Digital Medicine and ML are here. AI is coming. How will innovation in digital medicine and biomedicine affect the future of healthcare? By Shahid N. Shah (@ShahidNShah) Health Futurist and Healthcare IT Entrepreneur Publisher, Netspective Media LLC 

www.himssqatar.org No Conflict of Interest This and many of my other presentations are available at www.SpeakerDeck.com/shah @ShahidNShah [email protected] www.ShahidShah.com 

Population health access and quality are not easy anywhere. What can the USA and Europe learn from the Middle East and what can the Middle East learn from the West? 

Can digital healthcare help Qatar and Middle East get onto the startup ecosystem map? https://startupgenome.com 

Technology has digitized our experiences Last and past decades Digitize mathematics & engineering Digitize maps, literature, news Digitize purchasing, social networks Predict crowd behavior This and future decades Digitize biology Digitize chemistry Digitize physics Predict human behavior Gigabytes and petabytes, all sharable Petabytes and exabytes, not shareable 

WHAT TECH WILL MAKE THE MOST DIFFERENCE? BLOCKCHAIN MACHINE LEARNING & AI CONVERSATIONAL UX BIOINFORMATICS VIRTUAL REALITY SELF DIAGNOSTICS Cybersecuriy is eating IT budgets Cybersecuriy is eating IT budgets 

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Machine Learning is here, AI is coming soon Solves access and quality. 

Computational drug discovery is here, but it’s mostly human led – AI based drug development is on the way 

“Cybertherapy” is showing great promise in pain management without drugs 

In the USA, Digital Medicine is slowed by intermediated business models, misunderstood regulations and protective regulations such as licensure and credentialing. Qatar and the Middle East could avoid these traps. Our business models are harming innovation in USA Our business models are harming innovation in USA 

Intermediation kills innovation, it is growing in many countries, and continues inefficient marketplaces between beneficiaries and funders. Population health requires collaborative engagement (CE), it cannot be done by individual institutions on their own. 

“My institution first” approach to patient care is harming healthcare in the USA Insurer | Payer Product 1 Product 2 Each population requires different engagement techniques at various times. But ecosystem participants don’t work together. Tech marketers cannot solve these problems but they can highlight inefficiencies and use them as conversation starters. Provider 2 Provider 1 

Collaborative engagement for shared benefit is how investors and innovators in Qatar and the Middle East could be more competitive Insurer | Payer Government Product 1 Product 2 Product 3 Each member population gets personal care through their provider or other advocate, enabled by health insurer tools and support. Provider 2 Provider 1 Influencers Influencers Caregiver 

www.netspective.com © 2017 Netspective. All Rights Reserved. 16 How do we move from “institution first” to “patient first” to true “patient centered” innovation? Hint: it’s not about patient engagement. It’s about knowing the patient reported outcomes drivers. 

www.netspective.com © 2017 Netspective. All Rights Reserved. 17 

www.netspective.com © 2017 Netspective. All Rights Reserved. 18 

www.netspective.com © 2017 Netspective. All Rights Reserved. 19 

Health Behaviors Clinical Care Social & Economic Factors Physical Environment 30% 20% 40% 10% Access to Care Quality of Care Education Employment Income Family/Social Support Community Safety Air & Water Quality Housing & Transit Source: RWJF/UWPHI. Genetics Diet & Exercise Tobacco Use Alcohol & Drug Use Sexual Activity Sleep Population based outcomes drivers 

Vector 2: Evidence-Based Decisions Vector 3: B2C Health Improvement Programs Vector 1: Next Generation Primary Care Self-tracking/testing: Wearables/Hardware Personalized Medicine/Genomics Health Information Care Navigation Disease Management Peer Networks Health Coaching Decision-Making Tools Care Access Remote Patient Monitoring Patient Engagement Health Behaviors 30% Wellness Programs Source: RWJF/UWPHI. Genetics Diet & Exercise Tobacco Use Alcohol & Drug Use Sexual Activity Sleep Family support & self- help patient groups Health behaviors outcomes drivers 

Vector 5: Analytics and Clinical Decision Support Vector 2: Next Generation Primary Care Vector 3: Value-Based Care Vector 4: Operational Efficiency Vector 1: Disease-Specific Care Pathways Care Coordination Patient Engagement Big Data Personalized Medicine Medication Management Clinical Care 20% Access to Care Quality of Care Nanotechnology Source: RWJF/UWPHI. Knowledge Sharing Clinical care outcomes drivers Practice Management, EMRs, Pharmacy Management Transparency Tech-enabled services Retail Clinics, DPC House Calls 

Advance Directives Programs/Services Next Gen Benefits Social Services Access/Management Vector 1: Equilibrating Healthcare Expense Vector 2: Community-Based Health Initiatives Vector 3: Aging & End-of-Life Programs Social & Economic Factors 40% Education Employment Income Family/Social Support Community Safety House Calls Hospice Programs Virtual Medicine Incentive Programs Wellness Programs Source: RWJF/UWPHI. Early ID and prevention programs Social & economic factors 

GPS-enabled sensors Physical Environment 10% Air & Water Quality Housing & Transit Vector 1: Targeted Monitoring and Rapid Response Vector 2: Community-Based Health Initiatives Vector 3: Affordable Living and Access Food , Housing, and Transportation Access Next Generation Public Transport Environmental Response Mechanisms Continuous Monitoring Source: RWJF/UWPHI. Built Environment Design Broadband connectivity Physical environment 

Data must lead the transformation, Middle East innovators must lead the data movement Manual Data Collection Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Docs and nurses as clerical staff TODAY 

Data must lead the transformation, Middle East innovators must lead the data movement Manual Data Collection Systems Integration Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence PGHD, Med Device Connectivity TODAY, ACCELERATING 

