Targeted Injury Detection System for Adverse Drug Events: An AHRQ- Funded Patient Safety Initiative TIDS-ADE The Quality Colloquium August 20, 2008 Andrew

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



• 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


Hypoglycemia-1 2 0 0 .

Hypoglycemia-2 41 12 23 0

Hypokalemia-1 496 7 111 15


Hypotension-1 16 31 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



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





Hypoglycemia-1 2 0 0 .Hypoglycemia-2 41 12 23 0



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


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












Rash-2 30 0 30 0



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





Hypokalemia-1 496 5 111 5Hypokalemia-2 56 5 11 9Hypotension-1 16 31 0 .Hypotension-2 2 0 0 .


Rash-2 30 0 30 0



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

Documents

Targeted Injury Detection System for Adverse Drug Events: An AHRQ- Funded Patient Safety Initiative TIDS-ADE The Quality Colloquium August 20, 2008 Andrew