University of Pennsylvania Health System Three urban hospitals Medical school & residency training Sub-specialty practices Primary care network Urban &

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Presentation transcript:

University of Pennsylvania Health System Three urban hospitals Medical school & residency training Sub-specialty practices Primary care network Urban & suburban offices Disease management Extensive rules-based algorithms

Electronic Medical Record Penn wanted a platform to integrate the health system with sufficient data capability to support disease management 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

Early Implementation Minimize impact on productivity EMR sought to emulate paperwork flow Gradual introduction

UPHS retreated from Disease Management 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 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 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 Problem list Medication list Immunizations Cancer screening GIGO: legibility & completeness of paper record requires attention before Go Live

Health Maintenance - Basic Colonoscopy Mammography Pap smear PSA Lipid screening Immunizations

Health Maintenance - Advanced Disease specific monitoring Diabetes Criteria are added automatically based on Dx Patient lists Population management Allows one to track a group of patients based on clinical parameters

Meaningful Use E-prescribing Electronic lab Clinical summaries Quality measures

E-prescribing Electronic transmission Formulary compliance – real time Rx hub

Electronic Lab Place order from within EMR Receive results back in EMR Trend and graph results Discrete data triggers health maintenance

Quality Metrics Completed documentation Review of test results Structured documentation of patient medications Med reconciliation Problem list Vital signs Medicare screening questions Allergies Clinical history documented in standard location Health maintenance

Lessons Learned 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