Bridging the GapEmpowering Caregivers With Real Time Access to Aggregate Patient Safety Data

Jeffrey M. Ferranti, MD, MSDirector, Computerized Patient Safety Initiatives

Director, Enterprise Data WarehouseDuke University Health System

The Recent IOM Report

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

• 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

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

TechnologyO

perations

• 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

Error Monitoring at Duke A Multi Faceted Approach

The Qualitative Approach Voluntary Safety Reporting System (SRS)

• 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

Error Monitoring at Duke A Multi Faceted Approach

The Quantitative Approach Computerized ADE Surveillance

Daily

Reports

ADE

Database

Event Report Generator CDR

LabPharmacy

ADT Orders

Phar

mac

ist R

evie

w

Possible ADEs to Pharmacist for Review

Naranjo

SI

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

• Predictive Analytics

Bridging the GapDuke’s Strategy for Operationalizing Safety Data

OLAP Processing / Data Exploration

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

• Predictive Analytics

Bridging the GapDuke’s Strategy for Operationalizing Safety Data

ADE-S / SRS Trend Report for Narcotics

Transition Period / Surveillance Data

Unavailable

63,033 Total PatientsExposed to Narcotics

322 Narcotic ADEs SI>=3

Patient AgePatient LOSPatient GenderClinical ServiceMorphine (Y/N)Fentanyl (Y/N)Midazalam (Y/N)Etc …

Six Sigma Opiate Pilot Project Develop a Predicative Risk Model

LOS > 4 DaysAge > 51FentanylFluoxetine

63,033

322 Narcotic ADEs SI>=3

LOS > 4 DaysAge > 51FentanylScopolamine

Thoracic SurgeryAny NarcoticSertralineMidazolam

Six Sigma Opiate Pilot Project Develop a Predictive Risk Model

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

Six Sigma Opiate Project Develop a Predictive Risk Model

LOS > 4 DaysAge > 51FentanylFluoxetine

Acute Pain Consults

Frequent Re-Assessment

Increased Monitoring

Pharmacy Consults

Clinical Information is an Enterprise Asset

Questions