Archive for the ‘Healthcare’ Category

Why Healthcare IT Should Abandon Data Storage Islands and Take the Plunge into Data Lakes

One of the most significant technology-related challenges in the modern era is managing data growth. As healthcare organizations leverage new data-generating technology, and as medical record retention requirements evolve, the exponential rise in data (already growing at 48 percent each year according to the Dell EMC Digital Universe Study) could span decades.

Let’s start by first examining the factors contributing to the healthcare data deluge:

  • Longer legal retention times for medical records – in some cases up to the lifetime of the patient.
  • Digitization of healthcare and new digitized diagnostics workflows such as digital pathology, clinical next-generation sequencing, digital breast tomosynthesis, surgical documentation and sleep study videos.
  • With more digital images to store and manage, there is also an increased need for bigger picture archive and communication system (PACS) or vendor-neutral archive (VNA) deployments.
  • Finally, more people are having these digitized medical tests, (especially given the large aging population) resulting in a higher number of yearly studies with increased data sizes.

Healthcare organizations also face frequent and complex storage migrations, rising operational costs, storage inefficiencies, limited scalability, increasing management complexity and storage tiering issues caused by storage silo sprawl.

Another challenge is the growing demand to understand and utilize unstructured clinical data. To mine this data, a storage infrastructure is necessary that supports the in-place analytics required for better patient insights and the evolution of healthcare that enables precision medicine.

Isolated Islands Aren’t Always Idyllic When It Comes to Data

The way that healthcare IT has approached data storage infrastructure historically hasn’t been ideal to begin with, and it certainly doesn’t set up healthcare organizations for success in the future.

Traditionally, when adding new digital diagnostic tools, healthcare organizations provided a dedicated storage infrastructure for each application or diagnostic discipline. For example, to deal with the growing storage requirements of digitized X-rays, an organization will create a new storage system solely for the radiology department. As a result, isolated storage siloes, or data islands, must be individually managed, making processes and infrastructure complicated and expensive to operate and scale.

Isolated siloes further undermine IT goals by increasing the cost of data management and compounding the complexity of performing analytics, which may require multiple copies of large amounts of data copied into another dedicated storage infrastructure that can’t be shared with other workflows. Even the process of creating these silos is involved and expensive because tech refreshes require migrating medical data to new storage. Each migration, typically performed every three to five years, is labor-intensive and complicated. Frequent migrations not only strain resources, but take IT staff away from projects aimed at modernizing the organization, improving patient care and increasing revenue.

Further, silos make it difficult for healthcare providers to search data and analyze information, preventing them from gaining the insights they need for better patient care. Healthcare providers are also looking to tap potentially important medical data from Internet-connected medical devices or personal technologies such as wireless activity trackers. If healthcare organizations are to remain successful in a highly regulated and increasingly competitive, consolidated and patient-centered market, they need a simplified, scalable data management strategy.

Simplify and Consolidate Healthcare Data Management with Data Lakes

The key to modern healthcare data management is to employ a strategy that simplifies storage infrastructure and storage management and supports multiple current and future workflows simultaneously. A Dell EMC healthcare data lake, for example, leverages scale-out storage to house data for clinical and non-clinical workloads across departmental boundaries. Such healthcare data lakes reduce the number of storage silos a hospital uses and eliminate the need for data migrations. This type of storage scales on the fly without downtime, addressing IT scalability and performance issues and providing native file and next-generation access methods.

Healthcare data lake storage can also:

  • Eliminate storage inefficiencies and reduce costs by automatically moving data that can be archived to denser, more cost-effective storage tiers.
  • Allow healthcare IT to expand into private, hybrid or public clouds, enabling IT to leverage cloud economies by creating storage pools for object storage.
  • Offer long-term data retention without the security risks and giving up data sovereignty of the public cloud; the same cloud expansion can be utilized for next-generation use cases such as healthcare IoT.
  • Enable precision medicine and better patient insights by fostering advanced analytics across all unstructured data, such as digitized pathology, radiology, cardiology and genomics data.
  • Reduce data management costs and complexities through automation, and scale capacity and performance on demand without downtime.
  • Eliminate storage migration projects.

 

The greatest technical challenge facing today’s healthcare organizations is the ability to effectively leverage and manage data. However, by employing a healthcare data management strategy that replaces siloed storage with a Dell EMC healthcare data lake, healthcare organizations will be better prepared to meet the requirements of today’s and tomorrow’s next-generation infrastructure and usher in advanced analytics and new storage access methods.

