Digital Health and Emerging HealthTech in Southeast Asia

 
Digital Health and Emerging HealthTech in Southeast Asia
www.pwc.com/sg

Digital Health and Emerging
HealthTech in Southeast Asia:
Facts and the Value, Challenges Faced
& Success Factors for Implementation

Digital Health Conference: Telemedicine 4.0
Dorsett Grand Hotel, Subang, Malaysia

20-21 June 2019

Dr. Zubin J Daruwalla, MBBCh (Hons), BAO, MRCSI, MCh (Orth), MMed (Orth)

Health Industries Leader, PwC Singapore & PwC South East Asia Consulting
Digital Health and Emerging HealthTech in Southeast Asia
Facts and the Value

Digital Health and Emerging HealthTech in Southeast Asia   June 2019
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Digital Health and Emerging HealthTech in Southeast Asia
How long did it take the telephone to get to 50 million users?

  A. 15 years
  B. 35 years
  C. 55 years
  D. 75 years

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Digital Health and Emerging HealthTech in Southeast Asia
How long did it take the television to get to 50 million users?

  A. 3 years
  B. 13 years
  C. 23 years
  D. 33 years

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Digital Health and Emerging HealthTech in Southeast Asia
How long did it take Angry Birds to get to 50 million users?

  A. 1 year
  B. 1/2 year
  C. 3 months
  D. 1 month

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Digital Health and Emerging HealthTech in Southeast Asia
NEW ENTRANTS – NEW TECHNOLOGY – NEW BUSINESS MODELS

     NEW FINANCING MECHANISMS – NEW HEALTHCARE DELIVERY MODELS

             Accessibility                  Interoperability              Security (Cyber)
             Affordability                    Integration    New entrants     Safety
               A+ Care

 New Health Economy
People                       Technology   Engagement                 Transparency
Privacy                    Transformation Experience                  Treatment
                                           Expertise

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Digital Health and Emerging HealthTech in Southeast Asia
The pace of digitization is exponentially increasing; years to days

                                                  Digitalization Adoption

        Telephone                                                                         75 years

               Radio                                                   38 years

                   TV                                       13 years

           Internet                               4 years

         Facebook                           3.5 years

                 iPod                  3 years
                                                                                  TIME TO 50
                 AOL              2.5 years                                        MILLION
                                                                                    USERS
DrawSomething!             50 days

               Angry     35 days
               Birds

Source: visual.ly.com
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Digital Health and Emerging HealthTech in Southeast Asia
Singapore has already become the Asian centre of HealthTech deals, providing
 potential for start-ups to grow and scale in the region with the expectation that
 more HealthTech start-ups will be based in Singapore as our HealthTech market
 continues to grow significantly

 HealthTech Deal Volume Share by Market                         Singapore’s HealthTech Funding
 (excluding China and India)                                    According to Galen Growth Asia’s report, Singapore witnessed
                                                                26 HealthTech funding deals in 2018, closing a record breaking
              2017                                2018          total of US$134M. It is in fact the third largest digital health
                                                                ecosystem in Asia.
  Japan
  Japan              30%              Singapore          29%
                                      Japan

  Singapore
  Australia          29%              Japan              27%
                                      Australia

  Australia          18%              South              13%
                                      SingaporeKorea
  Singapore

  Vietnam
  Vietnam            5%               Australia          11%
                                      Vietnam

  South    Korea
  South Korea        4%               Indonesia            5%
                                      South Korea

  Taiwan
  Japan              3%               Taiwan             3%
                                      Japan

  Hong
  Australia Kong     1%               Thailand           3%
                                      Australia

  Myanmar
  Singapore          1%               Philippines        3%
                                      Singapore

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Digital Health and Emerging HealthTech in Southeast Asia
According to Enterprise Singapore, HealthTech start-ups currently
already comprise 9% of all start-ups in Singapore

                                                           HealthTech Start-ups in Singapore
                                                           According to Enterprise Singapore, there are 269 HealthTech and
                                                           MedTech startups out of 3,144 startups. Among these, 53% of
                                                           HealthTech startups are incorporated within 5 years.

