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Targeted Injury Detection System for Adverse Drug Events: An AHRQ-Funded Patient Safety Initiative. TIDS-ADE. The Quality Colloquium August 20, 2008 Andrew Masica, MD, MSCI Baylor Health Care System-Dallas, TX. TIDS-ADE Background. Trigger tool methodology

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targeted injury detection system for adverse drug events an ahrq funded patient safety initiative

Targeted Injury Detection System for Adverse Drug Events: An AHRQ-Funded Patient Safety Initiative

TIDS-ADE

The Quality ColloquiumAugust 20, 2008Andrew Masica, MD, MSCIBaylor Health Care System-Dallas, TX

tids ade background
TIDS-ADE Background
  • Trigger tool methodology

focused mechanism for risk reduction

event precipitates a response

Example: IHI

  • Adverse drug events

common/costly

usually actionable

clinical/IT interface

project goals
Project 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 ADEs

2. Mitigation of ongoing ADEs

3. Capture of “true” ADE rate

  • Toolkit for real-world implementation
definitions
Definitions
  • 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 ≥ 6.0 and active warfarin order

-event prompted discontinuation of drug=ADE

  • Broader concept of ADEs
organizational structure
Organizational Structure

Coordinating Center

RTIConference Calls

AHRQ In-person meetings

Site leads

  • Site System Leadership
  • Patient Safety
  • Health Care Improvement
  • Project champion
  • -oversight
  • -data management
  • Local Test Site
  • Pharmacy champion
  • Pharmacy IT
  • Pharmacy Staff
implementation 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

Implementation: Site Environments

Task

Timing

implementation triggers
Implementation: Triggers
  • Choice/set-up of triggers:

higher yield alerts (Classen, Evans JAMA 1991)

core set of 1520 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
slide8

TIDS-ADE Workflow

Central Pharmacy Floor Virtual

  • Alert Work List
  • Patient ID
  • Date/location
  • Trigger details
  • Triage
  • Alert Review
  • Chart
  • Patient
  • Intervention
  • Trigger Evaluation
  • Respond to ?’s
  • Data Warehouse
  • Biweekly meetings

15 minutes 1-2 minutes (review) 1-2 minutes

1 minute (response)

Per alert

results
Results†

Test site average: 5-10 alerts per 100 patient days

†Preliminary data from alpha-site testing

trigger evaluation
Trigger Evaluation

Was the alert useful?

trigger evaluation1
Trigger Evaluation

Did the alert detect an adverse event or trend?

trigger evaluation2
Trigger Evaluation

Did the alert change patient care?

trigger evaluation3
Trigger evaluation

Did a drug cause the adverse event or trend?

tids ade trigger summary
TIDS-ADE: Trigger Summary

Results can guide refinement of alerts.

impact on ade detection rates
Impact 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 trend

adverse event or trend was caused by a drug

Baylor Grapevine

  • >40 cases meeting both conditions over 10 weeks
  • Approximately 4-5 ADEs detected per week with TIDS

2.3 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 admissions

academic centers/training programs

mature EHRs/CPOE

experience with trigger tool methodology

vs.

  • Community setting

paper based with varying degrees of IT support

staffing limitations

acceptance of trigger approach to ADEs

verification process can be difficult

additional outcomes
Additional 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

slide19

Lessons learned from TIDS-ADE

  • 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 characteristics

performance of specific triggers

ADE detection rate

  • Dynamic evaluation process for alerts is critical

optimizes performance of the triggering system

reduction in alert fatigue

tids ade future directions
TIDS-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 projectrealistic planning for resource allocations