 

Get your fill of news, resources and videos on the Dell EMC Emerging Technologies Healthcare Resource Page

 

 

Big Data Analysis for the Greater Good: Dell EMC & the 100,000 Genome Project

Wolfgang Mertz

CTO of Healthcare, Life Sciences and High performance Computing

It might seem far-reaching to say that big data analysis can fundamentally impact patient outcomes around cancer and other illnesses, and that it has the power to ultimately transform health services and indeed society at large, but that’s the precise goal behind the 100,000 Genome Project from Genomics England.

DNA backgroundFor background, Genomics England is a wholly-owned company of the Department of Health, set up to deliver the 100,000 Genomes Project. This exciting endeavor will sequence and collect 100,000 whole genomes from 70,000 NHS patients and their families (with their full consent), focusing on patients with rare diseases as well as those with common cancers.

The program is designed to create a lasting legacy for patients as well as the NHS and the broader UK economy, while encouraging innovation in the UK’s bioscience sector. The genetic sequences will be anonymized and shared with approved academic researchers to help develop new treatments and diagnostic testing methods targeted at the genetic characteristics of individual patients.

Dell EMC provides the platform for large-scale analytics in a hybrid cloud model for Genomics England, which leverages our VCE vScale, with EMC Isilon and EMC XtremIO solutions. The Project has been using EMC storage for its genomic sequence library, and now it will be leveraging an Isilon data lake to securely store data during the sequencing process. Backup services are provided by EMC’s Data Domain and EMC Networker.

The Genomics England IT environment uses both on-prem servers and IaaS provided by cloud service providers on G-Cloud. According to an article from Government Computing, “one of Genomics England’s key legacies is expected to be an ecosystem of cloud service providers providing low cost, elastic compute on demand through G-Cloud, bringing the benefits of scale to smaller research groups.”

There are two main considerations from an IT perspective around genome and DNA sequencing projects such as those being done by Genomics England and others: data management and speed. Vast amounts of research data have to be stored and retrieved, and this large-scale biologic data has to be processed quickly in order to gain meaningful insights.

Scale is another key factor. Sequencing and storing genomic information digitally is a data-intensive endeavor, to say the least. Just sequencing a single genome creates hundreds of gigabytes and the Project has sequenced over 13,000 genomes to date, which is expected to generate ten times more data over the next two years. The data lake being used by Genomics England allows 17 petabytes of data to be stored and made available for multi-protocol analytics (including Hadoop).

For perspective, 1 PB is a quadrillion bytes – think of that as 20 million four-drawer filing cabinets filled with text. Or, considering the Milky Way has roughly two hundred billion stars in its galaxy, if you count each single star as a single byte – it would take 5,000 Milky Way galaxies to reach 1PB of data. It’s staggering.

The potential of being able to contribute to eradicating disease and identify exciting new treatments is truly awe inspiring.  And considering the immense scale of the data involved – 5,000 galaxies! – provides new context around reaching for the stars.

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Digital Health Strategies – An introduction to Elastic Cloud Storage (ECS)

Nathan Bott

Healthcare Solutions Architect at EMC

This past April, my father reached two important milestones – he turned 70 and retired from a 40-plus year career in food science.  He is now planning to head back to Spain to complete the Camino de Santiago – or the Way of St. James – a journey he started in 2014.  Unfortunately he had to stop 150 miles into the 500 mile trek because of severe back and hip pain due to the emergence of degenerative disc disease.  After working with his physician to manage this new condition, he started to prepare for the upcoming trip by walking between 5 and 10 miles three times a week.  Along with this training came other ailments that would be expected with anybody his age:  pulled muscles, strained knees, and “light-headedness.”  This last ailment can be attributed to another condition he happens to have – Type 2 Diabetes.  And so it goes, as he gets older and tries to maintain a high level of activity, he will suffer more ailments, and spend more time and money (via Medicare benefits) managing these chronic conditions.

And he will not be alone.  My father was born in 1946 and is thus a first year baby-boomer, the first wave of new Medicare beneficiaries in which about 10,000 enroll every day.  The Congressional Budget Office expects over 80 million Americans will be Medicare eligible by 2035, an almost 50% increase in enrollment from 2015.  The cost per beneficiary is expected to increase even more as each patient will have multiple chronic conditions to manage; per the National Council on Aging:

  • About 68% of Medicare beneficiaries have two or more chronic diseases and 36% have four or more.
  • More than two-thirds of all health care costs are for treating chronic diseases.