                                                                   HealthTech start-ups by sectors

                                                                                                   23%
                                                                   33%

                                                                                                        16%

                                                                          28%
                                                               Biotech    Digital health   Healthcare     Medtech

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Digital Health and Emerging HealthTech in Southeast Asia
2016

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Even across emerging markets, there are countless new digital
health models being developed, many of which have already
revolutionized the way care is delivered

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Harnessing the power of digital technology will be
      key to helping Southeast Asia’s health industry
         bridge the gap and provide access to and
        affordability of care, as well as catalyze the
    proliferation of quality care delivery in the region.

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Source: US Bureau of Labour Statistics, 2015
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Healthcare organizations have much to benefit from
         a developed digital health market.

                                                           Patient empowerment and centricity

    Improved client engagement and patient experience

                          Reduction in human error and thus improved patient safety

                                           Optimization of operations

                                                           Improved cost efficiency

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So if all these advantages exist, what are the challenges to
      adoption then? The reasons for this slow adoption in the
                   healthcare industry are complex.

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Challenges Faced

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“We are different with our differences making the application of
 developed market business models futile”

 At times, organisations do not realise that the varying and often
                      volatile demographics of
   emerging markets differ from developed economies
with market segment and consumer preferences changing rapidly,
              the four key differentiating factors being
                     (1) Population Growth,
                      (2) Population Aging,
             (3) Population Distribution, and the
      (4) Population Income Rise of the Middle Class.

  Digital Health and Emerging HealthTech in Southeast Asia     June 2019
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2016

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Population Growth

•     The rate of population growth in emerging markets presents a significant challenge as
      infrastructure is not being developed at the same rate resulting in a strain on resources

Source: United Nations – World Population Prospects 2015 Revision
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Population Aging

•     The portion of the population aged over 65 years increasing exponentially presents
      another challenge to business models that are not tailored to the elderly

Source: United Nations – World Population Prospects 2015 Revision
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Population Distribution

•     The rural percentage of populations across Southeast Asia (and Asia more broadly)
      make accessibility a challenge for businesses, especially to those whose models are
      built for developed markets

Source: United Nations – World Urbanization Prospects 2014
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Population Income Rise of the Middle Class

•     The increasing proportion of middle class whom have a greater willingness to spend
      result not only in higher expectations (basic and simple care -> quality and complex)
      but also a greater incidence and prevalence of non-communicable or chronic disease,
      necessitating a shift of focus of many of today’s point solutions to more holistic ones

Source: United Nations – Kharas, H (2010). “The Emerging Middle Class in Developing Countries.” Development Centre Working Papers. No. 295. OECD Publishing
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Other sources of inhibition also exist

•    Depleted labour market conditions
           •    Nurturing of local medical talent insufficient and compounded by fact that many
                strive to seek better opportunities overseas
           •    Problem even in developed countries with the need for workforce
                transformation high up on the agenda

•    Insufficient and inefficient finance
           •    Inadequate public sector funding impedes sector growth and calls for new
                financing sources like public-private partnerships

•    Fragmented and/or immature business, legal and regulatory environment
           •    Structure, governance, frameworks and guidelines are lacking in many nations
                with the ease of doing business, laws and regulations varying

Source: World Economic Forum ‘Network Readiness Index’ 2015
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The fact that fundamental gaps exist in every aspect of Information
Communication Technology makes it unlikely for emerging
economies to adopt the traditional health model

Ten parameters required to leverage ICT for social and economic impact

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As a result however, this allows emerging economies to leapfrog
developed markets and adopt the new digital health model

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“Cost and ROI are not necessarily real concerns”

              High upfront and maintenance costs
        for digital transformation, coupled with a difficulty in
                  defining and measuring value
      in healthcare often have organizations and governments
                questioning their ROI in digital health.

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Remember this from the earlier slide?

