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Targeted Injury Detection System Targeted Injury Detection System for Adverse Drug Events: An AHRQ-for Adverse Drug Events: An AHRQ-
Funded Patient Safety InitiativeFunded Patient Safety Initiative
TIDS-ADETIDS-ADE
The Quality ColloquiumThe Quality Colloquium
August 20, 2008August 20, 2008
Andrew Masica, MD, MSCIAndrew Masica, MD, MSCIBaylor Health Care System-Dallas, TXBaylor Health Care System-Dallas, TX
TIDS-ADE BackgroundTIDS-ADE Background
• Trigger tool methodology
focused mechanism for risk reductionevent precipitates a responseExample: IHI
• Adverse drug events
common/costlyusually actionableclinical/IT interface
Project GoalsProject Goals
• Develop a functional trigger tool for ADEs in hospitalized patients that can be disseminated broadly
• Detection at multiple time points related to event occurrence (before, during, or after)
• Potential benefits in clinical care setting:1. Prevention of ADEs2. Mitigation of ongoing ADEs3. Capture of “true” ADE rate
• Toolkit for real-world implementation
DefinitionsDefinitions
• Trigger = alert: any event prompting further investigation by clinician.
• ADE criteria = if event attributed to drug and:
reaches a level of harm that is durable or
requires a change in the treatment plan due to unacceptable level of risk for harm or patient discomfort
• Example of “unacceptable risk” for patient harm:-INR -INR ≥ 6.0 and active warfarin order≥ 6.0 and active warfarin order-event prompted discontinuation of drug=ADE
• Broader concept of ADEs Broader concept of ADEs
Organizational StructureOrganizational Structure
Coordinating Center
RTI Conference Calls AHRQ In-person meetings
Site leads
Local Test Site
• Pharmacy champion
• Pharmacy IT
• Pharmacy Staff
Site System Leadership
• Patient Safety
• Health Care Improvement
• Project champion -oversight -data management
Implementation: Site EnvironmentsImplementation: Site Environments
• Site leader meetings
• Activation of IT/programming resources
• Project introduction to site staff
• Validation of triggers
• Launch
• 3-9 months prior to start
• 2-6 months prior to start
• 1-4 months prior to start
• 4-6 weeks prior to start
• Begin pilot
Task Timing
Implementation: TriggersImplementation: Triggers
• Choice/set-up of triggers:
higher yield alerts (Classen, Evans JAMA 1991)
core set of 1520 consensus, tiered TIDS alerts
tailoring to local site capabilities/priorities
• Trigger validation steps (3-phases):
programmer’s bank of “dummy data”
real-time pre-launch tests by site IT pharmacist
post-launch troubleshooting for obvious “misses”
• Uniform process for evaluating trigger utility
TIDS-ADE WorkflowTIDS-ADE Workflow
Alert Work List
Patient ID
Date/location
Trigger details
Triage
Alert Review
Chart
Patient
Intervention
Trigger Evaluation
Respond to ?’s
Data Warehouse
Biweekly meetings
Central Pharmacy Floor Virtual
15 minutes 1-2 minutes (review) 1-2 minutes
1 minute (response)
Per alert
ResultsResults††
Alert # Times Fired % Patients (N=4171)* K+<3.4 and K+ reducer 85 2.0 K+>5.5 and K+ raiser 60 1.4 INR >3 and active warfarin 51 1.2 PTT > 100 and heparin 28 0.7 Platelets < 100 and platelet reducer 10 0.2 Platelets <50 and platelet inhibitor 9 0.2 K+<3.2 and digoxin 6 0.1 Creatinine >133% of previous 5 0.1 Digoxin level >2.5 4 0.1 Mg2+ < 0.75 and digoxin 0 0 Total 258 6.2% *8 week study period. Data from Providence Health Care System.
Test site average: 5-10 alerts per 100 patient days
†Preliminary data from alpha-site testing
Trigger EvaluationTrigger Evaluation
Was the alert useful?
3 Site Total Baylor GRVAlert useful # Alerts % Useful # Alerts % Useful
Bleed-1 123 14 7 29
Bleed-1b 53 17 53 17
C diff-1 49 8 49 8
Creatinine-1 6 0 0 .
Digoxin related-1 20 20 13 23
Hyperkalemia-1 15 0 15 0
Hyperkalemia-2 18 11 12 0
Hypoglycemia-1 2 0 0 .
Hypoglycemia-2 41 12 23 0
Hypokalemia-1 496 7 111 15
Hypokalemia-2 48 10 11 18
Hypotension-1 16 31 0 .
Hypotension-2 2 0 0 .
Platelets-1 1 0 0 .
Platelets-2 13 23 6 17
Rash-2 30 0 30 0
Renal clearance-1 76 22 75 23
Renal clearance-2 82 20 21 29
Trigger EvaluationTrigger Evaluation
Did the alert detect an adverse event or trend?3 Site Total Baylor GRV
Adverse event # Alerts % AE # Alerts % AE
Bleed-1 123 15 7 29
Bleed-1b 53 17 53 17
C diff-1 49 8 49 8
Creatinine-1 6 0 0 .
Digoxin related-1 20 20 13 23
Hyperkalemia-1 15 0 15 0
Hyperkalemia-2 25 48 12 0
Hypoglycemia-1 2 0 0 .Hypoglycemia-2 41 12 23 0
Hypokalemia-1 496 7 111 15
Hypokalemia-2 56 23 11 18
Hypotension-1 16 31 0 .Hypotension-2 2 0 0 .
