’s also to explain what they already have or what’s running in their family.

 

Intel: What kind of impact can genomic sequencing have on patients?


Green: Genome sequencing isn’t going to be relevant to everyone’s disease. It isn’t going to be relevant to everyone’s medication. But it is going to be relevant to people with rare diseases and those on some medications. It’s going to be relevant to a lot of people who have cancer. And it’s highly relevant to people who are planning their family and want to do preconception testing to avoid recessive conditions.

 

When it comes to individuals who are dealing with sepsis or bad infection, we’re going to not only sequence those patients, but also sequence the microbiomes of the bacteria that are infecting them.

 

One of the directions for sequencing is to have a file or a database of genomic information a patient can call upon to use when they face a situation where they need a new medication, are going to have a family, or have a mysterious illness. That information will be there. It can be brought up in an electronic health record at the point of care in a decision support manner.

 

Intel: What’s the biggest hurdle right now?


Green: One of the great challenges for the practice of medicine is to keep up with, educate ourselves about, and use research effectively in our practices.

With initiatives to accelerate the implementation of genomics, like the Intel All in One Day goal, it’s going to be important that clinicians and those who are in training—fellows, residents, medical students—become much more familiar with genomics than they are today.

 

Intel: What’s your vision for the future of genomic research application?


Green: I think five years from now, about 20 percent of the population is going to walk into their doctor’s office with their own genome, and doctors are going to have to decide how they want to use this information. I can envision that about 10 years from now everyone will use their genome as a daily part of their medical care.

The 3rd and final webinar in Frost & Sullivan’s series on Big Data in Healthcare took place recently and is now available to view on-demand. The webinar is a must-watch for healthcare leaders and features some very practical advice on how to get the most value from the data your organizations holds.

 

Greg Caressi, Sr. VP of Transformational Health at Frost & Sullivan, opened with an overview of how providers are leveraging big data platforms to drive health, concluding with ‘the real bottleneck is in turning data into knowledge’.

 

David Delaney, MD, Chief Medical Officer at SAP Healthcare, took the conversation forward by sharing his thoughts on how HANA® Healthcare In-Memory simplifies and accelerates data analysis for healthcare providers. Intel and SAP have a long-standing relationship and have worked together on SAP HANA® since 2005.

 

Finally, Kevin Fitzpatrick, CEO of ASCO CancerLinQ, gave a fantastic presentation on shaping the future of cancer through rapid learning. A brilliant insight into really important work for the cancer community.

 

Listen to this webinar now on-demand and don’t forget that if you missed the first two webinars you can also view them today using the links below:

 

  • Watch Webinar 3: Big Data in Clinical Medicine: Bringing the Benefits of Genome-Aware Medicine to Cancer Patients
  • Watch Webinar 2: Predictive Healthcare Analytics in a Big Data World: Use Cases from the Field
  • Watch Webinar 1: Future of Healthcare is Today: Leveraging Big Data

In the wild, no prey is completely safe from predators. However, it is clear to prey which members of the herd are weak or vulnerable to predators. They certainly also know which one is being pursued, or has been caught by a predator.

 

In healthcare, no organization is immune from breaches, regardless of how advanced their security is. There is always residual risk, for example from spear phishing. Healthcare organizations, even those that do risk assessments well, and address any deficiencies identified, don’t know how their security stands relative to other healthcare organizations. In a sense they don’t know whether they are “low hanging fruit” for predators such as cybercriminals. Exacerbating this, many healthcare organizations lack the security intrusion detection capabilities to detect when they are being actively pursued by hackers. Many cybercrime breaches go on for months or even years before they are detected and stopped, vastly increasing the number of patient records compromised and the business impact of the breach.

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Intel Health and Life Sciences, together with Intel Security, just released an online Healthcare Security Survey that invites participants from healthcare organizations to securely and confidentially answer a few questions about their breach security safeguards and posture. Based on the input provided their breach security is scored, and summary recommendations are made on possible next steps improve. Participants are then offered the opportunity to engage in a subsequent 1-2 hour breach security assessment that confidentially analyzes their healthcare organizations breach security posture in more detail, identifying any potential gaps and improvements. Post assessment participants receive a report of their results together with how their healthcare organizations breach security compares with the rest of the healthcare industry. Several of the breach security controls analyzed improve detection of breaches, enabling the organization to detect hacking, intrusions or breaches.