Source: US Bureau of Labour Statistics, 2015
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2017

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High upfront and maintenance costs

A transition to paperless records and virtual consults signals
a paradigm shift from traditional medical practices
                                    Upfront costs to acquire technology may be high
                            Employee training
                                            Change management
Creation of governance and compliance strategies
                  Cybersecurity for data management, ownership and privacy
  System integration and maintenance

                                      Investing in resources and building capabilities

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• Different stakeholders see “value” differently (hospitals vs
 patients)
• Taking into account the positive externalities of a healthcare         investment
 (wider impact of vaccinations, for example)
•      Future outlook shrouded in uncertainty (unable to project long-term)
• Lack of consensus over methodology for ROI measurement and metrics in
 healthcare (ROI = ? net profit/total cost of investment)
•      Broad impact of technology (cross-functional)
•      Differing healthcare system characteristics (data availability)

                                 defining and measuring value

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• Different stakeholders see “value” differently (hospitals vs
 patients)
• Taking into account the positive externalities of a healthcare
 investment (wider impact of vaccinations, for example)
•      Future outlook shrouded in uncertainty (unable to project long-term)
• Lack of consensus over methodology for ROI measurement and metrics in
 healthcare (ROI = ? net profit/total cost of investment)
•      Broad impact of technology (cross-functional)
•      Differing healthcare system characteristics (data availability)

                                 defining and measuring value

    Digital Health and Emerging HealthTech in Southeast Asia              June 2019
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• Different stakeholders see “value” differently (hospitals vs
 patients)
• Taking into account the positive externalities of a healthcare         investment
 (wider impact of vaccinations, for example)
• Future outlook shrouded in uncertainty (unable to project
 long-term)
• Lack of consensus over methodology for ROI measurement and metrics in
 healthcare (ROI = ? net profit/total cost of investment)
•      Broad impact of technology (cross-functional)
•      Differing healthcare system characteristics (data availability)

                                 defining and measuring value

    Digital Health and Emerging HealthTech in Southeast Asia                  June 2019
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• Different stakeholders see “value” differently (hospitals vs
 patients)
• Taking into account the positive externalities of a healthcare         investment
 (wider impact of vaccinations, for example)
•      Future outlook shrouded in uncertainty (unable to project long-term)
• Lack of consensus over methodology for ROI measurement and
 metrics in healthcare (ROI = ? net profit/total cost of investment)
•      Broad impact of technology (cross-functional)
•      Differing healthcare system characteristics (data availability)

                                 defining and measuring value

    Digital Health and Emerging HealthTech in Southeast Asia                  June 2019
    PwC
• Different stakeholders see “value” differently (hospitals vs
 patients)
• Taking into account the positive externalities of a healthcare         investment
 (wider impact of vaccinations, for example)
•      Future outlook shrouded in uncertainty (unable to project long-term)
• Lack of consensus over methodology for ROI measurement and metrics in
 healthcare (ROI = ? net profit/total cost of investment)
•      Broad impact of technology (cross-functional)
•      Differing healthcare system characteristics (data availability)

                                 defining and measuring value

    Digital Health and Emerging HealthTech in Southeast Asia                  June 2019
    PwC
• Different stakeholders see “value” differently (hospitals vs
 patients)
• Taking into account the positive externalities of a healthcare     investment
 (wider impact of vaccinations, for example)
•      Future outlook shrouded in uncertainty (unable to project long-term)
• Lack of consensus over methodology for ROI measurement and metrics in
 healthcare (ROI = ? net profit/total cost of investment)
•      Broad impact of technology (cross-functional)
•      Differing healthcare system characteristics (data availability)

                                 defining and measuring value

    Digital Health and Emerging HealthTech in Southeast Asia              June 2019
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ROI measurements re-imagined

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Recognizing the potential for cost savings

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Success Factors for Implementation

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2018

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The clock is already ticking…Is the time ripe for healthcare?

                                                     The most valuable retailer,
                                                       owns no inventory

             The world’s most popular media
              owner, creates no content

                                                                            The world’s largest taxi company,
                                                                                  owns no vehicles

                                      The world’s largest accommodation
                                       provider, owns no real estate

Digital Health and Emerging HealthTech in Southeast Asia                                                        June 2019
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A new era of health is upon us…Are we ready for a hospital which
has no patients?

