Transcript Slide 1

University of Pennsylvania Health System
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Three urban hospitals
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Medical school & residency training
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Sub-specialty practices
Primary care network
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Urban & suburban offices
Disease management
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Extensive rules-based algorithms
Electronic Medical Record
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Penn wanted a platform to integrate the
health system with sufficient data capability
to support disease management
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Free text vs discrete data
Discrete data is searchable and can trigger
real-time provider alerts
Epic is preferred product for large integrated
health systems distributed across extensive
geographic regions
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Early Implementation
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Minimize impact on productivity
EMR sought to emulate paperwork flow
Gradual introduction
UPHS retreated from Disease Management
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Early 2000s new Epic roll outs were halted
Continued to provide support for the
practices already on Epic
We had six years “on our own” to refine our
use of the product
Observe physicians before and after
Habits don’t change!
Scanning
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Paper first
Provider sees results on paper and report is
scanned after clinical action has taken place.
Scan first
Result is scanned on same day
Provider sees results electronically
Built-in quality control
UPHS Recommitted to EMR
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2006 new roll outs resumed
Slow at first “Don’t damage productivity”
Later conclusion: Faster is better
“Steeper learning curve gets to ROI sooner”
Instead of trying to emulate every paperwork flow,
teach an electronic process that already works
elsewhere
Allow practices to modify after they are up and
running
Abstraction
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Problem list
Medication list
Immunizations
Cancer screening
GIGO: legibility & completeness of paper
record requires attention before Go Live
Health Maintenance - Basic
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Colonoscopy
Mammography
Pap smear
PSA
Lipid screening
Immunizations
Health Maintenance - Advanced
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Disease specific monitoring
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Diabetes
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Criteria are added automatically based on Dx
Patient lists
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Population management
Allows one to track a group of patients based on clinical
parameters
Meaningful Use
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E-prescribing
Electronic lab
Clinical summaries
Quality measures
E-prescribing
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Electronic transmission
Formulary compliance – real time
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Rx hub
Electronic Lab
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Place order from within EMR
Receive results back in EMR
Trend and graph results
Discrete data triggers health maintenance
Quality Metrics
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Completed documentation
Review of test results
Structured documentation of patient medications
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Med reconciliation
Problem list
Vital signs
Medicare screening questions
Allergies
Clinical history documented in standard location
Health maintenance
Lessons Learned
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Paper chart prep before go live enables
higher quality abstraction
Rapid implementation puts pain up front but
leads to faster turn around
Discrete data is what powers EMR
Lean charting is the goal
Best practice documentation metrics may
encourage meaningful use