Pharmacopsychiatry 2020; 53(05): 220-227
DOI: 10.1055/a-1156-4193
Original Paper

Potential Drug interactions with Drugs used for Bipolar Disorder: A Comparison of 6 Drug Interaction Database Programs

Scott Monteith
1   Michigan State University College of Human Medicine, Traverse City Campus, Traverse City, MI, USA
,
Tasha Glenn
2   ChronoRecord Association, Fullerton, CA, USA
,
Michael Gitlin
3   Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles (UCLA), Los Angeles, CA, USA
,
Michael Bauer
4   Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Medical Faculty, Technische Universität Dresden, Dresden, Germany
› Author Affiliations

Abstract

Background Patients with bipolar disorder frequently experience polypharmacy, putting them at risk for clinically significant drug-drug interactions (DDI). Online drug interaction database programs are used to alert physicians, but there are no internationally recognized standards to define DDI. This study compared the category of potential DDI returned by 6 commercial drug interaction database programs for drug interaction pairs involving drugs commonly prescribed for bipolar disorder.

Methods The category of potential DDI provided by 6 drug interaction database programs (3 subscription, 3 open access) was obtained for 125 drug interaction pairs. The pairs involved 103 drugs (38 psychiatric, 65 nonpsychiatric); 88 pairs included a psychiatric and nonpsychiatric drug; 37 pairs included 2 psychiatric drugs. Every pair contained at least 1 mood stabilizer or antidepressant. The category provided by 6 drug interaction database programs was compared using percent agreement and Fleiss kappa statistic of interrater reliability.

Results For the 125 drug pairs, the overall percent agreement among the 6 drug interaction database programs was 60%; the Fleiss kappa agreement was slight. For drug interaction pairs with any category rating of severe (contraindicated), the kappa agreement was moderate. For drug interaction pairs with any category rating of major, the kappa agreement was slight.

Conclusion There is poor agreement among drug interaction database programs for the category of potential DDI involving psychiatric drugs. Drug interaction database programs provide valuable information, but the lack of consistency should be recognized as a limitation. When assistance is needed, physicians should check more than 1 drug interaction database program.

Supporting Information Appendix 1



Publication History

Received: 30 December 2019
Received: 05 April 2020

Accepted: 06 April 2020

Article published online:
30 April 2020

© 2020. Thieme. All rights reserved.