Platelets-1 1 0 0 .Platelets-2 13 23 6 17
Rash-2 30 0 30 0
Renal clearance-1 76 22 75 23Renal clearance-2 82 20 21 29
Trigger EvaluationTrigger Evaluation
3 Site Total Baylor GRVPrompt change # Alerts % Changed # Alerts % Changed
Bleed-1 123 12 7 29
Bleed-1b 53 13 53 13
C diff-1 49 0 49 0
Creatinine-1 6 0 0 .
Digoxin related-1 20 10 13 8
Hyperkalemia-1 15 0 15 0
Hyperkalemia-2 18 11 12 0
Hypoglycemia-1 2 0 0 .
Hypoglycemia-2 41 10 23 0
Hypokalemia-1 496 5 111 5
Hypokalemia-2 48 8 11 9
Hypotension-1 16 19 0 .
Hypotension-2 2 0 0 .
Platelets-1 1 0 0 .Platelets-2 13 23 6 17
Rash-2 30 0 30 0
Renal clearance-1 76 18 75 19
Renal clearance-2 82 10 21 24
Did the alert change patient care?
Trigger evaluationTrigger evaluation
Did a drug cause the adverse event or trend?3 Site Total Baylor GRVDrug cause # Alerts % drug cause # Alerts % drug cause
Bleed-1 123 15 7 29Bleed-1b 53 13 53 13C diff-1 49 0 49 0
Creatinine-1 6 0 0 .Digoxin related-1 20 10 13 8
Hyperkalemia-1 15 0 15 0
Hyperkalemia-2 25 8 12 0
Hypoglycemia-1 2 0 0 .
Hypoglycemia-2 41 10 23 0
Hypokalemia-1 496 5 111 5Hypokalemia-2 56 5 11 9Hypotension-1 16 31 0 .Hypotension-2 2 0 0 .
Platelets-1 1 0 0 .Platelets-2 13 23 6 17
Rash-2 30 0 30 0
Renal clearance-1 76 18 75 19
Renal clearance-2 82 16 21 24
TIDS-ADE: Trigger SummaryTIDS-ADE: Trigger Summary
3 Site Totals Alerts % Useful % Changed % Adverse % Drug
Bleed-1 123 14 12 15 15
Bleed-1b 53 17 13 17 13
C diff-1 49 8 0 8 0
Creatinine-1 6 0 0 0 0
Digoxin related-1 20 20 10 20 10
Hyperkalemia-1 15 0 0 0 0
Hyperkalemia-2 18 11 11 48 8
Hypoglycemia-1 2 0 0 0 0
Hypoglycemia-2 41 12 10 12 10
Hypokalemia-1 496 7 5 7 5
Hypokalemia-2 48 10 8 23 5
Hypotension-1 16 31 19 31 31
Hypotension-2 2 0 0 0 0
Platelets-1 1 0 0 0 0
Platelets-2 13 23 23 23 23
Rash-2 30 0 0 0 0
Renal clearance-1 76 22 18 22 18
Renal clearance-2 82 20 10 20 16
Results can guide refinement of alerts.
Impact on ADE Detection ratesImpact on ADE Detection rates
• Expanded definition of ADEs for project:patient harm or unacceptable risk for patient harm
• TIDS Alerts considered to have detected an ADE if:alert detected an adverse event or trendadverse event or trend was caused by a drug
Baylor Grapevine Baylor Grapevine • >40 cases meeting both conditions over 10 weeks
• Approximately 4-5 ADEs detected per week with TIDS2.3 ADEs per 100 admissions
• Voluntary reporting: <0.5 ADEs per 100 admissions
Lower ADE rate at Baylor?Lower ADE rate at Baylor?
• Sites in published literature: 3-6 ADEs per 100 admissionsacademic centers/training programsmature EHRs/CPOEexperience with trigger tool methodology
vs.vs.• Community setting
paper based with varying degrees of IT supportstaffing limitationsacceptance of trigger approach to ADEs
verification process can be difficult
Additional OutcomesAdditional Outcomes
• Qualitative Feedback
level of detail in alert felt to be beneficial
favorable view of alerts with trending
evaluation piece undermined perceived usefulness
sharp learning curve
fits well into existing practice patterns
• Quantitative
80 hours of programming time for study triggers
45 minutes pharmacist time daily
• High risk situations can be captured prospectively with use of a trigger tool
• Need to resource multi-site collaboration
general framework for implementation
• Outcomes are influenced by site characteristicsperformance of specific triggers
ADE detection rate
• Dynamic evaluation process for alerts is criticaloptimizes performance of the triggering system
reduction in alert fatigue
Lessons learned from TIDS-ADELessons learned from TIDS-ADE
TIDS-ADE: Future DirectionsTIDS-ADE: Future Directions
• Full analysis/toolkit development in progress
• Incorporation of broader ADE definition into daily patient care
• Clarify endpoints for “successful” triggers
• Cross-cutting projectrealistic planning for resource allocations
TIDS-ADE Leaders/Sites…thanks to all!TIDS-ADE Leaders/Sites…thanks to all!
Michael Harrison, PhD AHRQ
Jim Battles, PhD AHRQ
Amy Helwig, MD, MS AHRQ
Shula Bernard, RN, PhD* RTI
Jonathan Nebeker, MD, MS† University of Utah/VA
Scott Evans, MS, PhD Intermountain
Brent James, MD, MS Intermountain
Bruce Bayley, PhD Providence Health Care
Steve Pickette, PharmD, BCPS Providence Health Care
Howard Peckman, PharmD UNC-Chapel Hill
Baylor Grapevine Pharmacy Staff Baylor Health Care
Andrew Masica, MD, MSCI Baylor Health Care
*Principal Investigator; †Senior Scientist