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Illuminating - PPT Presentation

the Fine Print Visualizing Medication SideEffects in Complex Multidrug Regimens Jon D Duke MD NLM Medical Informatics Fellow Regenstrief Institute Indiana University The QuARK ID: 377739

drug quark data adverse quark drug adverse data side placebo patients frequency effect effects medications medication reactions polypharmacy clinical

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Slide1

Illuminating the Fine Print: Visualizing Medication Side-Effects in Complex Multi-drug Regimens

Jon D. Duke,

MD

NLM Medical

Informatics Fellow

Regenstrief

Institute

Indiana UniversitySlide2

The QuARK Project

Quantitative Adverse

R

eaction KnowledgebaseSlide3

The Tao of QuARK

The Concept

Building the Knowledgebase

Clinical Applications

Testing the Model

Future Directions and Research

QuARK

:

Quantitative

Adverse Reactions KnowledgebaseSlide4

Part I:

The ConceptSlide5

The primary goal of QuARK is to simplify the process of assessing adverse drug reactions in patients taking multiple medications.

QuARK

: What is it good for?

QuARK

:

Quantitative

Adverse Reactions KnowledgebaseSlide6

PolypharmacySlide7

Polypharmacy

Kaufman DW, Kelly JP, Rosenberg L, Anderson TE, Mitchell AA. Recent patterns of medication use in the ambulatory

adult population of the United States: the Slone survey. JAMA 2002;287: 337-44.Slide8

PolypharmacyHas increased significantly over past 20 yearsIncreases risk for adverse drug reactions

Known risk factor for overall morbidity and mortality

Estimated cost $76B annually

Hajjar

ER,

Cafiero

AC, Hanlon JT. Polypharmacy in elderly patients. Am J

Geriatr

Pharmacother

2007;5: 345-51.

2. Nguyen JK,

Fouts

MM,

Kotabe

SE, Lo E. Polypharmacy as a risk factor for adverse drug reactions in geriatric

nursing home residents. Am J

Geriatr

Pharmacother 2006;4: 36-41.3. Tam-McDevitt J. Polypharmacy, Aging, and Cancer: Growing Risks. Oncology 2008;9.

1

2

1

3Slide9

Side-Effect ComplexitySlide10

Number of Drugs

SE Complexity

X

Physician Time

= The ProblemSlide11

Side-Effects InteractionsSlide12

Current SolutionsSlide13

GoalsLook up multiple medications simultaneouslyRapidly get to side-effect of interest

Show the relative strength of association between a drug and its side-effects

Well-integrated into clinical workflowSlide14

Origins of QuARKSlide15

Hmmmmm….

Zocor

Metformin

Norvasc

Lisinoprol

/HCTZ

Azithromycin

Nausea Dizziness Edema Fatigue Cough PalpitationsSlide16

Part II:Building the KnowledgebaseSlide17

Which Medications to Include?By prescribing volumeBy formulary

QuARK

Wishard

Top 500

Clarian Top 500

U.S. Top 300Slide18

Coding the MedicationsRxNormUNI

NDC

Regenstrief

Dictionary

QuARK

RI Dictionary

RxNormSlide19

Sources of Adverse Reaction Data

FDA Label

MedWatch

/ AERS

Clinical Repository (

eg

. RMRS)

Social Networks (

eg

. patientslikeme.com)

QuARK

FDA LabelSlide20

Coding the Side-EffectsMedDRACTCAE

SNOMED-CT

ICD-9

UMLS CUI

QuARK

MedDRA

UMLS CUI

SNOMED-CTSlide21

Which Side-Effects to Include?

Must select a

single

unique

representation of each

medication / side-effect pairSlide22

Which Side-Effect Data to Include?

Which treatment indication?

Which dose?

Which trial duration?

Pre- / Post-marketing data?

QuARK

Most common indication preferred

Aggregate dose

data preferred,

otherwise most

common dose

Larger trials with

longer duration

preferred

If duplicate data:

Post-marketing

data included if

not present in trialsSlide23

Side-Effect Quantification

The

assignment of a

numeric

score

to represent the relative frequency at which a particular medication causes a particular side-effect.Slide24

Types of Frequency DataDrug vs

Placebo

34% of

Neurontin

patients experienced nausea

vs

12% of placebo patientsFrequency RangeBetween 3% and 9% of patients taking Lipitor experienced dizzinessQualitative Frequency Descriptor

Diarrhea occurred

infrequently in patients taking

Lisinopril

Statement of Occurrence

Thrombocytopenia was reported in patients taking

Norvasc

.Slide25

Drug vs Placebo

Optimal data format

Applied “Absolute Risk Reduction” approach (

ie

. treatment incidence – placebo incidence)

ex. Score = 34 - 12 = 22

Database would include both the original raw data in addition to the calculated score

QuARK

Drug

vs

Placebo

Score =

Treatment Incidence

-

Placebo

Incidence

eg

. 34% of

Neurontin

pts experienced nausea

vs

12% of placebo ptsSlide26

Frequency RangeNo placebo data given

Study size and duration not available

Patient population unknown

Conservative score calculation: Score = x+(y-x)/3 = 3+(9-3)/3 = 5

Original data range preserved in database

QuARK

eg

. Between 3% and 9% of Lipitor patients experienced dizziness

Frequency Range

Scoring

Between X% and Y% of patients taking {drug} experienced {effect}

Score =

X+(Y-X)/3Slide27

Qualitative Frequency Descriptor

No placebo or population data

Wide range of terms used (

eg

. rarely, occasionally, often)