The US government and the healthcare industry are well aware of the current “silver tsunami” and planning has been underway.

For the past 7 years, since the passage of the Hi-Tech provision in the American Recovery and Reinvestment Act (ARRA) in 2009 and the Medicare Shared Saving Program (MSSP) in 2011 the ground work has been laid to implement various programs and incentives to distribute the efforts to manage the cost of delivering healthcare to an ever expanding beneficiary population.  The prolific adoption of electronic health records technology by healthcare providers and the reorganization of reimbursements to these providers – from a fee-for-service to an outcomes based model – have combined to become a catalyst for a digital revolution in healthcare.

Government led healthcare reform programs like Accountable Care Organizations (ACO), the Patient Centered Medical Home, and the Precision Medicine initiative are predicated with having a digital technology platform that can use the demographic, financial, clinical and genetic data acquired from the vast population of patients to develop evidence-based plans of care that are specifically tailored based on the genetic disposition and the disease(s) of a given patient.

Medicine doctor hand working with modern medical iconsRegardless of the industry, product or service, a disruptive technology that drives innovation through digitization requires a re-assessment of the infrastructure that supports it; the healthcare industry is no different.  As healthcare providers have implemented electronic medical records systems, deployed enterprise imaging solutions, piloted next generation sequencing programs, and developed clinical informatics capabilities, new infrastructure requirements and operating modes have emerged.  Furthermore, in response to the evolving markets and reimbursement models explained above, many healthcare entities – providers, payers, and pharmaceuticals alike – have consolidated through mergers and acquisitions which also necessitate re-evaluating infrastructure architectures in order to rationalize operational capabilities, drive utilization efficiency and decrease both operational and capital costs.

Working directly with healthcare customers, collaborating with healthcare software vendors, and partnering with IT service providers, EMC has been on the front line to provide architectural guidance and infrastructure solutions to support this digital revolution and its emerging infrastructure requirements. A key infrastructure solution to support the digitization revolution in healthcare is a highly durable, geo-distributed, performant storage platform that will work with legacy monolithic systems using file system interfaces as well as cloud-native distributed applications using standard storage APIs like AWS S3 or OpenStack Swift.

ECSEMC’s Elastic Cloud Storage system (ECS) is a modern object storage platform that does just that…and more.  Just as important, the ECS object platform can be used for a myriad of use cases specifically for the healthcare industry to support:

  • Innovative technology platforms which enable coordinated and accessible medical services such as outlined by the Patient-Centered Medical Home program
  • Collaboration and data sharing as needed for programs such as the Accountable Care Organization initiative
  • An increase in IT operational agility using a storage platform that can be provisioned with cloud-based API’s
  • A decrease in costs through storage utilization efficiency at scale using modern data protection and replication methods

In my follow-up blog entries here, I will provide more details on the functional capabilities of ECS as well as map these capabilities to specific use cases that are driving the digital revolution to take on the challenges of delivering collaborative and personalized healthcare services to an aging population with multiple complex chronic conditions while driving down IT operational costs as well as the overall cost of the healthcare system.

Examples of the use cases I mentioned above include various new technology trends like the emerging Internet of Things (IoT) solutions that support remote patient monitoring, telehealth, and behavior modification tools to help manage chronic diseases; data lake functionality with the Hadoop ecosystem for population and precision health based analytics programs; and cloud-native development efforts to launch distributed mobile applications that can capture and access data from any location.

I look forward to exploring these use cases and examining how ECS’s unique capabilities will help our healthcare customers move towards meeting their technical, operational, and “digitized-mission” goals.

Delivering the Best Patient Care Possible

Barry Morris

Sales DVP at EMC Federal Division

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Military Health – From Volume to Value

The digital world is driving us to act as both patients and consumers of healthcare information. For example – wearable devices, such as Fitbits, provide users with personalized data and the insight required to make more informed lifestyle decisions.

IoT_HealthcareAt the same time, healthcare providers are shifting to value-based care – from “pay per pill” to “pay for performance” and “pay for outcomes” while working to meet meaningful use goals. Comprehensive patient and population health data, and data collection opportunities enabled by the Internet of Things (IoT) can provide opportunities for healthcare providers – including military – to attain new insights and deliver the best care possible.

