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Illuminating the Fine Print: Visualizing Medication Side-Effects in Complex Multi-drug Regimens. Jon D. Duke, MD NLM Medical Informatics Fellow Regenstrief Institute Indiana University. The QuARK Project. Quantitative Adverse R eaction Knowledgebase. The Tao of QuARK. The Concept
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Illuminating the Fine Print: Visualizing Medication Side-Effects in Complex Multi-drug Regimens Jon D. Duke, MD NLM Medical Informatics Fellow RegenstriefInstitute Indiana University
The QuARK Project Quantitative Adverse Reaction Knowledgebase
The Tao of QuARK • The Concept • Building the Knowledgebase • Clinical Applications • Testing the Model • Future Directions and Research QuARK: Quantitative Adverse Reactions Knowledgebase
QuARK: What is it good for? The primary goal of QuARK is to simplify the process of assessing adverse drug reactions in patients taking multiple medications. QuARK: Quantitative Adverse Reactions Knowledgebase
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.
Polypharmacy • Has increased significantly over past 20 years • Increases risk for adverse drug reactions • Known risk factor for overall morbidity and mortality • Estimated cost $76B annually 1 2 1 3 Hajjar ER, Cafiero AC, Hanlon JT. Polypharmacy in elderly patients. Am J GeriatrPharmacother 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 GeriatrPharmacother 2006;4: 36-41. 3. Tam-McDevitt J. Polypharmacy, Aging, and Cancer: Growing Risks. Oncology 2008;9.
X Number of Drugs SE Complexity Physician Time = The Problem
Goals • Look up multiple medications simultaneously • Rapidly get to side-effect of interest • Show the relative strength of association between a drug and its side-effects • Well-integrated into clinical workflow
Hmmmmm…. Zocor Metformin Norvasc Lisinoprol/HCTZ Azithromycin Nausea Dizziness Edema Fatigue Cough Palpitations
Which Medications to Include? • By prescribing volume • By formulary QuARK Wishard Top 500 Clarian Top 500 U.S. Top 300
Coding the Medications • RxNorm • UNI • NDC • Regenstrief Dictionary QuARK RI Dictionary RxNorm
Sources of Adverse Reaction Data • FDA Label • MedWatch / AERS • Clinical Repository (eg. RMRS) • Social Networks (eg. patientslikeme.com) QuARK FDA Label
Coding the Side-Effects • MedDRA • CTCAE • SNOMED-CT • ICD-9 • UMLS CUI QuARK MedDRA UMLS CUI SNOMED-CT
Which Side-Effects to Include? Must select a singleunique representation of each medication / side-effect pair
Which Side-Effect Data to Include? • Which treatment indication? • Which dose? • Which trial duration? • Pre- / Post-marketing data? QuARK If duplicate data: Most common indication preferred Aggregate dose data preferred, otherwise most common dose Larger trials with longer duration preferred Post-marketing data included if not present in trials
Side-Effect Quantification The assignment of a numericscore to represent the relative frequency at which a particular medication causes a particular side-effect.
Types of Frequency Data • Drug vs Placebo • 34% of Neurontin patients experienced nausea vs 12% of placebo patients • Frequency Range • Between 3% and 9% of patients taking Lipitor experienced dizziness • Qualitative Frequency Descriptor • Diarrhea occurredinfrequently in patients taking Lisinopril • Statement of Occurrence • Thrombocytopenia was reported in patients taking Norvasc.
Drug vs Placebo eg. 34% of Neurontin pts experienced nausea vs 12% of placebo pts • 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
Frequency Range eg. Between 3% and 9% of Lipitor patients experienced dizziness • No 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 Frequency Range Scoring Between X% and Y% of patients taking {drug} experienced {effect} Score = X+(Y-X)/3
Qualitative Frequency Descriptor • eg. Diarrhea occurred infrequently in patients taking Lisinopril • 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 Qualitative Scoring Occasionally 0.75 Infrequently 0.5 Rarely 0.3
Statement of Occurrence • eg. Thrombocytopenia was reported in patients taking Norvasc. • 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 Occurrence Scoring Occurs in drug 0.8 Occurs in class 0.7 Occurs more often in placebo 0.1
Rxplore • Interactive 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 profile
QuARK & Gopher • Goal: 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 chart
Medication Heat Map Adverse Effects by Organ System Dizziness 24% vs 3% Headache 11% vs 2% Insomnia 6% vs 3% Diazepam Highly Affected Minimally Affected
QuARK & Clinical Reminders • Chief Complaint-driven • Trigger Event-driven
QuARK & Clinical Reminders • Chief 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%) ”
QuARK & Clinical Reminders • Trigger 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) ”
QuARK Part IV: Testing the Model
Garbage In / Garbage Out? • Limitations of the Data • Algorithmic Considerations • Does a Gold Standard exist? • An Approach to Validation
Comparison with AERS • Adverse Event Reporting System • Captures over 400,000 reports a year • Allows for listing of multiple medications • Records Adverse Reaction and Suspected Cause • Subset includes “Dechallenge” Data
QuARKvs 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 medications • Compared the QuARK “suspected drug” with actual reported cause
Accuracy of QuARK Ranking for AERS Reports Q2 2008 % Accuracy n=21 n=14 n=25 n=31 Reported Adverse Reaction
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 AERS
Evaluation Studies • Laboratory study of “decision velocity” • Survey of User Satisfaction / Efficiency
Clinical Reminder Study • Generate 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 discontinuation
Build a Better QuARK • Additional medications • Expansion of AERS-QuARK analysis • Optimization of scoring algorithm • Additional visualization methods • Potential use in consumer health