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Jumping the crevasse between 
assertions of drug interactions and 
clinical relevance 
Daniel C. Malone, RPh, PhD 
Profess...
The Problem! 
You wouldn’t believe how many BIG BAD drug‐drug interactions 
there are. Just ask your doctor about all the ...
Prescriber’s Knowledge 
Computer Screening 
Pharmacist’s Knowledge 
Latent Failures 
Patient Risk Factors 
Drug Administra...
Market Removals Due to 
Drug‐Drug Interactions 
• Terfenadine (Seldane®) – 1998 
• Mibefradil (Posicor®)‐ 1998 
• Astemizo...
5 
VA practitioner knowledge of 
drug-drug interactions 
• 168 responses to a postal survey 
• 135 physicians 
• 22 nurse ...
6 
National Survey of Prescribers’ 
Knowledge of DDIs - Methods 
• Postal survey of prescribers (12,500) 
• Sample: Identi...
7 
Summary of Prescriber DDI 
Knowledge 
• Correct classification of drug-pairs 
• Mean (SD) = 6.0 (3.1) 
• Overall – 42.7...
Background 
• Drug‐drug interaction alerts can be useful 
• Prescriber knowledge of DDIs is lacking1,2 
• 42.7% of drug pa...
Sensitivity of Computer Software to Detect Drug 
Interactions in Arizona Pharmacies (N=64) 
75% 
80% 
83% 
87% 
88% 
86% 
...
DDI Prevalence in Elderly 
• Elderly veterans with new 
DDI at ED discharge:1 
13% 
• Older adults exposed to a 
“major” D...
Who Prescribes Drug‐Drug 
Interactions? 
70 
60 
50 
40 
30 
20 
10 
0 
Potential Drug‐Drug Interactions 
by the Same Pres...
Concordance Among DDI Compendia
Methods 
• Review of print versions of compendia for 
“major” interactions 
• Inclusion Criteria: 
• DDI listed in at leas...
Rating Systems & Selection 
Criteria 
• Evaluation of Drug Interactions 
• Uses 4-item summary measure based on: 
• Potent...
Rating Systems & Selection 
Criteria 
• Drug Interaction Facts 
• Uses 5-item summary measure based on: 
• Severity (i.e.,...
Rating Systems & Selection 
Criteria 
• Drug Interactions: Analysis and Management 
• Used 5-item summary measure based on...
Rating Systems 
• Drug-REAX (MicroMedex) 
• Used 5-item severity scale 
• Major 
• Moderate 
• Minor 
• None 
• Not specif...
Results 
• 62 ‘major’ DDIs identified 
• Additional criteria: 
• 18 ‘major’ DDIs excluded : 
• 8 DDIs - not available in U...
Agreement Among Four Drug 
Interaction Compendia 
 DDIs in 4 of 4: 2.2% (9/406) 
 DDIs in 3 of 4: 8.6% (35/406) 
 DDIs ...
Clinical Pharmacology and Therapeutics 2011: 87:48‐51
“Only 13.6% of “critical interactions” listed in both compendia
Quantity and Quality of DDI Evidence 
– Interactions with Macrolides 
Harper, Jackson, and Malone – unpublished data
Reasons for Differences in Drug‐Drug 
Interaction Compendia 
• Rating systems are different 
• Lack of high‐quality studie...
Hierarchy of Evidence 
Systematic Reviews 
RCTs 
Controlled Clinical Trials 
and Observational Studies 
Uncontrolled Obser...
Theophylline – Allopurinol: 
A Major Drug Interaction? 
Theophylline 
1A2 16% 
35% 1-methylxanthine 
1A2 40% 3A, 2E1 
3-Me...
Theophylline – Allopurinol: 
A Major Drug Interaction? 
• Listed as major in several CDS databases 
• Two studies found no...
Theophylline Label 
Table II. Clinically significant drug interactions with theophylline*. 
Drug Type of Interaction Effec...
Azithromycin 
Product Label 
• “The following drug interactions have not been reported in clinical 
trials with azithromyc...
Health Systems Approach to DDIs 
• Evidence for DDIs is lacking 
• Very few well-controlled studies 
• Lack of concordance...
Problems With DDIs in CDS Systems 
• Classification systems that are based on rules of 
questionable relevance 
• Reliance...
Model for DDI alerting in CPOE 
Knowledge‐base (rules) 
Integration 
software 
Patient database 
(meds, etc.) 