In a recent article in Health IT Analytics, EMC’s Roberta Katz writes, “In the current accountable care environment, where electronic health record documentation is being prioritized, this new realm of patient generated data can build on a caregiver’s clinical expertise and augment hospital protocols…With the use of IoT tools and sensors, we can review our own data in real-time, from the number of steps we are taking, cardio output, sleep cycles, blood pressure, and even mood, to become an ‘empowered’ patient.”

Modern tablet showing medical diagnosisWorking toward a transformative goal to achieve, among others, the results stated by Katz show that the Military Health System (MHS) http://www.health.mil/ is undergoing a disruptive application migration from the current system (AHLTA) to the new Cerner-based  MHS GENESIS – targeted for launch at the end of this year. Their goal: the ability to share health records electronically and document the complete continuum of care between MHS locations, private providers, and possibly Veteran Affairs.

Centralized data collection and analysis as part of an extended Electronic Health Record (EHR) system can provide a picture otherwise impossible to obtain – bringing together disparate information that alone does not raise an alert, but pulled together, can signal a need for intervention.

EMC is proud to participate in the Defense Health Information Technology Symposium (DHITS) 2016 on August 2-4 – and will focus on supporting the MHS Transformation. Please visit us at booth 401 to learn more about how Big Data analytics and data lakes are transforming military health.

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Death Stars Are Powerless Against the Power of Knowledge

Yasir Yousuff

Sr. Director, Global Geo Marketing at EMC Emerging Technologies Division

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We have seen it happen again and Death Staragain, first with the Death Star, then with the Death Star II, and most recently, with the Starkiller Base. Precision shots by a pilot equipped with the right knowledge could destroy a weaponized base a thousand times bigger than his fighter craft. If you know what we’re talking about, chances are you’re a Star Wars fan, or have at least watched the series and understood the plot.

Medical Treatment Vs Death Star Destruction

So what do medical treatment and the destruction of Death Stars have in common? For one, it saves lives. For another, how insightful knowledge lies at the heart of such noble activity. But you see, insights do not just show themselves. They are the refined product of data analysis, supported by a base of powerful infrastructure.

To offer a better idea, let’s turn our attention to Sydney Adventist Hospital. Commonly referred to as the San, the facility is New South Wales’ largest private hospital, with some 53,000 patients and 180,000 outpatients treated annually.

Doctors here use a picture archive and communication system (PACS) as an essential diagnostic tool for patients. Since 2004, the average PACS study size for each patient has doubled from 32 megabytes to 76 megabytes with the number of cases exploding from 1,457 to over 64,000 studies a year.

“It is difficult to assess future storage requirements in a hospital environment because we can’t predict what diagnostic modalities will be brought on board,” says John Hoang, Senior Systems Engineer at Sydney Adventist Hospital.

At the San, specialist departments do their own research, attend conferences, and decide what tools will make a difference to patient outcomes. This means that the storage environment needs to be able to accommodate new tools as they are onboarded.

One can only imagine the kind of storage requirements needed to support such data expansion. And more than that, the speed required to scour and retrieve the right data files.

Imagine if you were an X-Wing fighter pilot taking heavy enemy fire and you had just one fly pass to take a single shot to destroy the Death Star. Chances are you’d need to know where to make the shot, and you’d need to know it really quick.

Similarly, time waits for no man in the medical world. Sometimes doctors only have one shot to treat a patient, and they need all the insights they can glean from patient diagnostic data. And they need it fast.

Turning Uncertainty into Certain Certainty

In addition to the San’s existing EMC VNX unified storage solution, a PACS storage environment has been deployed with two EMC Isilion X-Series clusters at two separate sites with 85 terabytes of storage. This has been further enhanced by EMC Isilon SyncIQ to provide easy-to-manage replication of data between the two sites, which is critical to the hospital’s agile infrastructure, ensuring all nodes in the Isilon cluster concurrently send and receive data during replication jobs.

“The PACS system is more resilient because more storage is handled on a multi-node architecture. If we lose one node, we still have two nodes online so specialists can continue to retrieve images. In this sense the technology has paid for itself – we simply don’t need to worry about outages or disruption to services due to storage limitations anymore,” explains Hoang.

Another piece of good news is when data volumes increase, capacity can be seamlessly scaled to ensure performance is consistent. An Isilon X-Series cluster can be easily brought online within minutes, with a single cluster possessing the ability to scale from a few terabytes to more than 50 petabytes. Now that’s over 200 gigabytes per second of throughput. From another perspective, a patient’s entire PACS history file could be downloaded even before a doctor finishes saying, “Do you feel pain here?”