 

Ponemon Institute 2015 Cost of a Data Breach Research estimates the total average cost of a data breach at $6.53M, or $398 per patient record. In fact, we have seen the business impact of recent cybercrime breaches going higher than $100M. With this kind of impact, and the alarming frequency of breaches, the need to rapidly address this issue has never been more urgent.

 

If you are working for a healthcare organization, join us now in taking the online Healthcare Security Survey challenge, and enrolling in our Healthcare Breach Security Assessment pilot program to confidentially see where your healthcare organization stands in terms of breach security posture relative to the healthcare industry, and any potential gaps and opportunities to improve with a multi-year, incremental, layered approach that fits within your budget and resource constraints.

 

What questions do you have?

The 2nd webinar in Frost & Sullivan’s series on Big Data in Healthcare took place recently and featured a fantastic insight from Vijay Venkatesan of Sutter Health and Shawn Dolley of Cloudera on the subject of Predictive Analytics in a Big Data world. The webinar is now available on-demand via the Frost & Sullivan website.

 

This on-demand webinar features some great learnings from Sutter Health including:

  • Objective and role for Data and Enterprise Management
  • Dealing with Volume and Variety of Data
  • Best Approach to Transformation
  • Critical Success Factors
  • Closing Q&A

 

Listen to this webinar now and register for the 3rd and final webinar which features Dr. David Delaney of SAP sharing insights into how SAP’s HANA in-memory database along with Intel tailored hardware are being leveraged by the American Society of Clinical Oncology, and Dr. Kevin Fitzpatrick, CEO of CancerLinQ who will discuss the fantastic work around the aggregation and analysis of a huge web of real-world cancer care data.

 

  • Register Now: Big Data in Clinical Medicine: Bringing the Benefits of Genome-Aware Medicine to Cancer Patients
  • Watch Webinar 2: Predictive Healthcare Analytics in a Big Data World: Use Cases from the Field
  • Watch Webinar 1: Future of Healthcare is Today: Leveraging Big Data

As we arrive at the $1,000 genome, we find the fundamental challenges with next generation sequencing have shifted. The issue is no longer about shrinking the cost of sequencing but the explosive growth of big data: the downstream analytics with rapidly evolving parameters, data sources and formats; the storage, movement and management of massive datasets and workloads; and perhaps most paradoxical of all, the challenge of articulating the results and translating the latest findings directly into improving patient outcomes.

This topic, and more, will be front and center at the Personalized Medicine World Conference (PMWC) coming up in January 2016. As we transition from a “one-size-fits-all” approach and a focus on treatment rather than prevention, it’s a good time for the industry to gather to make personalized medicine a reality.

 

Combining patient, clinical, diagnostic and ‘omic data will give us more diversified data, allowing us to view health data differently with the potential for new personalized treatments. To analyze such diverse and large data sets will require new technical approaches. We will need to collect and store patient data in central and secure repositories when we can. We will also need solutions that can accommodate large amounts of genomic data which isn’t efficient to move from the clinics that generate and store it.

 

The challenge of analyzing data is also the reason that Intel, along with Oregon Health & Sciences University, launched the Collaborative Cancer Cloud, a precision medicine analytics platform that allows institutions to securely share patient genomic, imaging and clinical data for potentially lifesaving discoveries. It will enable large amounts of data from sites all around the world to be analyzed in a distributed way, while preserving the privacy and security of that patient data at each site.

 

The end goal is to empower researchers and doctors to help patients receive a diagnosis based on their genome and potentially arm clinicians with the data needed for a targeted treatment plan. By 2020, we envision this happening in 24 hours -- All in One Day. The focus is to help cancer centers worldwide—and eventually centers for other diseases—securely share their private clinical and research data with one another to generate larger datasets to benefit research and inform the specific treatment of their individual patients.

 

Genome Centers

I’m honored to be part of the PMWC 2016 agenda. On the third day of the event (January 26), I will be addressing how Genome Centers, including core facilities, are handling these challenges along with ethical and privacy issues. Several center directors will be on hand to discuss how they work with clinical data and how they share data with their customers.

 

Learn more about the Personalized Medicine World Conference on January 24-27, I hope to see you there as treating patients as individuals becomes the norm in healthcare delivery.

 

What questions do you have?