Knowledge 
...
Too many alerts! 
• Organizational alert override rates are high 
• 96% in Netherlands1 
• US medical center2 
• 461 diffe...
Case Study ‐ Sentara Healthcare 
• Amiodarone + warfarin DDI fires 1000 times 
• 960 – alert overridden/bypassed 
• 40 – w...
Practitioners’ Views on DDI Alerts 
• Methods 
• Random sample of 100 to 125 practitioners 
in outpatient clinics at 6 VAM...
Practitioners’ Views of Alerts 
Prescribers’ Views on DDI Alerts Mean 
Response 
I am satisfied with the accuracy of DDI 
...
Attitudes Toward Improving DDI 
Alerts 
Attribute Mean 
Response 
DDI alerts should be accompanied by management 
alternat...
Top Ranked Changes to VA’s 
Alerting System 
Change Weighted 
Preference Score 
Provide management options for DDIs 1.53 
...
“Asthma sufferer wins $28.6 million award” – 
Seattle Time (9/3/94) 
• 24 year old man on theophylline went to 
ER with an...
Tranylcypromine (Parnate®) + 
Phenylpropanolamine (Tavist‐D®) 
• Patient on Parnate went to ER for URI: 
received Rx for T...
Current “Lists” of Important DDIs 
Source Purpose Systematic 
Review 
Expert 
Panel 
Consensus 
Process 
Classen 2011 / 
L...
Rationale for Changing the Approach 
• Drug interaction clinical decision support should 
improve patient safety 
• Instea...
Rationale for Changing the Approach 
• Concerns about process used to generate 
current “lists” 
• No well‐defined, broadl...
AHRQ Conference Series 
• DDI CDS conference series to: 
• Develop guidelines for systematic appraisal of DDI 
evidence (E...
Project At A Glance
DDI CDS Conference Website 
https://sites.google.com/site/ddiconferenceseriessite/home
DRug Interaction eVidence Evaluation 
(DRIVE) Instrument 
Category Evidence 
Sufficient 
Sufficient 
evidence to 
evaluate...
DRug Interaction eVidence Evaluation 
(DRIVE) Instrument 
Category Evidence 
Insufficient 
Insufficient 
evidence to 
eval...
AHRQ Conference Series 
Workgroup Recommendations 
• Establish national expert consensus panel 
• Oversight by national or...
Transparent, Systematic Process for a 
Standard Set of DDIs 
1. Evidence 
Synthesis & 
Grading 
2. Expert 
Advice 
Nationa...
Support 
Agency for Healthcare Research and Quality 
• Grant #1R13HS021826‐01 (PI –Malone) 
• Grant #1R13HS018307‐01 (PI –...
Acknowledgements 
• Lisa Hines, PharmD, University of Arizona 
• Richard T. Scheife, PharmD, FCCP, Tufts University 
• Dar...
Acknowledgements 
• Lisa Hines, PharmD, University of Arizona 
• Hugh Tilson, MD, DrPH, University of North Carolina 
• Da...
Acknowledgements 
• Thomas H Payne, MD, FACP, University of Washington 
• Bruce W Chaffee, PharmD, University of Michigan ...
Thanks! 
Questions and Comments? 
Answers (Even Better)?!
Keynote malone-clinical-relevance-of-ddi-evidence
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Keynote malone-clinical-relevance-of-ddi-evidence

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The slides from the keynote given by Dr. Dan Malone RPh, PhD at the First International Drug-Drug Interaction Knowledge Representation Workshop on October 6th 2014 (http://icbo14.com/sessions/drug-drug-interaction-knowledge-representation-workshop/). Posted with his permission.

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Keynote malone-clinical-relevance-of-ddi-evidence

  1. 1. Jumping the crevasse between assertions of drug interactions and clinical relevance Daniel C. Malone, RPh, PhD Professor The University of Arizona
  2. 2. The Problem! You wouldn’t believe how many BIG BAD drug‐drug interactions there are. Just ask your doctor about all the DDI alerts she gets!
