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Process Redesign, Implementation and Impact Analysis

Process Redesign, Implementation and Impact Analysis. Director of Informatics Department of Emergency Medicine Boston University School of Medicine Co-chair, Emergency Care Special Interest Group Health Level 7 Immediate Past Chair Section of Emergency Medical Informatics

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Process Redesign, Implementation and Impact Analysis

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  1. Process Redesign, Implementation and Impact Analysis Director of Informatics Department of Emergency Medicine Boston University School of Medicine Co-chair, Emergency Care Special Interest Group Health Level 7 Immediate Past Chair Section of Emergency Medical Informatics American College of Emergency Medicine Todd Rothenhaus, MD FACEP

  2. Boston Medical Center • Level 1 Trauma Center • 127,000 annual visits • 38 full time attendings and NPs • >200 rotating house staff per year • >150 full time RN staff • 5 geographically separate locations

  3. The Emergency Department • People • Architecture • Communication

  4. Health Care “Deliverables” • Medications • Procedures • Education

  5. ED IT Adopters • “Well Tuned” Emergency Department • Disaster Area • Begging HIS to computerize • CPOE Victim • Reluctant Adopter • Homegrown Developer

  6. The Perfect EHR • Simplicity • Flexibility • Elasticity • Invisibility

  7. Basic ED workflow

  8. Basic ED workflows • Most “variable” workflows • Triage • Discharge • Patient Entry • 1 versus 2 step triage • Meet/greet • Full versus variable/minimal triage • 5 level triage (CDS) • Triage directly to a room • Bedside registration

  9. ED Workflow Ideas • Patients brought directly to the treatment area get a different kind of triage than patients who wait. • “Uncouple” triage and RN care. • Roll out EDIS to supporting departments • Registration • Admitting • Housekeeping • Radiology

  10. loose coupling • Coupling is the dependency between interacting systems. This dependency can be decomposed into real and artificial dependency: • Real dependency is the set of features or services that a system consumes from another system. Real dependency always exists and cannot be reduced. • Artificial dependency is the set of factors that a system has to comply with in order to consume the features or services provided by other systems. Artificial dependency always exists, but it or its cost can be reduced. • Loose coupling describes the configuration in which artificial dependency has been reduced to the minimum.

  11. EDIS Evaluation • Grid/RFP • Use Case Scenarios • EHR Functionality Requirements and Conformance Criteria (CCHIT)

  12. Use Case Actors Roles in the ED Triage RN, Primary RN, Physician, Tech, Transport, etc. Roles in the EDIS

  13. Potential Use Case Scenarios • A 64 year old trauma patient on 6 medications and with extensive PMH presents to the ED. He needs plain x-rays, a full body CT, morphine, tetanus, and Ancef (entry  orders sent). • A 19 year old girl with an ankle sprain presents to fast track and is sent to x-ray prior to being seen by a physician (entry  orders sent). • A 63 year old man is admitted to the ward for nausea an vomiting. He is found to have a positive troponin and his admission is changed to telemetry (disposition  departure). • A patient’s primary care physician calls the ED looking to find out what happened to a patient seen yesterday. He wants no know what was done and where the patient was admitted (patient lookup and chart evaluation). • A patient seen with a resident or PA is discharged. The attending physician wants to review her charts for the day, read the note, write a note, sign the chart, and send the chart to billing (chart workflow).

  14. EDIS Reports • Legacy data • System generated reports • Data mining the back end

  15. How is data captured • “Active” tracking vs. “passive” tracking • “Gaming” the system

  16. How (not) to Lie with EDIS Statistics • The best • Overall LOS • Waiting time • The worst • Time to be seen by MD • Disposition to departure

  17. Profiling and benchmarking • Physician statistics • Patients per hour • RN statistics • Patient-hours per hour

  18. Summary • Small changes in workflow can substantially perturb ED operations • Implementations take much longer to recover from that you think

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