1. Impact of the Institute for Healthcare Improvement Global Trigger Tool Compared to Current Adverse Event Monitoring Systems at a Large Teaching Hospital
Tania Vila, PharmD
Drug Information Specialty Resident
Duke University Hospital
Co-Investigators:
Heidi Cozart, R.Ph.; Lynn Eschenbacher, PharmD, MBA; Diana Brown, RN; William Richardson, MD

2. Background: Adverse Event Detection Methods
44,000 to 98,000 deaths per year occur in U.S. hospitals as a result of errors
Three-pronged approach to adverse event monitoring
Voluntary Reporting
Computerized Monitoring
Global Trigger Tool – New methodology
Kohn LT, Corrigan JM, Donaldson MS, editors. To err is human: building a safer health system. Washington, DC: National Academy Press; 2000.

3. Background: Adverse Event Detection Methods
Voluntary Reporting
Qualitative data informs and guides safety and quality (sentinel events, near misses)
First-hand account of event from reporters
Anonymous & accessible to all hospital employees (available online)
Under-reporting

4. Background: Adverse Event Detection Methods
Computerized Monitoring
Automated surveillance for possible ADEs based on logic-based rules followed by chart review
Scans demographic, laboratory, pharmacy system, and other clinical databases
Quantitative data allows for trending
Standardized scoring system for severity and causality (Naranjo Scale)
Only high risk medication rules are evaluated
Killbridge P, Classen. Surveillance for adverse drug events: history, methods and current issues. VHA’s 2002 Research series;3:1-44. 4

5. Example of Computerized Monitoring (ADE-S) Rules
Antidotes or combinations of medications and laboratory values
Naloxone IV
Dextrose 50% IV AND low blood glucose (<50 mg/dL)
2 consecutive aPTT values > 100 OR one >150 seconds in patient receiving heparin

6. Background: Adverse Event Detection Methods
IHI Global Trigger Tool™
New methodology
Trigger-based manual chart review
Review team minimum of 3 people
20 charts per month recommended
20 minutes/chart
Less resource intensive
Griffin FA, Resar RK. IHI Global Trigger Tool for Measuring Adverse Events. IHI Innovation Series white paper. Cambridge, MA: Institute for Healthcare Improvement; 2007.

7. 7

8. Purpose: Primary Objective
To determine the frequency and types of adverse events in urology and orthopedics services as identified by the IHI Global Trigger Tool™
Frequency defined as follows:
Adverse events/1,000 patient days

9. Purpose: Secondary Objectives
To compare the frequency and characteristics of AEs detected by the IHI Global Trigger Tool™, computerized monitoring, and the voluntary reporting system
To identify potential quality improvement opportunities and to recommend enhancements to the computerized monitoring system based on results

10. Design
Retrospective chart review of patients admitted between January 1, 2007 and June 30, 2007
Inclusion Criteria
≥18 years
Patients admitted to urology or orthopedics
Chart must be closed and complete
Approved by the Duke University Institutional Review Board

11. Methods: IHI Global Trigger Tool™
120 patients admitted to urology and orthopedic services were randomly selected (5/service) in 2 week blocks
Training: Nurse, pharmacist, and physician completed IHI training process
Phase I: IHI standardized practice charts with key
Phase II: IHI trigger tool with Duke-specific charts
Data Collection: Nurse and pharmacist reviewed each chart; MD reviewed discordant cases

12. IHI Chart Review Process
Data Collection Process
Discharge summary
Laboratory results
Physician orders/MAR
Nursing notes/flow sheets and progress notes
Documentation
All triggers documented whether or not an adverse event occurred
Event severity was scored according to an internal scale and a nationally validated scale

13. Methods: Severity Scores
Severity Index, (internal scale; 0 through 6)
Only 3 through 6 represent patient harm 3
Transient adverse patient effects occurred which required some corrective therapy, increased length of stay (LOS) 1-2 days or resulted in lab values, vital signs or medication effects outside the desirable parameters 4
Significant adverse patient effects occurred which required aggressive intervention such as code, intubation, transfer to ICU, antidote, interventional drug therapy or increased LOS > 2 days 5
Permanent adverse patient effects occurred such as paralysis, brain damage, disability or loss of limb, organ, or bodily function 6
Patient death