  3. 3. Prescriber’s Knowledge Computer Screening Pharmacist’s Knowledge Latent Failures Patient Risk Factors Drug Administration Patient Education Monitoring ADR A + B “When the Holes Line Up” Defenses Hansten PD, Horn JR. Modified from: James Reason, Human Error, 1990
  4. 4. Market Removals Due to Drug‐Drug Interactions • Terfenadine (Seldane®) – 1998 • Mibefradil (Posicor®)‐ 1998 • Astemizole (Hismanal®) – 1999 • Cisapride (Propulsid®) – 2000 • Cerivastatin (Baycol®) – 2001
  5. 5. 5 VA practitioner knowledge of drug-drug interactions • 168 responses to a postal survey • 135 physicians • 22 nurse practitioners • 11 physician assistants • Clinicians correctly categorized 53% of drug-drug interactions • But, only • 64% correctly answered sildenafil-isosorbide (28% not sure) • 58% correctly answered cisapride-erythromycin (27% not sure) • 43% correctly answered phenelzine-sertraline (46% not sure) Source: Glassman PA et al. Medical Care 2002; 40:1161-1171
  6. 6. 6 National Survey of Prescribers’ Knowledge of DDIs - Methods • Postal survey of prescribers (12,500) • Sample: Identified via pharmacy claims to a pharmacy benefit manager • Cases – history of 1 or more DDI’s • Controls – match on prescribing either objective or precipitant medication • Practice characteristics • Respondents asked to classify 14 drug pairs • Contraindicated • May be used together but with monitoring • No interaction • Not sure • Usual source of drug-drug interaction information Ko et al. Drug Saf. 2008;31(6):525‐536.
  7. 7. 7 Summary of Prescriber DDI Knowledge • Correct classification of drug-pairs • Mean (SD) = 6.0 (3.1) • Overall – 42.7% of drug pairs correctly identified • 30% or more of respondents answered “unsure” for 8 of the 16 the drug pairs • 2 combinations are contraindicated
  8. 8. Background • Drug‐drug interaction alerts can be useful • Prescriber knowledge of DDIs is lacking1,2 • 42.7% of drug pairs correctly identified1 • VA practitioners generally agree that DDI alerts are useful3 1) Ko et al. Drug Saf. 2008;31(6):525‐536. 2) Glassman. Med Care. 2002;40(12):1161‐ 1171. 3) Ko et al. JAMIA 2007;14:56‐64
  9. 9. Sensitivity of Computer Software to Detect Drug Interactions in Arizona Pharmacies (N=64) 75% 80% 83% 87% 88% 86% 89% 45% 81% 90% 75% 84% 70% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Warfarin + sulfamethoxazole/trimethoprim Warfarin + naproxen Warfarin + gemfibrozil Warfarin + fluconazole Warfarin + amiodarone Simvastatin + gemfibrozil Simvastatin + amiodarone Simvastain + itraconazole Nitroglycerin + sildenafil Digoxin + itraconazole Digoxin + clarithromycin Digoxin + amiodarone Carbamazepine + clarithromycin Saverno et al. JAMIA; 2011:18:32-37
  10. 10. DDI Prevalence in Elderly • Elderly veterans with new DDI at ED discharge:1 13% • Older adults exposed to a “major” DDI:2 4% • Medicare Part D enrollees exposed to certain DDIs: 7.3% 1) J Am Geriatr Soc. 2008;56:875‐80. 2) JAMA. 2008;300:2867‐78.
  11. 11. Who Prescribes Drug‐Drug Interactions? 70 60 50 40 30 20 10 0 Potential Drug‐Drug Interactions by the Same Prescriber
  12. 12. Concordance Among DDI Compendia
  13. 13. Methods • Review of print versions of compendia for “major” interactions • Inclusion Criteria: • DDI listed in at least 3 compendia • Available in US for human use • Medications likely to be dispensed in community pharmacy • Medications likely captured in electronic database • Interacting medications not used for therapeutic benefit Abarca J et al. J Am Pharmacist Assn 2003: 44:136-141.
  14. 14. Rating Systems & Selection Criteria • Evaluation of Drug Interactions • Uses 4-item summary measure based on: • Potential harm to the patient • Frequency and predictability of occurrence • Degree and quality of documentation • Code 1: highly clinically significant • Code 2: moderately clinically significant • Code 3: minimally clinically significant • Code 4: not clinically significant Abarca J et al. J Am Pharmacist Assn 2003: 44:136-141.
  15. 15. Rating Systems & Selection Criteria • Drug Interaction Facts • Uses 5-item summary measure based on: • Severity (i.e., major, moderate, minor) • Documentation (i.e., established, probable, suspected, possible, unlikely) • 1: major/established, probable, suspected • 2: moderate/established, probable, suspected • 3: minor/established, probable, suspected • 4: major,moderate/possible • 5: minor/possible or any/unlikely Abarca J et al. J Am Pharmacist Assn 2003: 44:136-141.