© Georg Thieme Verlag KG
Stuttgart · New York

 
  • References

  • 1 FDA. Preventable adverse drug reactions: a focus on drug interactions. 2018. Accessed at https://www.fda.gov/drugs/drug-interactions-labeling/preventable-adverse-drug-reactions-focus-drug-interactions#ADRs:%20Prevalence%20and%20Incidence Accessed: Dec. 5, 2019
  • 2 Gören JL, Tewksbury A. Drug interactions and polypharmacy. In: Ritsner MS ed. Polypharmacy in Psychiatry Practice, Volume I. Multiple Medication Use Strategies. Dordrecht: Springer; 2013: 45-74
  • 3 Magro L, Moretti U, Leone R. Epidemiology and characteristics of adverse drug reactions caused by drug-drug interactions. Expert Opin Drug Saf 2012; 11: 83-94
  • 4 Bauer M, Monteith S, Geddes J. et al. Automation to optimise physician treatment of individual patients: examples in psychiatry. Lancet Psychiatry 2019; 6: 338-349
  • 5 Scheife RT, Hines LE, Boyce RD. et al. Consensus recommendations for systematic evaluation of drug-drug interaction evidence for clinical decision support. Drug Saf 2015; 38: 197-206
  • 6 Tilson H, Hines LE, McEvoy G. et al. Recommendations for selecting drug-drug interactions for clinical decision support. Am J Health Syst Pharm 2016; 73: 576-585
  • 7 Grizzle AJ, Horn J, Collins C. et al. Identifying common methods used by drug interaction experts for finding evidence about potential drug-drug interactions: web-based survey. J Med Internet Res 2019; 21: e11182
  • 8 Kongsholm GG, Nielsen AK, Damkier P. Drug interaction databases in medical literature: transparency of ownership, funding, classification algorithms, level of documentation, and staff qualifications. A systematic review. Eur J Clin Pharmacol 2015; 71: 1397-1402
  • 9 Romagnoli KM, Nelson SD, Hines L. et al. Information needs for making clinical recommendations about potential drug-drug interactions: a synthesis of literature review and interviews. BMC Med Inform Decis Mak 2017; 17: 21
  • 10 Bourgeois FT, Shannon MW, Valim C. et al. Adverse drug events in the outpatient setting: an 11-year national analysis. Pharmacoepidemiol Drug Saf 2010; 19: 901-910
  • 11 English BA, Dortch M, Ereshefsky L. et al. Clinically significant psychotropic drug-drug interactions in the primary care setting. Curr Psychiatry Rep 2012; 14: 376-390
  • 12 Guthrie B, Makubate B, Hernandez-Santiago V. et al. The rising tide of polypharmacy and drug-drug interactions: population database analysis 1995-2010. BMC Med 2015; 13: 74
  • 13 Ong MS, Olson KL, Chadwick L. et al. The impact of provider networks on the co-prescriptions of interacting drugs: a claims-based analysis. Drug Saf 2017; 40: 263-272
  • 14 Tannenbaum C, Sheehan NL. Understanding and preventing drug-drug and drug-gene interactions. Expert Rev Clin Pharmacol 2014; 7: 533-544
  • 15 Bauer M, Andreassen OA, Geddes JR. et al. Areas of uncertainties and unmet needs in bipolar disorders: clinical and research perspectives. Lancet Psychiatry 2018; 5: 930-939
  • 16 Bauer M, Glenn T, Alda M. et al. Drug treatment patterns in bipolar disorder: analysis of long-term self-reported data. Int J Bipolar Disord 2013; 1: 5
  • 17 Golden JC, Goethe JW, Woolley SB. Complex psychotropic polypharmacy in bipolar disorder across varying mood polarities: A prospective cohort study of 2712 inpatients. J Affect Disord 2017; 221: 6-10
  • 18 Greil W, Häberle A, Haueis P. et al. Pharmacotherapeutic trends in 2231 psychiatric inpatients with bipolar depression from the International AMSP Project between 1994 and 2009. J Affect Disord 2012; 136: 534-542
  • 19 Peselow ED, Naghdechi L, Pizano D. et al. Polypharmacy in maintenance of bipolar disorder. Clin Neuropharmacol 2016; 39: 132-134
  • 20 Rej S, Herrmann N, Shulman K. et al. Current psychotropic medication prescribing patterns in late-life bipolar disorder. Int J Geriatr Psychiatry 2017; 32: 1459-1465
  • 21 Weinstock LM, Gaudiano BA, Epstein-Lubow G. et al. Medication burden in bipolar disorder: a chart review of patients at psychiatric hospital admission. Psychiatry Res 2014; 216: 24-30
  • 22 Goldberg JF, Brooks JO, Kurita K. et al. Depressive illness burden associated with complex polypharmacy in patients with bipolar disorder: findings from the STEP-BD. J Clin Psychiatry 2009; 70: 155-162
  • 23 de Leon J, Spina E. Possible pharmacodynamic and pharmacokinetic drug-drug interactions that are likely to be clinically relevant and/or frequent in bipolar disorder. Curr Psychiatry Rep 2018; 20: 17
  • 24 Finley PR. Drug interactions with lithium: an update. Clin Pharmacokinet 2016; 55: 925-941