14. Methods: Severity Scores
National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP), (A through I)
Only E through I represent patient harm E
Temporary harm to the patient and required intervention F
Temporary harm to the patient and required initial or prolonged hospitalization G
Permanent patient harm H
Intervention required to sustain life I
Patient death

15. Patient Population Definitions
IHI Global Trigger Tool™
Random sample of 120 patients from all orthopedics and urology admissions between Jan. 1 to June 30, 2007
Voluntary Reporting and Computerized Monitoring
Unique admissions to orthopedics or urology services on the 2 patient care units most likely to care for these patients between Jan. 1 to June 30, 2007

16. Results: Demographics of Adverse Event Population
Detection Method
(admissions with AE*)
IHI
(n = 50)
Computerized Monitoring
(n = 17)
Voluntary Reporting
(n =11)
Mean Age, years ± SD
Range
18-64 years, n (%)
≥65 years, n (%)
59.9 ± 15.5
21-90
29 (58%)
21 (42%)
69.5 ± 14.2
37-90
5 (29%)
12 (71%)
51.2 ± 13.1
30-74
10 (91%)
1 (9%)
Gender
Male, n (%)
31 (62%)
7 (41%)
5 (46%)
Admit Service
Orthopedics, n (%)
Urology, n (%)
24 (48%)
26 (52%)
9 (53%)
8 (47%)
9 (73%)
3 (27%)
Median LOS †, Days 4
1-23 8
1-44 5
3-14
*unique admissions to orthopedics or urology with an adverse event identified
†LOS = Length of stay

17. Results: Adverse Event Detection Methods
59 events 57
19 events
IHI Trigger Tool
289 positive triggers
IHI Trigger Tool
Computerized
Monitoring
222 rules fired
Computerized Monitoring 1 16 1 2
Voluntary
Reporting
85 reports
Voluntary Reporting
Random sample
of 120 unique
admissions 10
1294 unique
admissions
13 events 17

18. Results: Adverse Event Frequencies
IHI Global Trigger Tool
Computerized Monitoring
Voluntary Reporting
High risk medication related adverse events/1000 patients
Adverse events/1000 patients
Primary
endpoint
136
SRS compared to IHI global trigger tool and ADE-S – less than 2-fold difference; but IHI captures much more overall than ADE-S or SRS;
HC: It is amazing how close these numbers are.. 4 3 4 2 23 18

19. Results: IHI Global Trigger Tool™ Adverse Event by Category
Fall, 1.7%
Miscellaneous†, 5.1%
Narcotics/Benzodiazepines, 11.9%
Care Module
(47.5%)
Medication
Module
(30.6%)
Surgical
(22%)
Hospital-associated infection, 13.6%
Chest pain, 3.4%
Thrombosis/ Anticoagulation, 5.1%
Adverse drug reaction, 13.6%
Surgical complications, 22%
59 adverse events detected
Transfusion/blood loss anemia, 23.7%
†Miscellaneous includes chemo-induced neutropenia (n = 1), hyponatremia/delirium (n = 2)

20. Results: Computerized Monitoring Adverse Event by Category
Compared to IHI…
11.9% captured
by IHI
Narcotics/ Benzodiazepines, 26.3%
19 adverse events detected
Anticoagulants, 52.6%
Hypoglycemia, 21.1%
5.1% captured
by IHI
0% captured
by IHI

21. Results: Voluntary Reporting Adverse Events by Category
Cathartics/Laxatives, 7.7%
Electrolyte Replacement Therapy (potassium), 7.7%
Compared to IHI…
More high risk
medication
adverse events
No hypoglycemia
events
Anesthetics, 7.7%
Narcotics/ Benzodiazepines, 38.5%
Anticoagulants, 15.4%
13 adverse events detected
Antibiotics, 23.1%

22. Results: Adverse Event Severity
Internal Severity Index
Nationally validated
NCC MERP
84.7%
79%
66%
Percentage (%)
67%
34%
21%
33%
15.3%
<3 = did not reach patient; 3 = temporary harm, required corrective therapy OR resulted in labs/vitals outside desirable range; 4 = required aggressive treatment, prolonged LOS > 2 days OR resulted in initial hospitalization