  16. 16. Rating Systems & Selection Criteria • Drug Interactions: Analysis and Management • Used 5-item summary measure based on: • Severity • Corresponding documentation • Availability of alternatives are considered • 1: Avoid combination • 2: Usually avoid combination • 3: Minimize risk • 4: No action needed • 5: No interaction Abarca J et al. J Am Pharmacist Assn 2003: 44:136-141.
  17. 17. Rating Systems • Drug-REAX (MicroMedex) • Used 5-item severity scale • Major • Moderate • Minor • None • Not specified • No summary measure Abarca J et al. J Am Pharmacist Assn 2003: 44:136-141.
  18. 18. Results • 62 ‘major’ DDIs identified • Additional criteria: • 18 ‘major’ DDIs excluded : • 8 DDIs - not available in U.S. (e.g., terfenadine, mibefradil) • 4 DDIs – not dispensed from a community pharmacy • 4 DDIs – not likely to be captured in electronic database (e.g, ethanol, tyramine-containing foods) • 1 DDI – occurs upon discontinuation (clonidine-β blockers) • 1 DDI – used for therapeutic benefit (phenothiazine-SSRI) Abarca J et al. J Am Pharmacist Assn 2003: 44:136-141.
  19. 19. Agreement Among Four Drug Interaction Compendia  DDIs in 4 of 4: 2.2% (9/406)  DDIs in 3 of 4: 8.6% (35/406)  DDIs in 2 of 4: 17.4% (71/406)  DDIs in 1 of 4: 71.7% (291/406)  Intra-class Correlation Coefficient: -0.092 Abarca J et al. J Am Pharmacist Assn 2003: 44:136-141.
  20. 20. Clinical Pharmacology and Therapeutics 2011: 87:48‐51
  21. 21. “Only 13.6% of “critical interactions” listed in both compendia
  22. 22. Quantity and Quality of DDI Evidence – Interactions with Macrolides Harper, Jackson, and Malone – unpublished data
  23. 23. Reasons for Differences in Drug‐Drug Interaction Compendia • Rating systems are different • Lack of high‐quality studies • Case reports • Small pharmacokinetic studies • Rating is subjective • Different editors/contributors • Few “tools” for evaluating “poor quality” evidence
  24. 24. Hierarchy of Evidence Systematic Reviews RCTs Controlled Clinical Trials and Observational Studies Uncontrolled Observational Studies Case reports and case series Expert Opinions Lowest risk of bias Hypothesis Testing Hypothesis Generating
  25. 25. Theophylline – Allopurinol: A Major Drug Interaction? Theophylline 1A2 16% 35% 1-methylxanthine 1A2 40% 3A, 2E1 3-Methylxanthine 1,3 dimethyluric acid Xanthine Oxidase 1-methylurinc acid
  26. 26. Theophylline – Allopurinol: A Major Drug Interaction? • Listed as major in several CDS databases • Two studies found no change in theophylline PK with allopurinol 300 mg daily x 7 days.1 • One study found ~25% increase in AUC and half-life after 2 weeks of concurrent allopurinol 300 mg BID.2 1. Vozeh S et al. CPT. 1980;27:194‐7. 2. Manfredi RL et al. CPT 1981;29:224‐9
  27. 27. Theophylline Label Table II. Clinically significant drug interactions with theophylline*. Drug Type of Interaction Effect Alcohol A single large dose of alcohol (3 mL/kg of whiskey) decreases theophylline clearance for up to 24 hours. 30% increase Allopurinol Decreases theophylline clearance at allopurinol doses ≥600 mg/day. 25% increase Source: http://dailymed.nlm.nih.gov/dailymed
  28. 28. Azithromycin Product Label • “The following drug interactions have not been reported in clinical trials with azithromycin; however, no specific drug interaction studies have been performed to evaluate potential drug‐drug interaction. Nonetheless, they have been observed with macrolide products. Until further data are developed regarding drug interactions when azithromycin and these drugs are used concomitantly, careful monitoring of patients is advised: • Digoxin–elevated digoxin levels. • Ergotamine or dihydroergotamine–acute ergot toxicity characterized by severe peripheral vasospasm and dysesthesia. • Triazolam–decrease the clearance of triazolam and thus may increase the pharmacologic effect of triazolam. • Drugs metabolized by the cytochrome P450 system–elevations of serum carbamazepine, cyclosporine, hexobarbital, and phenytoin levels.” Source: http://dailymed.nlm.nih.gov
  29. 29. Health Systems Approach to DDIs • Evidence for DDIs is lacking • Very few well-controlled studies • Lack of concordance among DDI compendia1 • Differing severity rating systems, terminology, methodologies • Limitations of DDI clinical decision support2-4 • “Alert fatigue” • High rates of alert override 1) Abarca et al. J Am Pharm Assoc (2003). 2004;44(2):136-141. 2) Grizzle et al. Am J Manag Care. 2007;13(10):573-578. 3) Murphy et al. Am J Health Syst Pharm. 2004;61(14):1484-1487. 4) Abarca et al. J Manag Care Pharm. 2006;12(5):383-389.