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As a clinician, I’ve always believed we should use technology to
complement our clinical practices, not replace them (at least not yet)

                          Are we losing the
                          healing ‘touch’ of
                          medicine?

                                                                                             Image from: Philips /
                                                                                             www.usa.philips.com

         Image from: http://medicalfuturist.com/why-people-should-not-fear-digital-health/

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NEW ENTRANTS – NEW TECHNOLOGY – NEW BUSINESS MODELS

     NEW FINANCING MECHANISMS – NEW HEALTHCARE DELIVERY MODELS

             Accessibility                  Interoperability              Security (Cyber)
             Affordability                    Integration    New entrants     Safety
               A+ Care

 New Health Economy
People                       Technology   Engagement                 Transparency
Privacy                    Transformation Experience                  Treatment
                                           Expertise

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Accessibility                  Interoperability              Security (Cyber)
             Affordability                    Integration    New entrants     Safety
               A+ Care

P.A.T.I.E.N.T.S.
People                       Technology   Engagement                 Transparency
Privacy                    Transformation Experience                  Treatment
                                           Expertise

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As technology gets more sophisticated, digital innovations and
care delivery could evolve from a HCP professional coming to the
patient to detection & treatment capabilities inside the body
                                  2010                                 2020                            2025                           2030

     Improved Processing and                  Shrinking sensor sizes and          Cloud and mobile            Artificial intelligence and
       software engineering                   innovative manufacturing        communication technologies          Nano-technology

                                                            Wearables
                                                            Ingestible & implantable
                                                            sensors
                                                            Ambulance drones
                                                                                                              Convergence of
                                                            “Trauma care in a rucksack”
                                                                                                                healthcare
                                                            Smart homes                                         technology
                                                                                                               capabilities

                                                                                                                 Run by
                                                                                                             brain-machine
                                                                                                           interfaces and AI?
  You go to healthcare                          Healthcare comes to             You carry healthcare          Healthcare is inside you
                                                       you

Source: “The Singularity is Near” by Ray Kurzweil, PwC analysis
Digital Health and Emerging HealthTech in Southeast Asia                                                                             June 2019
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“If you fail to prepare, prepare to fail”

Three key factors amongst many that support the culmination of a state of
adequate preparedness exist

•   Regulatory and compliance management

•   Secure deployment of connected medical devices

•   Data governance, protection and privacy

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Other success factors also exist

                                                           s
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Connectivity
                                            Culture

                            Credibility                           Change
                                                                management
               Cost
          (Affordability)
                                                                  Convenience
                          Consent                                (Accessibility)
                          (Privacy,
                        HIPPA, PDPA)                       Cybersecurity

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8 Cs -> 1 C
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ollaboration

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THE FUTURE OF HEALTH IS DIGITAL

                       LET US KEEP PATIENTS AT THE HEART
                       OF WHAT WE DO

USE TECHNOLOGY TO COMPLEMENT OUR
CLINICAL PRACTICES, NOT REPLACE THEM

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THANK YOU

    For further information, please contact:

                                    Dr. Zubin J Daruwalla
                                    Health Industries Leader
                                    PwC Singapore & PwC South East Asia Consulting

                                    t: +65 9751 7023
                                    e: zubin.j.daruwalla@pwc.com

© 2019 PricewaterhouseCoopers. All rights reserved.
PwC refers to the Singaporean member firm, and may sometimes refer to the PwC network.
Each member firm is a separate legal entity. Please see www.pwc.com/structure for further details.

Liability limited by a scheme approved under Professional Standards Legislation
Wearables

Case Study: Verily and Alcon – Digital contact lenses for
diabetes management

     1                                                                   2

    Sensors are embedded                                                 A microscopic wireless antenna
    between two soft layers of                                           then communicates this data to a
    lens material and a pinhole                                          wireless device, which transmits
    in the lens allows tear fluid                                        it to external receiver devices
    to seep into the sensor and                                          (users, care givers, providers
    be used to measure blood                                             etc.)
    sugar levels.

