Presentation for mHealth Israel by Dr. David Allard, Chief Medical Information Officer, Henry Ford Health System. The lecture discusses why EMRs lag other innovations in Healthcare and other industries. David then proposes an approach to innovation and examines common issues with which CMIOs contend. He finishes with a few successful case studies.

1. EMR Innovation
R. David Allard, MD
Chief Medical Information Officer
Henry Ford Health System
mHealth Israel: January 10, 2018

2. Goals
 Discuss Why EMRs lag other innovation in Healthcare and other industries
 Propose an approach to innovation
 Discuss common issues with which CMIOs contend
 Give a few examples of why there is hope

4. Medicine is the Highest Tech Low Tech Industry
 Care techniques are advancing at a phenomenal
rate
– Gamma knife
– Precision Medicine
– DaVinci Surgery
– Et Cetera
 The mechanisms we use to learn about these best
practices and deliver the techniques have
changed very slowly with healthcare and medicine
still acting like a cottage industry

5. Cottage Industry vs. Standards Driven High Reliability
Industry
Cottage Industry
 Emphasis on craftsmanship
– Great doctor/provider
– “Centers of Excellence”
 Highly individualized care
 Highly variable in cost and outcome
 Optimized for the craftsman
 Hard to measure or predict outcomes levels
Standards Driven Industry
 Emphasis on process and reliability
– Create processes that anyone (within reason) can do
 Consistency, highly reliable
 Transparency
 Optimized for the end recipient
– (consider the airline industry)

6. Medicine is the Highest Tech Low Tech Industry
 13% of physicians in the USA are still on paper
charts in 20171
 53% of practices describe their EMR as “basic”
 83% of residential care communities are on paper
(2010)
 32% of EHRs can exchange information with other
provider’s systems (2014)
1https://www.cdc.gov/nchs/fastats/electronic-medical-records.htm

7. Medical Education and Dissemination of Clinical
Innovation
Today
 Medical Student learns from
Senior Providers…
 Becomes a Resident who goes to
a new place to learn and get
experience…
 Sets up a practice as a senior
provider and (sometimes) trains
new medical students
Ca. 650 AD
 Apprentice Learns from a
Master…
 Becomes a Journeyman who
travels to learn more and get
experience…
 Sets up as new master, practices
and starts training new apprentices

8. Why is This a Problem?
 CMIO Lie #1 – Medicine is becoming a retail business
 Is medicine a service industry or a consulting industry at its heart?
– Service industry
• We certainly do things to and for people
• The literature is full of articles about the retailization of healthcare
– Consulting industry
• At the core of Medicine is knowing what to do
• Population Health, Big data, machine learning,
• The management of information such that it is represented of knowledge and applying that
knowledge to benefit the health of populations and individual patients
Bytes → Data → Information → Knowledge → Wisdom

9. Back to the antiquated system of sharing best
practices and innovation
Today
 Medical Student learns from
Senior Providers…
 Becomes a Resident who goes to
a new place to learn and get
experience…
 Sets up a practice as a senior
provider and (sometimes) trains
new medical students
Ca. 650 AD
 Apprentice Learns from a
Master…
 Becomes a Journeyman who
travels to learn more and get
experience…
 Sets up as new master, practices
and starts training new apprentices

10. If the Core of Medicine is Knowledge Management,
Why Has That Been So Slow to Change?
 Technology capability
– Medical Records are more than a database –
• Innovation requires facilitated workflow – implies standardization, connectivity, data standards
• Information should feed Clinical Decision Support
 Technology availability
– The cost of devices to all required users was prohibitive
 Technology Utility
– Are there changes in outcomes to justify the cost (both IT cost and human cost?)

11. Why is EMR Innovation happening now?
Ca. 1800 New England Pre-Industrial
Revolution
 Demand exceeds supply
 Quality enormously variable given
the “cottage industry” state of the
operations
 New technology enabling greater
supply and services with greater
standardization
US Statistics
 In 2016, median age is 37.9 years
– 29.5 in 1960
 In 2016, total USA population 326.4 M
– 179.3 M in 1960
 In 2016, Healthcare spending per
capita $10,345
– $146 in 1960
 In 2007, physicians/1000 2.4
– About 1 in 1960
Source: www.census.gov

12. Why is EMR Innovation Happening Now?
 Changes in the support for the hierarchy of information - EMR Utility catching
up to the needs of a knowledge based industry
– Better connectivity with sources of information – more availability of data
• Monitoring device integration with IT systems, wearables, HIEs
– Better codified standards to turn data into information
– Better reporting and data manipulation to turn information into better representations of
reality (knowledge)
• Better graphing and visualization tools
– More availability of digitized algorithms for clinical decision support – digital wisdom
• Guideline clearinghouses beginning to be codified

13. So Why do Doctors Hate EMRs?

14. So Why Do Doctors Hate EMRs
 Data Entry is burdensome
 New capabilities have created new work streams
– Regulatory requirements
– Expansion of the patient visit
– Incorporation of more data sources
 Redistribution of work
 Clerical perspective of the EMR
– Providers rarely view EMRs as a clinical competency – neither does almost anyone
else - but I would argue it is

15. Organization focus in change and innovation
 CMIO Lie #2 – We want to be on the cutting edge of technology
 Organizations must decide who they want to be from a digital standpoint (and
other innovations as well)
– Disruption
– Leading as a key differentiator
– Early adopter or follower
– Trailer
 Is technology who we are or a tool we use?

16. Organization Focus in Change – More Ideas Than
Time
 Device integration
 Data Mining
 New EMR modules
 Machine learning
 Enabling best practices (screening, risk scoring etc)
 Supply chain management
 Interaction with regulatory agencies
 Decision support tools
 Patient communication tools

17. Organization focus in change and innovation
 Problems with leading innovation/disruption
– Higher risk
– Labor intensive, iterative work
– Opportunity cost
– May require a high focus in a small area of change
– May be difficult to scale
 Most organization want to be leaders or adopters –
– Allows scalability
– Predictability of future state

18. Value of a change based on many domains
Domains of Value
 Safety and Quality
 User Experience
 Patient Experience
 System Stability
 ROI
 Information Portability
 Regulatory Compliance
Domain relationships
 Improving one area often leads to a
degradation in another
 The Net Total Experience needs to
be positive
 Projects need to coexist peacefully
and productively

19. Innovation in using tools vs. Innovation in making
more tools
New Tools
 May be easier to control or
customize
 Often more industry friendly since
each may represent separate
products
 Creates new integration challenges
from data to scale to workflow
Using tools in new ways
 More integrated but harder to build
 Less highly customized to a specific
use case
 Usually more cost controlled
 Often more scalable

20. Desirable Projects
 Highly defined scope
 Specific goals related to organizational strategy
 Fits into the landscape of the organization
 Includes longer term support and planning

21. Approach to Innovation
 Workflow integration
– Avoid creating separate parallel work streams
– Designs that are accessed when a clinician is already thinking about that patient
and – even better- that aspect of a patient
 Recognize the skills of the team
– Have all members of a team operate to the top of their abilities
 Data presentation
– Vetter visualization and digestion of data
– Data → information → knowledge → wisdom
 Pay attention to User interfaces – simple and in line with other work
 Pay attention to scalability -

22. Reasons for Hope
 Video visits from providers to
smart phones
 Real time delivery of patient
results – increasing patient
partnership in care
 Wearable monitors populating
EMR data
 Consolidating data from
multiple health systems
 Big data use in
–Sepsis prediction
–Readmission risk
–Assessing social determinants of
care
 Decision Support
–Better imaging test ordering
–Drug-drug and drug-disease
interaction