  30. 30. Problems With DDIs in CDS Systems • Classification systems that are based on rules of questionable relevance • Reliance on label without informed review or evaluation • Assumption of ‘class–based’ interactions • Conclusion: “the current DDI alert system is broken”1 1Hatton RC, et al. Ann Pharmacother. Mar 2011;45(3):297‐308.
  31. 31. Model for DDI alerting in CPOE Knowledge‐base (rules) Integration software Patient database (meds, etc.) Knowledge engineering Literature, domain expertise Potential DDI report MD Pharmacist Nurse
  32. 32. Too many alerts! • Organizational alert override rates are high • 96% in Netherlands1 • US medical center2 • 461 different physicians, 18,354 medication orders • 2,455 alerts • DDI override rate: 95.1% 1van der Sijs H, Aarts J, Vulto A, Berg M. Overriding of drug safety alerts in computerized physician order entry. J Am Med Inform Assoc. 2006 2006 Mar‐Apr;13(2):138‐47. 2Bryant AD, Fletcher GS, Payne TH. Drug interaction override rates in the Meaningful use era: no evidence of progress. Applied Clinical Informatics 2014; 5:802‐813
  33. 33. Case Study ‐ Sentara Healthcare • Amiodarone + warfarin DDI fires 1000 times • 960 – alert overridden/bypassed • 40 – warfarin dose adjusted • 10 – INR or CBCs ordered • 30 – INR or CBC frequency adjusted • 50 – pt. education or anticoagulation clinic scheduled • 5 – alert overridden, INR > 5
  34. 34. Practitioners’ Views on DDI Alerts • Methods • Random sample of 100 to 125 practitioners in outpatient clinics at 6 VAMCs • Results (N = 258) (Response rate: 36%) • Internal medicine – 31% • Primary care – 29% • Years in practice (mean) - 14.8 (10.6) • Rx’s written per week – 97.7 (155.5) Ko et al. JAMIA 2007; 14: 56-6434
  35. 35. Practitioners’ Views of Alerts Prescribers’ Views on DDI Alerts Mean Response I am satisfied with the accuracy of DDI alerting system 3.1 DDI alerts provide me with information I already know 3.4 The DDI system provides alerts that seems to be just about exactly what I need 2.7 DDI alerts change my initial prescribing decisions 1.9 1= strongly disagree; 2 = disagree; 3 = neither disagree or agree; 4 = agree; 5 = strongly agree 35
  36. 36. Attitudes Toward Improving DDI Alerts Attribute Mean Response DDI alerts should be accompanied by management alternatives 3.8 DDI alerts should be accompanied by more detailed information about the interaction 3.7 DDI alerts should only appear once in the order entry process 3.6 DDI alerts are presented in a useful format 3.2 1= strongly disagree; 2 = disagree; 3 = neither disagree or agree; 4 = agree; 5 = strongly agree 36
  37. 37. Top Ranked Changes to VA’s Alerting System Change Weighted Preference Score Provide management options for DDIs 1.53 Show DDI alerts one at a time 1.24 Make it more difficult to override lethal interactions 0.95 Eliminate all DDI alerts 0.05 Rank 1 = 3 points, Rank 2 = 2 points, Rank 3 = 1 point 37
  38. 38. “Asthma sufferer wins $28.6 million award” – Seattle Time (9/3/94) • 24 year old man on theophylline went to ER with an infection, prescribed ciprofloxicin by ER physician • Theophylline levels doubled, patient had permanent brain damage • Patient awarded $22.5 million in pain and suffering
  39. 39. Tranylcypromine (Parnate®) + Phenylpropanolamine (Tavist‐D®) • Patient on Parnate went to ER for URI: received Rx for Tavist-D® • Rx filled at his regular pharmacy (technician ignored computer warning) • Patient developed an acute hypertensive episode resulting in a stroke • Patient committed suicide, leaving a note that the disabilities induced by the stroke were intolerable Williams KG. Am J Health-Syst Pharm 1996;53:1709.