23. Future Enhancements Expand computerized monitoring
Discharge notes and nursing notes were valuable in adverse event identification in IHI
As technology advances and nursing notes become electronic, free-text scanning may become a valuable implementation
Example “oversedation” search versus IV naloxone rule

24. Limitations Retrospective chart review
Not generalizable to other services
Causality and preventability not assessed on IHI Global Trigger Tool™
Physician reviewer was an orthopedic surgeon which may introduce bias

25. Limitations
Subjective judgment of adverse events (e.g. anemia due to blood loss from surgery)
Not 1:1 comparisons with IHI
Computerized monitoring and voluntary reporting data extracted by the units most likely to care for these orthopedics and urology patients
IHI Trigger Tool™ used a random sample rather than all admissions to orthopedics and urology

26. Conclusions
IHI Trigger Tool™ identifies the greatest number of events overall
Computerized monitoring and voluntary reporting identify greater proportion of medication-related events
Voluntary systems good at capturing near misses/rare events whereas surveillance (IHI and computerized monitoring) better at capturing harm
All 3 adverse event detection methods are complementary 26

27. Acknowledgements Department of Pharmacy Residency Research Committee
Computerized Patient Safety Initiatives, Duke Health Technology Solutions
Julie Eckstrand, Pharm.D.
Monica Horvath, Ph.D.
Andrea Long, Pharm.D.
Julie Whitehurst, Pharm.D.

28. Questions

29. ADE-S System Pharmacy Clinical Rules Engine Laboratory
Demographic Data
Pharmacy
Immediate
Intervention
required?
Health-system clinical pharmacists
List of Triggers (daily)
Computerized Patient Safety Initiative (CPSI) pharmacists
Score and
document
ADE causality,
severity, and
narrative
Investigate trigger
(e.g. chart review)
Kappa
pharmacist No
Yes
Kappa
pharmacist
Intervene and document intervention

30. Adverse Drug Reaction Probability Scale
Do Not Know
Adverse Drug Reaction Probability Scale
Yes No
Are there previous conclusive reports on this reaction? +1
Did the adverse event appear after the drug was administered? +2 -1
Did the adverse reaction improve when the drug was discontinued or a specific antagonist was administered?
Did the adverse reaction reappear when the drug was re-administered?
Are there alternative causes (other than the drug) that could, on their own, have caused the reaction? -2
Did the reaction re-appear when a placebo was given?
Was the drug detected in the blood (or other fluids) in concentrations known to be toxic?
Was the reaction more severe when the dose was decreased?
Did the patient have a similar reaction to the same or similar drugs in any previous exposure?
Was the adverse event confirmed by an objective evidence?
≥9 Definite; 8 to 5 Probable; 1 to 4 Possible; ≤0 Doubtful
Naranjo CA, Busto U, Sellers EM, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther 1981;30:

31. Sample Size Calculation
87% power at 120 charts to detect a 4-fold difference in rates between IHI Trigger Tool™ and ADE-S during a 6 month period 31

34. IHI Surgical Trigger Tool™
Surgical Trigger Tool™ contains 28 triggers
Surgical triggers have corresponding code on global trigger tool (not limited to surgical module)
193 surgical triggers vs. 289 global triggers (67% correspondence) 34

35. Results: IHI Triggers by Frequency
Return to surgery
Admission to ICU post-op
X-ray or doppler studies for emboli
Any procedure complication
SCr > 2 times baseline
Consult requested in PACU
C. diff positive culture
Romazicon (flumazenil) use
Time in ED > 6 h
Narcan (naloxone) use
Abrupt med stop
3.5%
op-time >6 h
3.1%
Fall 2.8%
Other triggers
20%
X-ray intra-op
5.6%
Transfusion
10.1%
Benadryl use
6.9%
Abrupt drop in Hct of 25%
13.9%
Oversedation/ hypotension
7.6%
Anti-emetic use
18.4%
Readmission 8%
289 triggers