         4                                                                 3
      Providers can predict                                              Continuous glucose data
      adverse events caused by                                           is also sent to an
      diagnosis based on                                                 associated app on the
      continuous glucose                                                 user’s smartphone which
      monitoring data                                                    prompts the user to act
                                                                         and make decisions

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Wearables

Case Study: SENSIMED Triggerfish® – Smart contact lenses
to tackle glaucoma

    1 SENSIMED Triggerfish Sensor is a
                          ®
                                                                         3 The data is transmitted through a thin
        soft disposable silicone contact lens                               flexible cable from the Antenna to the
        embedding a micro-sensor that                                       portable recorder
        captures spontaneous circumferential
        changes at the corneoscleral area

                                                                         4 The portable recorder, worn by the patient,
                                                                            stores the acquired data during the monitoring
  2 The adhesive SENSIMED
                                                                            session. At the end of the recording period, the
      Triggerfish Antenna, which is placed
              ®

      around the eye, receives wirelessly the                               data is transferred via Bluetooth from the
      information from the contact lens                                     recorder to the software previously installed on
                                                                            the practitioner’s computer

      • Provides information on continuous natural changes to the eye
        to ophthalmologists including intraocular pressure
      • Allows improved glaucoma management and faster intervention

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Wearables

Case Study: GenSight Biologics – Biomimetic goggles to
treat faulty retina with a goal to preserve or restore vision

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Wearables

Case Study: ReThink Medical – Heart failure prediction

                                                        •    Raised $3m for a wearable that predicts and
                                                             prevents heart failure

                                                        •    Algorithms can detect signatures of worsening
                                                             heart conditions weeks before patient senses them;
                                                             usually a month of worsening conditions and heart
                                                             failure

                                                        •    Data transmitted via WiFi hub to a provider, who
                                                             intervenes if problems detected

                                                        •    Partnership with Japanese device company
                                                             Terumo

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Wearables

Companies driving innovations in smart clothing

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Wearables

  Other wearable examples by Pharma and MedTech

                        NEC/Gunze Ltd. - Developed an                        Toshiba - rolling out two activity trackers that
                        intelligent undershirt that can be                   can help caregivers monitor seniors
                        connected to a smartphone and provide                remotely. Through an analysis of sensor data, the
                        data on the health of the person wearing             Silmee W20 and W21 wristbands can help track
                                                                             the amount of time a user spends eating as well as
                        it. The shirt has an ultra-fine and flexible         conversing with others. The bands can compile the
                        sensor (which can be removed before                  data into life logs to be shared with caregivers
                        the shirt is washed) that can monitor
                        posture, heart rate, and calories
                        consumed and burned.

Kyocera - announced that it will collaborate with The                      Takeda – Getting serious about digital Takeda walks the walk
Association for Preventive Medicine of Japan in the field of               with its digital accelerator model The company has also
healthcare to offer a new service, Daily Support®, which aims              launched iBData, a wearable digital technology pilot program
to assist with continuous lifestyle habit improvements through             to support patients and physicians with the management of
the use of a smartphone and wearable device combined with                  inflammatory bowel disease (IBD). The program is a
individual guidance from healthcare professionals. Planned to              partnership with Texas Digestive Disease Consultants and
launch in fall 2015 in Japan, the service will be provided to              Vanderbilt University Medical Center and is designed for IBD
companies, health insurance unions and healthcare service                  patients to track their symptoms and lifestyle factors with
providers seeking better health management for employees                   wearable watch technology
and clients.