  40. 40. Current “Lists” of Important DDIs Source Purpose Systematic Review Expert Panel Consensus Process Classen 2011 / Leapfrog List Verify whether an inpatient COPE system has the potential to intercept critical DDIs Unknown Unknown Unknown CMS FTag 329‐ Unecessary Medications Medications requiring increased involvement from consultant pharmacists. Unknown Yes Unknown Malone 2004 To develop a list of clinically important DDIs in outpatient setting Yes; primary literature and tertiary references Yes Modified Delphi process Phansalkar 2012 / ONC List To reduce alert fatigue and describe the most clinically significant high‐priority DDIs Unclear Yes Mixed approach Pharmacy Quality Alliance Evaluate prescription drug plans and ambulatory/community pharmacists No No Yes van Roon 2005 / G‐standard Dutch database for CDS in Netherlands Yes Yes Yes
  41. 41. Rationale for Changing the Approach • Drug interaction clinical decision support should improve patient safety • Instead…. • Evidence lacking to support effectiveness • Excessive irrelevant alerts • Wide variation across health systems for DDI CDS • Pandemic clinician annoyance • What’s needed • Guiding principles for evidence‐based, clinically relevant, consistent alerts with improved usability • Evidence of effectiveness
  42. 42. Rationale for Changing the Approach • Concerns about process used to generate current “lists” • No well‐defined, broadly accepted, uniform standard for rating: • Strength (quality) of DDI evidence • Strength of recommendations for patient risk management • Concerns about liability
  43. 43. AHRQ Conference Series • DDI CDS conference series to: • Develop guidelines for systematic appraisal of DDI evidence (Evidence Workgroup) • Recommend principles for including DDIs in CDS (Content Workgroup) • Establish preferred strategies for presenting DDI CDS (Usability Workgroup) • Consensus recommendations by international experts https://sites.google.com/site/ddiconferenceseriessite
  44. 44. Project At A Glance
  45. 45. DDI CDS Conference Website https://sites.google.com/site/ddiconferenceseriessite/home
  46. 46. DRug Interaction eVidence Evaluation (DRIVE) Instrument Category Evidence Sufficient Sufficient evidence to evaluate a clinically relevant drug interaction One or more of the following: • Well‐designed and executed prospective controlled studies • Well‐designed and executed retrospective controlled studies • Case reports or series demonstrating probable or highly probable causality of an interaction (DIPS score of 5‐10)* • Reasonable extrapolation on the basis of: • Studies of drugs with similar pharmacologic properties • Studies with in vitro substrate data • Human genetic polymorphism studies * Drug Interaction Probability Scale; Horn et al. Ann Pharmacother 2007;41:674‐80.
  47. 47. DRug Interaction eVidence Evaluation (DRIVE) Instrument Category Evidence Insufficient Insufficient evidence to evaluate a clinically relevant drug interaction One or more of the following, without supporting evidence from the “sufficient” category: • Extrapolation on the basis of studies with in vitro inhibitor or inducer data • Case reports or series demonstrating only possible or doubtful causality of an interaction (DIPS score of <5) • Studies of poor design or execution • Hypotheses‐generating research methods • Unsupported data on file or unsupported recommendations from product manufacturer • Animal data * Drug Interaction Probability Scale; Horn et al. Ann Pharmacother 2007;41:674‐80.
