Process Redesign, Implementation and Impact Analysis

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Process Redesign, Implementation and Impact
Analysis

• Todd Rothenhaus, MD FACEP

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
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Boston Medical Center

• Level 1 Trauma Center
• 127,000 annual visits
• 38 full time attendings and NPs
• gt200 rotating house staff per year
• gt150 full time RN staff
• 5 geographically separate locations

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The Emergency Department

• People
• Architecture
• Communication

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Health Care Deliverables

• Medications
• Procedures
• Education

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ED IT Adopters

• Well Tuned Emergency Department
• Disaster Area
• Begging HIS to computerize
• CPOE Victim
• Reluctant Adopter
• Homegrown Developer

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The Perfect EHR

• Simplicity
• Flexibility
• Elasticity
• Invisibility

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Basic ED workflow
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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

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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

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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.

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EDIS Evaluation

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

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Use Case Actors

• Roles in the ED
• Triage RN, Primary RN, Physician, Tech,
  Transport, etc.
• Roles in the EDIS

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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 patients 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).

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EDIS Reports

• Legacy data
• System generated reports
• Data mining the back end

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How is data captured

• Active tracking vs. passive tracking
• Gaming the system

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How (not) to Lie with EDIS Statistics

• The best
• Overall LOS
• Waiting time
• The worst
• Time to be seen by MD
• Disposition to departure

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Profiling and benchmarking

• Physician statistics
• Patients per hour
• RN statistics
• Patient-hours per hour

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Summary

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