  Global Healthcare Trends and the Transformative Future of the Industry                                                  June 2017
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Point of care diagnostics

  Case Study: eyeNETRA – Point of care diagnostics and VR

             Mobile Clinic Kit with Printer

                                                                           • MIT-incubated start-up that offers a series of Point
                                                                             of Care diagnostic tests for refractive errors (near
                                                                             and far sightedness)
Smart Phone Autorefractor            Smart Phone Lensometer
                                                                           • The equipment easily plugs into smartphones and
                                                                             has supporting applications which enable easy
                                                                             diagnosis, recording and transmission of test results
                                                                           • The company is now seeking partners to create
                                                                             prescription Virtual Reality Screens

               Smart Phone Lensometer

  Global Healthcare Trends and the Transformative Future of the Industry                                                  June 2017
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Telemedicine

Case Studies: MedShr and MyDoc – Smart phone apps that
can be used to seek second opinions via affordable and
accessible teleconsults

                                                                         Create cases   Share & Discuss Connect & Network

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Telemedicine

Case Study: Tan Tock Seng Hospital, Singapore – Improving
eye care with tele-ophthalmology

                                                                         • Modified teleconferencing system to
                                                                           enable patients and specialists to see
                                                                           and speak to each other

                                                                         • System is set up at easily accessible
                                                                           neighborhood polyclinics and uses
                                                                           portable cameras and multiple
                                                                           computer screens

                                                                         • Clinic does a pre-consultation
                                                                           assessment and results are shared
                                                                           with specialists ahead of the
                                                                           consultation

                                                                         • Initiative found to reduce the load of
                                                                           acute care institutions and is now
                                                                           being extended to multiple polyclinics

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Drones

Case Study: Deft University of Technology – Ambulance
drone with cardiac defibrillator

•    Ambulance drone in-built with a cardiac defibrillator that can reach patients during a cardiac
     arrest within 12 square km in less than 1 minute
•    Via telemedicine and an in-built camera, an emergency operator can give instructions and observe
     for correct application by the civilian responder
•    Survival rate from a cardiac arrest could be increased to 80% under the quick arrival response of
     the ambulance drones, rising even to 90% when an untrained responder is given accurate
     instructions by the emergency operator.

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Genomics

Case Study: GenSight Biologics – Genetic engineering-based
novel therapies for neurodegenerative diseases of the eye

 The proprietary Mitochondrial                                                 Optogenetics uses gene therapy to
 Targeting Sequence (MTS) permits                                              introduce a gene encoding for a
 missing mitochondrial proteins to be                                          light-sensitive protein into specific target
 shuttled into the mitochondrion, enabling                                     cells in the retina enabling them to respond
 restoration of mitochondrial function                                         to light stimulation in place of damaged
                                                                               photoreceptor cells

   Leber Hereditary Optic Neuropathy (LHON)                    Retinitis Pigmentosa (RP)     Geographic Atropy in dry-AMD

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Big data

Case Study: Intelligent Research in Sight (IRIS™) – Registry
for ophthalmology cases

What is IRIS™?                                                           What does IRIS™ offer?
•    First comprehensive eye disease                                     •   Consistent quality reporting
     clinical database                                                       standards and outcome
•    Captured data from 10,800                                               measures for eye diseases
     ophthalmologists covering more                                      •   Measures efficacy of various
     than 48 million patients (2015                                          therapy options
     estimate)                                                           •   Identifies areas for further
•    Uses HIPAA-compliant methods to                                         research and validation
     collect data from EHRs
•    Provides real-time feedback and
     drives improvements in quality
     and outcomes

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Artificial intelligence

    Case Study: Google’s Deep Mind – AI to diagnose diabetic
    retinopathy and AMD

•    Google’s Deep Mind team is partnering with UK’s
     NHS to develop a machine learning algorithm that
     can scan millions of retinal images and detect
     diabetic retinopathy and age-related macular
     degeneration (AMD)
•    Physicians currently diagnose using physical
     medical charts and interviewing patients but the
     error rates are 10-20% on average

    Global Healthcare Trends and the Transformative Future of the Industry                    June 2017
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Artificial intelligence

Some other examples of AI in healthcare

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Digital

Case Study: 6 over 6 – Digital optometry tools for consumers

GlassesOn                                                                GlassesOn Eyes
•    Mobile-based digital optometric tools to                            •   Currently under development
     check eyesight and buy glasses online                               •   Manipulates optical and perceptual
•    Uses a patent technique involving                                       phenomena to give full measurement of
     manipulation of light; registered as a Class 1                          refractive errors
     Exempt Medical Device with the FDA
•    Provides a spontaneous, fashion-centric
     experience