Quantitative mappings may be provided (Rarely = “< 1/100”)

Where mappings unavailable, conservative scores assigned based on interpretation of terms (sometimes = occasionally > infrequently)

QuARK

eg

. Diarrhea occurred infrequently in patients taking

Lisinopril

Qualitative

Scoring

Occasionally 0.75

Infrequently 0.5

Rarely 0.3Slide28

Statement of Occurrence

No frequency information

No placebo or population data

Commonly seen with post-marketing reports or class effects

Conservative scoring applied

“Post-Marketing” status noted in database

QuARK

eg

. Thrombocytopenia was reported in patients taking

Norvasc

.

Occurrence

Scoring

Occurs in drug 0.8

Occurs in class 0.7

Occurs more often in placebo 0.1Slide29
Slide30

QuARK Part III:ApplicationsSlide31

RxploreInteractive visualization of

QuARK

data

Allows quick retrieval of most common side-effects of complex drug regimens

Highlights potential causal agents in the setting of an adverse drug event

Allows “virtual swapping” of a medication to assess impact on patient’s side-effect profileSlide32
Slide33

QuARK & GopherGoal: Allow

QuARK

visualizations to be retrieved directly from Gopher order entry

Created prototype running on Gopher Dev

Auto-populates medication list directly from Gopher patient chartSlide34
Slide35
Slide36

QuARK

Bubble MapSlide37

Medication Heat Map

Adverse Effects by Organ System

Dizziness 24%

vs

3%

Headache 11%

vs

2%

Insomnia 6%

vs

3%

Highly Affected

Minimally Affected

DiazepamSlide38

QuARK & Clinical RemindersChief Complaint-driven

Trigger Event-drivenSlide39

QuARK & Clinical RemindersChief Complaint-driven

Which of a patient’s medications are associated with the Chief Complaint?

At what frequency?

The patient’s complaint of Dizziness has been associated with use of:

Gabapentin (28% vs. 7% Placebo)

Atenolol

(13%

vs

6% Placebo)

Omeprazole

(Less than 1%) ”Slide40

QuARK & Clinical RemindersTrigger Event-driven

Laboratory / EKG change generates reminder

Offers suggestions for possible causal agents

Neutropenia

(WBC 1.4 10/22/08) has been

associated with use of:

Valsartan

(1.9%

vs

0.8% placebo)

Amiodarone

(Has been reported)

Lisinopril

(Occurs rarely) ”Slide41

QuARK

Part IV:

Testing the ModelSlide42

Garbage In / Garbage Out?Limitations of the DataAlgorithmic Considerations

Does a Gold Standard exist?

An Approach to ValidationSlide43

Comparison with AERSAdverse Event Reporting SystemCaptures over 400,000 reports a year

Allows for listing of multiple medications

Records Adverse Reaction and Suspected Cause

Subset includes “

Dechallenge

” DataSlide44

QuARK vs AERS

Dechallenge

data from 2008 Q2

Evaluated reports of four common reactions (nausea, edema, insomnia,

hyponatremia

)

Limited to cases where patient was taking at least 5 medicationsCompared the QuARK “suspected drug” with actual reported causeSlide45

% Accuracy

Reported Adverse Reaction

Accuracy of

QuARK

Ranking for AERS Reports Q2 2008

n=31

n=21

n=14

n=25Slide46

Sources of Error<10% missed cases due to algorithm error>90% missed cases due to complete absence of the adverse reaction from the drug label

Delays in drug label updating

Reflects nature of adverse event reporting

Known side-effects often not reported

New drug mandatory reporting predominates AERSSlide47

QuARK

Part V:

Future Directions and ResearchSlide48

Evaluation StudiesLaboratory study of “decision velocity”Survey of User Satisfaction / EfficiencySlide49

Clinical Reminder StudyGenerate

QuARK

-based reminders for laboratory triggers (

eg

. LFT’s)

Intervention group receives reminder noting potential causal agents / frequency data

Compare drug discontinuation rates as well as time between trigger and discontinuationSlide50

Build a Better QuARKAdditional medications

Expansion of AERS-

QuARK

analysis

Optimization of scoring algorithm

Additional visualization methods

Potential use in consumer healthSlide51

SummaryQuARK is a knowledgebase containing quantitative frequency data for adverse drug reactions

Potential applications include:

visualization of side-effect data

simplified lookup of multidrug regimens

clinical reminders targeted at

adverse drug

eventsOpportunities for research collaborationSlide52

Thanks! NLM, Steve Downs, Mike McCoy, Marc

Overhage

, Shaun

Grannis

,

Gunther

Schadow, Siu Hui, Martin Were, Marc

Rosenmann

,

Linas

Simonatis

,

Atif

Zafar

, Paul Dexter, Mike Weiner, Paul Biondich, Burke Mamlin, Anne

Belsito

Pop the QuARK

!