DHIN Summer Summit, Finding the Humans in Health IT
A landscape review of what HHS, ONC, and other gov't agencies are focused on vs. what the health IT industry is working on and how ML, AI fit into the overall picture.
on answering these questions? • Should we go into at-risk (downside, too not just upside) contracts? Is the uncertainty tolerable? • Will our current pricing allow us to maintain the margins necessary for us to stay in business? • Can we bear the scrutiny of pricing transparency? THIS IS THE HARD STUFF! @ShahidNShah
Health IT create “interruptions at scale”? AI / ML / Telemedicine / Messaging creates significant opportunity for increased unnecessary interruptions if not properly designed for multiple stakeholder workflows @ShahidNShah
goals of health IT should be to increase patient education, answer questions in a timely manner, improve patient outcomes, reduce patients’ administrative burdens, and increase staff productivity by allowing staff to focus on the neediest patients. @ShahidNShah
we move from “institution first” to “patient first” or “patient centered” health IT? Hint: it’s not about patient engagement. It’s about transparency and outcomes. @ShahidNShah
Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Docs and nurses as clerical staff TODAY
Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence PGHD, Med Device Connectivity TODAY, ACCELERATING
Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Pattern matching mastery (unsupervised and supervised)
Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Use past knowledge to make rudimentary predictions about the future
Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Finding known needles in haystacks and pop health TODAY, MAY SKIP FOR ML
Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Semi autonomous intelligence which needs humans ARRIVING SOON
Manual Data Collection Systems Integration Reporting and Analytics Data Mining Predictions Machine Learning Augmented Intelligence Artificial Intelligence Real intelligence indistinguishable from humans and fully autonomous YEARS AWAY
Think about nature Fit to known patterns Guess at answers 3.0 Identify data Generate questions Mine data Answer questions 2.0 Identify problem Ask questions Collect data Answer questions
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
Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Most Regulation Least Regulation Cohort specific Personalized Risk Data Sharing
Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Most Regulation Least Regulation Auto Literature Review Specialty-specific Content
Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Most Regulation Least Regulation Auto Adjudication Fraud Detection Quality Compliance Contract Adherence
Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Most Regulation Least Regulation Auto Triage for Low-risk Augmented Triage for Higher risk Infection control / Anti-microbial Stewardship Consulted Tele Diagnostics Med Device Continuous Diagnostics
Diagnostics Diagnostic Tools Patient Administration Payer Admin Clinical Professional Education Public Health Education Patient Education Most Regulation Least Regulation Physical Mental (chat, VR, etc.) Digital (nutritional, etc.) Clinical Research ( “systematic review automation”) Drug Development Clinical Discovery (unattended and digital)
Imaging Behavioral Phenotypics Admin Economics Connectivity Integration Transformation Comprehension Enrichment Insights Cognition No ML or AI possible without these
Shahid N. Shah
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