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Digital

Case Study: Novartis and TicTrac – Patient engagement
platform for people with multiple sclerosis

•    Partnership with patient engagement platform for multiple sclerosis patients to record data from
     wearables and social media

•    The campaign prompts participants to track different aspects of their lifestyle including weight,
     activity, mood, and workload

•    This data is used to create visualizations of their day-to-day life. Participants can sync various
     platforms and devices with Tictrac's platform including Fitbit, Jawbone UP, Withings, Gmail,
     Facebook, and Runkeeper

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Digital

Case Study: Mount Sinai – Healthcare information access

 Mount Sinai Hospital and Apple co-developed an
 app which connects healthcare professionals.

                         App provides healthcare professionals with
                         anywhere access to data from 66 applications used
                         in the hospital.
                         Data includes clinical data, reference materials
                         and patient information. Passwords and VPN
                         certificates provide the appropriate levels of
                         security

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Digital

Case Study: Ningbo – Digital and cloud hospital in China

Global Healthcare Trends and the Transformative Future of the Industry   June 2017
PwC                                                                             73
New entrants

Case Study: A futuristic combination to replace hospitals?

Global Healthcare Trends and the Transformative Future of the Industry          June 2017
PwC                                                                                    74
New entrants

    Case Study: Are telcos the perfect medium?

  PwC’s DoubleJump™ Interchange supports collaboration across an ecosystem with
                          telcos being ideal partners
Data Sources                                                                                Care Team /               Patient /                                Analytics/Apps
                                                 Remote                                    Clinician Apps            Consumer
                                                Monitoring                                                             Apps               Visualization
                                                                                                                                          / Reporting
                        Public /
                      Government                                                                                                                             Statistical
                                                                    Monitoring                                                                               Packages
                                                                     Devices
                                              Benchmarking         (biometrics)
      Sensing /                                                                                                                                                Analytics & Cognitive
                                  Activity
        IoT                                                                                                                                                     Computing Engines
                                  Sensors
                               (steps, GPS)                                  PwC’s
                                                                         DoubleJump™
                                       EHR/HIE
      Hospitals /
       Clinics
                                   (clinical records)                     Interchange                                                 Registry / Support
                                                                                                                                        Group (Self-
                                                                                                                                          Reported)                    Family, Friends,
                                          Kiosk (remote        Claims
                                                                                               Pharmacy platform                                                         and Patient
                                           monitoring)         (Cost/                                                    Research Data
                                                                              Activities        (prescription and                                                         Advocates
                                                             Utilization)                                                 (e.g., Omics)
                                                                                                 fulfillment data)
                    Retail
                                                                                                                                             Researchers

                                                 Risk-Bearing Entities      Community
Collaborators                                                                Programs             Pharmacy

                                                                      Ecosystem Enablers
            Technology                                    Contracts                                   Shared Services                                     Value Capture

    Global Healthcare Trends and the Transformative Future of the Industry                                                                                         June 2017
    PwC                                                                                                                                                                   75
New entrants

Case Study: Insurance

Global Healthcare Trends and the Transformative Future of the Industry          June 2017
PwC                                                                                    76
New entrants

Case Study: Retail

 Retail Health, Retail Medicine and the New Healthcare Experience

 People expect convenience, quality and transparency when choosing how to spend
 time and money – and increasingly they seek the same from healthcare providers.
 Retail health is emerging as a means of delivering quality, convenient care to millions
 of consumers, as well as a model for healthcare systems to consider when providing
 services to new and existing patient populations.
Global Healthcare Trends and the Transformative Future of the Industry               June 2017
PwC                                                                                         77
New entrants

Examples of various industry sectors using telemedicine
service offerings

Global Healthcare Trends and the Transformative Future of the Industry          June 2017
PwC                                                                                    78
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