Data must lead the transformation, Middle East innovators must lead the data movement Manual Data Collection Systems Integration Reporting and Analytics Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Automating retrospective visibility TODAY 

Data must lead the transformation, Middle East innovators must lead the data movement Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Machine Learning Augmented Intelligence Artificial Intelligence Pattern matching mastery (unsupervised and supervised) 

Data must lead the transformation, Middle East innovators must lead the data movement Manual Data Collection Systems Integration Reporting and Analytics Reporting and Analytics Data Mining Predictions Predictions Machine Learning Augmented Intelligence Artificial Intelligence Use past knowledge to make rudimentary predictions about the future 

Data must lead the transformation, Middle East innovators must lead the data movement Manual Data Collection Systems Integration Reporting and Analytics Data Mining Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Finding known needles in haystacks and pop health TODAY, MAY SKIP FOR ML 

Data must lead the transformation, Middle East innovators must lead the data movement Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Augmented Intelligence Artificial Intelligence Semi autonomous intelligence which needs humans ARRIVING SOON 

Data must lead the transformation, Middle East innovators must lead the data movement Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Artificial Intelligence Real intelligence indistinguishable from humans and fully autonomous YEARS AWAY 

Data ushering in Scientific Method 3.0 and the Middle East can lead it again 1.0 Identify phenomenon Identify phenomenon Think about nature Think about nature Fit to known patterns Fit to known patterns Guess at answers Guess at answers 3.0 Identify data Identify data Generate questions Generate questions Mine data Mine data Answer questions Answer questions 2.0 Identify problem Identify problem Ask questions Ask questions Collect data Collect data Answer questions Answer questions 

How will we know if we’ve reached 3.0 ? 

How will medical roles evolve or be eliminated? Find other opportunities within 2-3 years Clerical Focus on value- added tasks such as revenue growth or new business development within 3- 5 years Administrative •Learn data science •Seek digital imaging and digital pathology integration opportunities •Become telehealth native Early career clinical •Learn to teach computers •Become a digital transformation change agent / leader •Drive telehealth across the multiple institutions Mid career clinical • Learn to teach computers your wisdom • Ignore the transformation and retire early Late career clinical 

Where Middle East innovators and investors should focus their attention with respect to digital medicine Therapies Therapeutic Tools Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Cohort specific Personalized Risk Data Sharing Most regulated Least regulated in USA More difficult to compete with the USA Easier to compete 

Where Middle East innovators and investors should focus their attention with respect to digital medicine Therapies Therapeutic Tools Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Auto Literature Review Specialty-specific Content Most regulated Least regulated in USA More difficult to compete with the USA Easier to compete 

Where Middle East innovators and investors should focus their attention with respect to digital medicine Therapies Therapeutic Tools Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Auto Adjudication Fraud Detection Quality Compliance Contract Adherence Most regulated Least regulated in USA More difficult to compete with the USA Easier to compete 

Where Middle East innovators and investors should focus their attention with respect to digital medicine Therapies Therapeutic Tools Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Patient Self Diagnostics Unlicensed Pro Diagnostics Digitally and Heuristically Guided Diagnostics Images (self, guided, consulted) Labs and Chemistry (self, guided, consulted) Multi-omics (self, guided, consulted) Molecular Biology Most regulated Least regulated in USA More difficult to compete with the USA Easier to compete 

Where Middle East innovators and investors should focus their attention with respect to digital medicine Therapies Therapeutic Tools Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Auto Triage for Low-risk Augmented Triage for Higher risk Infection control / Anti-microbial Stewardship Consulted Tele Diagnostics Med Device Continuous Diagnostics Most regulated Least regulated in USA More difficult to compete with the USA Easier to compete 

Where Middle East innovators and investors should focus their attention with respect to digital medicine Therapies Therapeutic Tools Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Physical Mental (chat, VR, etc.) Digital (nutritional, etc.) Clinical Research ( “systematic review automation”) Drug Development Clinical Discovery (unattended and digital) Most regulated Least regulated in USA More difficult to compete with the USA Easier to compete 

Where Middle East innovators and investors should focus their attention with respect to data Proteomics Genomics Biochemical Imaging Behavioral Phenotypics Admin Economics Connectivity Integration Transformation Comprehension Enrichment Insights Cognition No outcomes driven medicine possible without these 

How should machines go through medical training? Which medical school will have the first machine learning algorithm training department? 

HOW DO YOU PREPARE DIGITAL- READY LEADERS? L v = (i)K c + (v)S PJ + C2 + (a)T i 2 + R PFU + E(wo) 

Here’s the formula that create the right leaders Lv → Leadership value = (target a large number greater than 1) • Kc → inquisitive knowledge of industry led by curiosity about why things are the way they are + • Spj → visionary strategy informed by problems to be solved and jobs to be done + • C2 → communication & coordination + • (a)Ti 2 → application of actionable transformative technology fully integrated into complex workflows + • Rpfu → understanding performance, financial, and utilization risk (shared, one-sided, two-sided) • Ewo → execution through workforce optimization • SQ → status quo is a constant, the size of which depends upon your organization. It means do no harm, focus on patient safety, reliability, intermediation, & maintain eminence and consensus based decision making Lv = SQ Kc + Spj + C2 + (a)Ti 2 + Rpfu + Ewo 

www.himssqatar.org How will innovation in digital medicine and biomedicine affect the future of healthcare? By Shahid N. Shah Health Futurist and Healthcare IT Entrepreneur Publisher, Netspective Media LLC This and many of my other presentations are available at www.SpeakerDeck.com/shah @ShahidNShah [email protected] www.ShahidShah.com