A Legacy Forged Today

A long time ago in a galaxy far, far away…

Perhaps in a century or more, technology and medical historians would look back at this period as a defining moment where data represented infinite possibilities for human health. Who would have thought something as simple yet complex at the same time, such as data storage and retrieval, could play such a pivotal role?

Telemedicine Part 1: TeleRadiology as the growth medium of Precision Medicine

Sanjay Joshi

CTO, Healthcare & Life-Sciences at EMC
Sanjay Joshi is the Isilon CTO of Healthcare and Life Sciences at the EMC Emerging Technologies Division. Based in Seattle, Sanjay's 28+ year career has spanned the entire gamut of life-sciences and healthcare from clinical and biotechnology research to healthcare informatics to medical devices. His current focus is a systems view of Healthcare, Genomics and Proteomics for infrastructures and informatics. Recent experience has included information and instrument systems in Electronic Medical Records; Proteomics and Flow Cytometry; FDA and HIPAA validations; Lab Information Management Systems (LIMS); Translational Genomics research and Imaging. Sanjay holds a patent in multi-dimensional flow cytometry analytics. He began his career developing and building X-Ray machines. Sanjay was the recipient of a National Institutes of Health (NIH) Small Business Innovation Research (SBIR) grant and has been a consultant or co-Principal-Investigator on several NIH grants. He is actively involved in non-profit biotech networking and educational organizations in the Seattle area and beyond. Sanjay holds a Master of Biomedical Engineering from the University of New South Wales, Sydney and a Bachelor of Instrumentation Technology from Bangalore University. He has completed several medical school and PhD level courses.

Real “health care” happens when telemedicine is closely joined to a connected-care delivery model that has prevention and continuity-of-care at its core. This model has been defined well, but only sparsely adopted. As John Hockenberry, host of the morning show “The Takeaway” on National Public Radio, eloquently puts it: “health is not episodic.” We need a continuous care system.

Telemedicine makes it possible for you to see a specialist like me without driving hundreds of miles

Image source: Chest. 2013,143 (2):295-295. doi:10.1378/chest.143.2.295

How do we get the “right care to the right patient at the right time”? Schleidgen et al define Precision Medicine also known as Personalized Medicine (1) as seeking “to improve stratification and timing of health care by utilizing biological information and biomarkers on the level of molecular disease pathways, genetics, proteomics as well as metabolomics.” Precision Medicine (2) is an orthogonal, multimodal view of the patient from her/his cells to pathways to organs to health and disease. There are several devices and transducers that would catalyze telemedicine: Radiology, Pathology, and Wearables. I will focus on Radiology for this part of my three-part series, since all of these modalities use multi-spectral imaging.

Where first?
The world is still mostly rural. According to World Bank statistics, 19% of the USA is rural, but the worldwide average is about 30% which is a spectrum from 0% rural (Hong Kong) to 74% rural (Afghanistan). With the recent consolidations (since 2010 in the US) of hospitals into larger organizations (3), it is this 30% to 70% of the world with sparse network connectivity that needs telemedicine sooner than the well-off “worried well” folks who live in dense urban areas with close access to healthcare. China has the world’s largest number of hospitals at around 60,000 followed by India at around 15,000. The US tally is approximately 5,700 hospitals. The counter-argument to the rural needs in the US is the risk of reduction of physician numbers (4), the growing numbers of the urban poor and the elderly. Then there is the plight of poor health amongst the world’s millions of refugees who are usually stuck in no-mans-lands, fleeing conflicts that never seem to wane. All these use-cases are valid, but need prioritization.

Connected Health and the “Saver App”
Many a fortune has been made by devising and selling “killer apps” on mobile platforms. In healthcare what we need is a “saver app.” Using the pyscho-social keys to the success of these “sticky” technologies, Dr. Joseph C. Kvedar succinctly builds the case for connected health in his recent book “The Internet of Healthy Things” with three strategies and three tactics:

Strategies: (1) Make It about Life; (2) Make It Personal; and (3) Reinforce Social Connections.

Tactics: (1) Employ Messaging; (2) Use Unpredictable Rewards; and (3) Use the Sentinel Effect.

Dr. Kvedar calls this “digital therapies.”