 

Interoperability should mean less cost for healthcare organizations and better data analysis for patients. Here are a few additional thoughts.

How does a centre of research excellence keep pace with ever increasing data volumes and demand for insight? It’s a recurring question we hear the world over so it’s great to be able to showcase an example of how one organisation is meeting these challenges here in Spain. Spain’s National Center of Genomic Analysis (CNAG) opened in 2009, supporting 120 researchers and conducting c. 300 projects per year. It has a clear mission: to deliver research and results that help make citizens’ lives better.

 

Finding the 0.1%

As one of the largest capacity sequencing facilities in Europe, CNAG sequences around 800 Gigabases per day. We know that for reliable analysis we need to sequence at 30-fold coverage, so CNAG are sequencing the equivalent of eight full human genomes every 24 hours, but it’s the variations that really hold the key to unlocking precision medicine.

And given that genomes are 99.9% identical the challenge becomes clear: find the 0.1%, break each genome down into short strings, sequence them and then rebuild them. Ivo Gut, director of CNAG summarizes this nicely in the Sequencing and Supercomputers case study when he says: “It’s like doing a jigsaw puzzle with 1 billion pieces.”

 

Combining Data Sources to Gain New Insights

If you are a regular reader of our Health and Life Sciences blogs you’ll know that the word collaboration appears frequently. Across the healthcare ecosystem, collaboration is driving change, it’s moved from something we all aspire to, to something we must embrace to deliver better care, reduced costs and improved workflows. So, it’s great to see CNAG combining their own data with other sources to gain new insights, e.g.  CNAG collaborated with other institutions as part of the International Cancer Genome Consortium to better understand chronic lymphocytic leukaemia.

 

Big Data leads to Big Information

CNAG’s aim is to be able to put the findings of their research into use in a clinical environment; this requires a powerful computing platform which allows them to locate and accurately predict the base variations in every genome of the 3.2m bases that are potentially responsible for diseases. Without the technical capabilities to deliver sequence analysis on an industrial scale it makes it difficult to do much more than one-off research projects. I recognise that these pockets of research are valuable but to move us closer to delivering personalized medicine we must begin to work more collaboratively.

 

CNAG’s new sequencing and analytics environment is helping the organisation to meet the growing volume and variety of data generated by collaborative working with Ivo Gut saying: “We’re certainly handling big data now – and it’s growing all the time – but what we’re really after is big information.”

 

Intel and Atos provide scale and flexibility

Being able to design the computational infrastructure from the ground up gives organisations such as CNAG the opportunity to utilise best-in-class technology. The organisations I talk to regularly all have the same priorities around flexibility and scale. With that in mind Atos Big Data and Security service line developed a tailor-made compute cluster, powered by the Intel® Xeon® processor E5 family, to conduct in-depth high-performance data analytics (HPDA) on genome sequencing.

 

And looking to the future, CNAG will provide more granular insights to help hospitals treat different diseases, whether that be for identification of the correct medication or for rapid initial diagnosis. As CNAG scales its computational infrastructure it will also increase its scope of research, ensuring that Spain stays at the forefront of global genomics research.

 

Contact Carlos Piqueras on LinkedIn

 

Read Part I of this blog series on wearables in healthcare

Read Part II of this blog series on wearables in healthcare

Read Part III of this blog series on wearables in healthcare

 

This blog series is about how wearables have become more than a passing trend and are truly changing the way people and organizations think about managing health. I hear from many companies and customers who want to understand how the wearables market is impacting patient care as well as some of the changes taking place with providers, insurers, and employers. In this series, I’m sharing some of their questions and my responses. This blog’s question is:


Are there applications for tracking employee movement or flow apart from wellness applications?

 

Yes, this is a fairly widespread and growing practice in healthcare – monitoring the location and movement of employees, patients, and equipment. So you know where the patient is, where the care team is, where the closest infusion pump is. The “wearable” in this case would be the badge with integrated active or passive RFID. This is typically referred to as RTLS or real-time location system.

I haven’t come across many healthcare organizations that monitor their clinicians; patient and medical device monitoring is more widespread. There are some privacy concerns with employees being monitored, but there are benefits such as easily locating the care team or adjusting workflow throughout the hospital. I suspect a growing number of organizations will deem examples like these to have high enough ROI to allow for the minor privacy intrusion.

 

What do you think? Have you seen a trend in monitoring medical staff?

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