  48. 48. AHRQ Conference Series Workgroup Recommendations • Establish national expert consensus panel • Oversight by national organization • Develop and maintain standard set of DDIs for CDS • Employ transparent, systematic, evidence‐driven process • Grade quality of evidence • Incorporate expert and clinical advice • Provide graded recommendations for risk management • Collect and incorporate user feedback • Ongoing reevaluation and updates
  49. 49. Transparent, Systematic Process for a Standard Set of DDIs 1. Evidence Synthesis & Grading 2. Expert Advice National DDI Expert Panel Oversight by Central Organization 3. Consensus Graded Recommendations 6. Reevaluation & Updates 5. Stakeholder Feedback 4. CDS Implementation
  50. 50. Support Agency for Healthcare Research and Quality • Grant #1R13HS021826‐01 (PI –Malone) • Grant #1R13HS018307‐01 (PI –Malone) National Library of Medicine Grant #R01LM011838‐01 (PI – Boyce) Additional Support • Cerner • Epocrates • First Databank • Truven Health Analytics • Wolters Kluwer Health • Elsevier
  51. 51. Acknowledgements • Lisa Hines, PharmD, University of Arizona • Richard T. Scheife, PharmD, FCCP, Tufts University • Darrell R. Abernethy, MD, PhD, Food and Drug Administration • Richard Boyce, PhD, University of Pittsburgh • Clarissa Borst, PharmD, Elsevier • Sophie Chung, PharmD, Epocrates, athenahealth, Inc. • Susan Comes, PharmD, Epocrates, athenahealth, Inc. • John Horn, PharmD, University of Washington • Gretchen Jones, PharmD, (formerly) Epocrates, athenahealth, Inc. • Jeremiah Momper, PharmD, PhD, University of California, San Diego • Alissa Rich, PharmD, MBA, (formerly) Cancer Treatment Centers of America • Stephen J Sklar, PharmD, Wolters Kluwer Health • Christine D Sommer, PharmD, FDB (First Databank, Inc.) • Tricia Lee Wilkins, PharmD, MS, Office of the National Coordinator for Health Information Technology • Michael A Wittie, MPH, Office of the Chief Medical Officer, Office of the National Coordinator for Health Information Technology • Samantha K Wong, BSPharm, RPh, Cerner
  52. 52. Acknowledgements • Lisa Hines, PharmD, University of Arizona • Hugh Tilson, MD, DrPH, University of North Carolina • David W Bates, MD, Harvard Medical School • Joseph T Hanlon, PharmD, MS, University of Pittsburgh • Philip Hansten, PharmD, University of Washington • Amy L Helwig, MD, MS, Office of the National Coordinator for HIT • Stefanie Higby‐Baker, RPh, MHA, CPHIT, Cerner Multum • Shiew‐Mei Huang, PhD, Food and Drug Administration • David R Hunt, MD, FACS, Office of the National Coordinator for HIT • Marianne le Comte, PharmD, Royal Dutch Association for the Advancement of Pharmacy • Karl Matuszewski, MS, PharmD, FDB (First Databank, Inc.) • Gerald McEvoy, PharmD, ASHP • Anthony Perre, MD, Cancer Treatment Centers of America • Lynn Pezzullo, RPh, CPEHR, Pharmacy Quality Alliance • John Poikonen, PharmD, MedVentive • Kathy Vieson, PharmD, Elsevier Clinical Solutions • David M Weinstein, RPh, PhD, Lexicomp, Wolters Kluwer Health • Michael A Wittie, MPH, Office of the National Coordinator for HIT
  53. 53. Acknowledgements • Thomas H Payne, MD, FACP, University of Washington • Bruce W Chaffee, PharmD, University of Michigan Health System • Raymond C Chan, PharmD, Sentara • Peter A Glassman, MBBS, VA, Greater Los Angeles Healthcare System • Brian Galbreth, PharmD, PeaceHealth Southwest Medical Center • Christian Hartman, PharmD, MBA, FSMSO, Pharmacy OneSource, Wolters Kluwer Health • Seth Hartman, PharmD, Oregon Health & Science University • Joan Kapusnik‐Uner, PharmD, FDB (First Databank, Inc.) • Gilad J Kuperman, MD, PhD, New York‐Presbyterian Hospital • Gordon Mann, RPh, Clinical Informatics, Epic • Shobha Phansalkar, RPh, PhD, Wolters Kluwer Health (formerly with Partners Healthcare System) • Alissa Russ, PhD, Roudebush VA Medical Center • Hugh Ryan, MD, Cerner Corporation • Howard Strasberg, MD, MS, Wolters Kluwer Health • Amanda Sullins, PharmD, Cerner • Vicki Tamis, PharmD, BCPS, PeaceHealth Southwest Medical Center • Heleen van der Sijs, PharmD, PhD, Erasmus Medical Center
  54. 54. Thanks! Questions and Comments? Answers (Even Better)?!

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