The Vendor Neutral Archive (VNA) and Virtual Radiology
The Western Roentgen Society, a predecessor of the Radiological Society of North America (RSNA), was founded in 1915 in St. Louis, Missouri (soon after the invention of the X-Ray tube in Bavaria in 1895). An interactive timeline of Radiology events can be seen here. Innovations in Radiology have always accelerated the innovations in healthcare.

The Radiology value chain is in its images and clinical reporting, as summarized in the diagram below (5):

Radiology value chain

To scale this value-chain for telemedicine, we need much larger adoption of VNA, which is an “Enterprise Class” data management system. A VNA consolidates multiple Imaging Departments into:

  • a master directory,
  • associated storage and
  • lifecycle management of data

The difference between PACS (Picture Archiving and Communications System) (6) and VNA is the Image Display and the Image Manager layers respectively.

The Image Display layer is a PACS Vendor or a Cloud based “image program”. All Admit, Discharge and Transfer (ADT) information must reside with the image. This means DICOM standards and HL7 X.12N interoperability (using service protocols like FHIR) are critical. The Image Manager for VNA is the “storage layer of images”, either local or cloud based. For telemedicine to be successful, VNA must “scale-out” exponentially and in a distributed manner within a privacy and security context.

VNA’s largest players (alphabetically) are: Agfa, CareStream, FujiFilm (TeraMedica), IBM (Merge), Perceptive Software (Acuo), Philips and Siemens. The merger of NightHawk Radiology with vRad which was then acquired by MedNax and IBM’s acquisition of Merge Healthcare (in Aug 2015) are important landmarks in this trend.

One of the most interesting journal articles in 2015 was on “Imaging Genomics” (or Radiomics) of glioblastoma, a brain cancer. By bidirectionally linking imaging features to the underlying molecular features, the authors (7) have created a new field of non-invasive genomic biomarkers.

Imagine this “virtual connected hive” of patients on one side and physicians, radiologists and pathologists on the other, constantly monitoring and improving the care of a population in health and disease at the individual and personal level. Telemedicine needs to be the anchor architecture for Precision Medicine. Without Telemedicine (and VNA), there is no Precision Medicine.

Postscript: Telepresence in mythology
Let me end this tale of distance and care with a little echo from my namesake, Sanjaya, who is mentioned in the first chapter of the first verse of the Bhagvad Gita (literally translated as the “Song of the Lord”) – an existential dialog between the warrior Arjuna and his charioteer, Krishna. The Gita, as it is commonly known, is set within the longest Big Data poem with over 100,000 verses (and 1.8 million words), the Mahabharata, estimated to be first written around 400 BCE.

Dhritarashtra, the blind king, starts this great book-within-book by enquiring: “O Sanjaya, what did my sons and the sons of Pandu decide about battle after assembling at the holy land of righteousness Kurukshetra?”

Sanjaya starts the Gita by peering into the great yonder. He is bestowed with the divine gift of seeing events afar (divya-drishti); he is the king’s tele-vision – and Dhritarashtra’s advisor and charioteer (just like Krishna in the Gita). The other great religions and mythologies also mention telepresence in their seminal books.

My tagline for the “trickle down” in technology innovation flow is “from Defense to Life Sciences to Pornography to Finance to Commerce to Healthcare.” One interpretation of the Mahabharata is that it did not have any gods – all miracles were added later. Perhaps we have now reached the pivot point for telepresence which has happened in war to “trickle down” into population scale healthcare without divine intervention or miracles!

References:

  1. Schleidgen et al, “What is personalized medicine: sharpening a vague term based on a systematic literature review”, BMC Medical Ethics, Dec 2013, 14:55
  2. “Toward Precision Medicine”, Natl. Acad. Press, June 2012
  3. McCue MJ, et al, “Hospital Acquisitions Before Healthcare Reform”, Journal of Healthcare Management, 2015 May-Jun; 60(3):186-203.
  4. Petterson SM, et al, “Estimating the residency expansion required to avoid projected primary care physician shortages by 2035”, Annals of Family Medicine 2015 Mar; 13(2):107-14. doi: 10.1370/afm.1760
  5. Enzmann DR, “Radiology’s Value Chain”, Radiology: Volume 263: Number 1, April 2012, pp 243-252
  6. Huang HK, “PACS and Imaging Informatics: Basic Principles and Applications”, Wiley-Blackwell; 2 edition (January 12, 2010)
  7. Moton S, et al, “Imaging genomics of glioblastoma: biology, biomarkers, and breakthroughs”, Topics in Magnetic Resonance Imaging. 2015

 

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