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

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 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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Sanjay Joshi

About the Author: Sanjay Joshi

Sanjay Joshi is Industry CTO Healthcare at the Dell Global CTO Office. Based in Seattle, he has spanned the gamut of life-sciences from clinical and biotechnology research to healthcare informatics to medical devices. A "skunkworks" engineer and informaticist, he defines himself as a "non-reductionist" with a "systems view of the world.” His current focus is a systems-level understanding of Healthcare, Genomics, Proteomics, Microbiomics, Imaging and IoT processes, and data infrastructures. Recent experience has included AI platforms, data management and instruments for Electronic Medical Records; Proteomics and Flow Cytometry; FDA and HIPAA verification and validation; 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 completed several medical school and PhD level courses (in Sydney and Seattle). A list of selected recent invited talks and panels: • Next Generation Bioinformatics & Biotech Conf, Oct 2019: Mumbai India, Keynote, “Time Series, Machine Learning and the Microbiome: A summary” • GratiFi Summit, Jul 2019, Seattle WA, Panelist, “AI in Biotechnology.” • 601 Club, Jun 2019, Seattle WA, Moderator, “Artificial Intelligence and the Future of Health.” • Bio2Device & Silicon Vikings, Apr 2019, Palo Alto CA, Panelist, “Digital Health.” • BioIT World West, Mar 2019, San Francisco CA, Chair and Speaker, “Streamed Postcards from the Edge: Medical Device Architectures.” • Data Day Texas, Jan 2019: Austin TX, “Morals from a Type 2 Diabetes dataset analytics journey.” • Global AI Conference, Jan 2019: Santa Clara, CA, “Medical Device Architectures: Machine Learning on Streams” • Next Generation Bioinformatics & Biotech Conf, Oct 2018: Jaipur India, Keynote, “A Machine Learning Operational Analytics Story” • EPPICGlobal conference, Oct 2018, Burlingame CA, “Digital Health Keynote Panel” • AI in Healthcare Summit, Jun 2018: San Francisco CA, Chair and Panelist, “Executive Physician Roundtable” • BioIT World, May 2018, Boston MA, Chair and Speaker, Machine Learning and Data Science track • Medical Imaging in Clinical Research, Feb 2018 San Francisco CA; Speaker “Operational Imaging in Clinical Trials.” • AI in Healthcare Summit, Jan 2018 Boston MA: Keynote Panel and Genomics AI moderator • Kaiser Permanente Machine Learning Day, Dec 2017 Oakland CA: Panelist on AI in Healthcare • Interface Summit, Oct 2017, Vancouver Canada; Speaker “Pain: can AI shine a light on it?” • MinneAnalytics HALICON; Oct 2017, Minneapolis MN; Speaker “Two use-cases and a summary: Diabetes and Communicable Disease.” • mHealth Israel; Sep 2017, Jerusalem, Israel; Speaker “AI in Health: Hope or Hype?”