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Bridging the Gap. Empowering Caregivers With Real Time Access to Aggregate Patient Safety Data. Jeffrey M. Ferranti, MD, MS Director, Computerized Patient Safety Initiatives Director, Enterprise Data Warehouse Duke University Health System. The Recent IOM Report.

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bridging the gap

Bridging the Gap

Empowering Caregivers With Real Time Access to Aggregate Patient Safety Data

Jeffrey M. Ferranti, MD, MS

Director, Computerized Patient Safety Initiatives

Director, Enterprise Data Warehouse

Duke University Health System

the recent iom report
The Recent IOM Report
  • Preventing Medication Errors (2006) 1
    • Employ error detection methodologies in all care settings
    • Assess the medication use process through active monitoring
    • Computerized detection of ADEs should complement voluntary reporting
  • “Health care systems should capture information on medication safety and use this information to improve the safety of their care delivery systems.”1

1. Institute of Medicine. Preventing Medication Errors: Quality Chasm Series. Washington, DC, National Academy Press, 2006.

utilizing data to facilitate safety and quality efforts
Utilizing Data To Facilitate Safety and Quality Efforts
  • IT Safety Systems
  • The Data Warehouse (DSR)
  • Business Intelligence Tools
  • Six Sigma Analytics
  • Performance Services
  • The Balanced Score Card
  • Patient Safety Office

Technology

Operations

slide4

Error Monitoring at DukeA Multi Faceted Approach

  • The Qualitative Approach  Safety Reporting (SRS)
    • Provides qualitative data that informs safety and quality initiatives
    • Recently upgraded to SRS 2.0 which standardizes the reporting process
    • Not a reliable metric.
  • The Quantitative Approach  ADE-S
    • Computerized detection of ADEs; Excellent Metric
    • Based on the gold standard of manual chart review
    • Standardized scoring system, published inter-rater reliability
slide6

Error Monitoring at DukeA Multi Faceted Approach

  • The Qualitative Approach  Safety Reporting (SRS)
    • Provides qualitative data that informs safety and quality initiatives
    • Recently upgraded to SRS 2.0 to facilitate front line reporting
    • Not a reliable metric.
  • The Quantitative Approach  ADE-S
    • Computerized detection of ADEs; Excellent Metric
    • Based on the gold standard of manual chart review
    • Standardized scoring system, published inter-rater reliability
slide7

The Quantitative ApproachComputerized ADE Surveillance

ADE

Database

Lab

Pharmacy

Naranjo

Pharmacist Review

ADT

Orders

SI

Event Report Generator

CDR

Kappa

Daily

Reports

Possible ADEs to Pharmacist for Review

slide8

Bridging the GapDuke’s Strategy for Operationalizing Safety Data

  • Empower caregivers with direct access to safety data (COGNOS)
  • Predictive Analytics
slide12

Bridging the GapDuke’s Strategy for Operationalizing Safety Data

  • Empower caregivers with direct access to safety data (COGNOS)
  • Predictive Analytics
ade s srs trend report for narcotics
ADE-S / SRS Trend Report for Narcotics

Transition Period / Surveillance Data Unavailable

slide14

Six Sigma Opiate Pilot ProjectDevelop a Predicative Risk Model

X

Y

63,033 Total Patients

Exposed to Narcotics

Patient Age

Patient LOS

Patient Gender

Clinical Service

Morphine (Y/N)

Fentanyl (Y/N)

Midazalam (Y/N)

Etc …

322 Narcotic ADEs SI>=3

slide15

Six Sigma Opiate Pilot ProjectDevelop a Predictive Risk Model

63,033

LOS > 4 Days

Age > 51

Fentanyl

Fluoxetine

322 Narcotic

ADEs SI>=3

0.5 % (1/200)

8.7 %

9.1 %

7.5 %

LOS > 4 Days

Age > 51

Fentanyl

Scopolamine

Thoracic Surgery

Any Narcotic

Sertraline

Midazolam

slide16

Six Sigma Opiate ProjectDevelop a Predictive Risk Model

LOS > 4 Days

Age > 51

Fentanyl

Fluoxetine

  • If we can predict who is at high risk we can target interventions more effectively

Acute Pain Consults

Increased Monitoring

9.1 %

Frequent Re-Assessment

Pharmacy Consults