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The Healthcare of
Tomorrow
Douglas Fahlbusch
Perioperative Healthcare Consulting, 2018
MIGA Key Opinion Leaders Dinners
The Past …
The Present …
The Future …
Healthcare today
DiseaseCare. What are the drivers?
Cover Credit: DENNIS CHALKIN, 1991
Healthcare Costs
Societal Demands
Reductionist thinking
Burnout Epidemic
* *
Future Tools
Machine Learning
Today
Machine Learning => Intelligence
What the ??
Tomorrow
Connectednes
s
http://smallbizclub.com/technology/hardware/employ-internet-things-business/
Wearable
Sensors
Wellness Apps
Digital Exhaust
/indiancountrymedianetwork.com/culture/health-wellness/diabetes-research-strikes-gold-with-a-graphene-
//www.linkedin.com/pulse/20140818165857-16808-wearable-sensors-are-the-future-of-personalized-medi
Supply Chain
Genomics
Telehealth & AR/ VR
https://www.silverchain.org.au/innovation/what-is-emmr/
Future Trends
“Those who have knowledge, don't predict.
Those who predict, don't have knowledge.”
Lao Tzu C4 BC
Centre of Health
Predictive Analytics/ AI
AI. Ethics.
https://youtu.be/ejczMs6b1Q4?t=11
Healthcare Roles
Clinical-Admin Collaborative
The Future …
Douglas
Fahlbusch
www.douglasfahlbusch.com
drfahlbusch@perioperative.com.au
admin@perioperative.com.au
www.perioperative.com.au
Perioperative Healthcare
Consulting

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Notes de l'éditeur

  1. “Prediction is very difficult, especially if it's about the future.” Niels Bohr 1885-1962
  2. Doctors & Hospitals Healthcare 1000’s yrs Prof Mx 100
  3. Public v Private Admin v Clinical Sub-speciality v sub-speciality Me anaesthesia 15 yrs, doctor 25
  4. Cultural/ behavioural obstruction to updating accepted practice
  5. Look at the past to see the future Scarce resources Rewards volume DiseaseCare
  6. Aus 9% GDP, US 18% … 150B pa AUS, 20% waste – $30B p.a.
  7. Definition of Insanity – doing the same thing and expecting different results
  8. Dr Google: Pts arrive with lists of questions Google surgeons - pick the one with the 'best website' I’ve been a patient – cancer – healthcare is difficult to navigate – what is it like for ‘normal’ patients
  9. Me -> GDM, GAICD Realisation that: - What we do only affects 20% of outcomes! - There are a whole lot of factors we could manipulate, but we don’t know how to Frustration with just in time admissions – poor data
  10. eg: CHF relapse - not taking night diuretic bc ‘inconvenient’
  11. Formed PHC to investigate/ tackle: Funding Societal demands Technology changes Non-clinical determinants of health Burnout epidemic
  12. Hunter-gather 1000’s years Agricultural 100’s Industrial generations Tech decades
  13. Hunter-gather 1000’s years Agricultural 100’s Industrial generations Tech decades
  14. Public ‘v’ private
  15. Detect at stage 0 - ‘Digital exhaust’ – my cancer
  16. Engaged, empowered, efficient staff know surgeon x wants zz, so hides it .. meanwhile not available to others, or restocked
  17. ‘antibiotics’ & immunisation for cancer Biome RNA transcription – altered expression based on environmental influences CRISPR: gene editing CAR-T: Immune reprogramming SCNT: cellular reprogramming
  18. Engaged, empowered, efficient
  19. Proactive continuous HealthCare vs Reactive Episodic Disease Care Assist transition from here to there: Strategy/ Governance Ethics, Data + Clinical Admin Collaboration
  20. Chris O’Brien Lifehouse - steps & sleep Predictive – diagnosis MI, COAD – cancer recovery – steps & sleep Family education readmissions: patient portal
  21. Connectedness of existing data; data warehouse Triage for surgeon referrals … ED … Trust: Robust, Secure, transparent Employment increases worldwide Solve JIT admissions - data prior
  22. Trust: Robust, Secure, transparent
  23. Engaged, empowered, efficient. Blurring public/ private lines Students: learning it as they go (from other industries) Need frameworks, not recipes App helping staff, patients, doctors
  24. Aetna 22.2 million medical members, 13.4 million dental members, 13.8 million pharmacy services members ~ 1.2 million health care professionals, .> 690,000 primary care doctors and specialists, > Over 5,700 hospitals Bought by CVS Health: Pharmacy - More than 246,000 colleagues across all 50 states, Washington, D.C., Puerto Rico and Brazil
  25. Engaged, empowered, efficient
  26. Exponential learning Data, Analytics, Therapeutic HC outside traditional/ non-clinical determinants of health Leverage domain knowledge from business and clinical teams Based around data & patients, not bricks and mortar (or public, or private)