  • 25 Tondo L, Alda M, Bauer M. et al. Clinical use of lithium salts: guide for users and prescribers. Int J Bipolar Disord 2019; 7: 16
  • 26 Johannessen Landmark C, Patsalos PN. Drug interactions involving the new second- and third-generation antiepileptic drugs. Expert Rev Neurother 2010; 10: 119-140
  • 27 Spina E, Pisani F, de Leon J. Clinically significant pharmacokinetic drug interactions of antiepileptic drugs with new antidepressants and new antipsychotics. Pharmacol Res 2016; 106: 72-86
  • 28 Spina E, Trifirò G, Caraci F. Clinically significant drug interactions with newer antidepressants. CNS Drugs 2012; 26: 39-67
  • 29 Wijesinghe R. A review of pharmacokinetic and pharmacodynamic interactions with antipsychotics. Ment Health Clin 2016; 6: 21-27
  • 30 Kemp DE, Sylvia LG, Calabrese JR. et al. General medical burden in bipolar disorder: findings from the LiTMUS comparative effectiveness trial. Acta Psychiatr Scand 2014; 129: 24-34
  • 31 Weber NS, Fisher JA, Cowan DN. et al. Psychiatric and general medical conditions comorbid with bipolar disorder in the National Hospital Discharge Survey. Psychiatr Serv 2011; 62: 1152-1158
  • 32 Monteith S, Glenn T. A comparison of potential psychiatric drug interactions from six drug interaction database programs. Psychiatry Res 2019; 275: 366-372
  • 33 Clinical Pharmacology Drug Interaction. 2019 https://www.clinicalkey.com/pharmacology Accessed: Dec. 5, 2019
  • 34 Lexicomp. 2019 https://www.wolterskluwercdi.com/lexicomp-online/user-guide/tools-interactions Accessed: Dec. 5, 2019
  • 35 IBM Micromedex Medication Management. 2019 ttps://www.ibm.com/products/micromedex-with-watson Accessed: Dec. 5, 2019
  • 36 Drugs.com. Drug Interactions Checker. 2019 https://www.drugs.com/drug_interactions.html Accessed: Dec. 5, 2019
  • 37 Medscape 2019 https://reference.medscape.com/drug-interactionchecker Accessed: Dec. 5, 2019
  • 38 Epocrates. 2019 https://online.epocrates.com/interaction-check Accessed: Dec. 5, 2019
  • 39 Barrett M, Keating A, Lynch D. et al. Clozapine patients at the interface between primary and secondary care. Pharmacy (Basel) 2018; 6: 19
  • 40 Hefner G, Unterecker S, Ben-Omar N. et al. Prevalence and type of potential pharmacokinetic drug-drug interactions in old aged psychiatric patients. Contemp Behav Health Care 2015; 1: 3-10
  • 41 Holm J, Eiermann B, Eliasson E. et al. A limited number of prescribed drugs account for the great majority of drug-drug interactions. Eur J Clin Pharmacol 2014; 70: 1375-1383
  • 42 Jazbar J, Locatelli I, Horvat N. et al. Clinically relevant potential drug-drug interactions among outpatients: A nationwide database study. Res Social Adm Pharm 2018; 14: 572-580
  • 43 Soerensen AL, Nielsen LP, Poulsen BK. et al. Potentially inappropriate prescriptions in patients admitted to a psychiatric hospital. Nord J Psychiatry 2016; 70: 365-373
  • 44 Zorina OI, Haueis P, Greil W. et al. Comparative performance of two drug interaction screening programmes analysing a cross-sectional prescription dataset of 84 625 psychiatric inpatients. Drug Saf 2013; 36: 247-258
  • 45 Kinsella KJ. Drug-drug interactions and psychiatric medication. In: Grossberg GT, Kinsella LJ (Eds.) Clinical Psychopharmacology for Neurologists. Switzerland: Springer; 2018: 181-200
  • 46 Smolders EJ, de Kanter CT, de Knegt RJ. et al. Drug-drug interactions between direct-acting antivirals and psychoactive medications. Clin Pharmacokinet 2016; 55: 1471-1494
  • 47 Yap KY, Tay WL, Chui WK. et al. Clinically relevant drug interactions between anticancer drugs and psychotropic agents. Eur J Cancer Care (Engl) 2011; 20: 6-32
  • 48 Kheshti R, Aalipour M, Namazi S. A comparison of five common drug-drug interaction software programs regarding accuracy and comprehensiveness. J Res Pharm Pract 2016; 5: 257-263
  • 49 McEvoy DS, Sittig DF, Hickman TT. et al. 2017. Variation in high-priority drug-drug interaction alerts across institutions and electronic health records. J Am Med Inform Assoc 2017; 24: 331-338
  • 50 Patel RI, Beckett RD. Evaluation of resources for analyzing drug interactions. J Med Libr Assoc 2016; 104: 290-295
  • 51 Clincalc.com. The Top 300 of 2019. 2019 https://clincalc.com/DrugStats/Top300Drugs.aspx Accessed: Dec. 5, 2019
  • 52 Urquhart L. Top drugs and companies by sales in 2018. Nature Reviews Drug Discovery 2019; 18: 245
  • 53 McHugh ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb) 2012; 22: 276-282
  • 54 Fleiss JL. Measuring nominal scale agreement among many raters. Psychol Bull 1971; 76: 378
  • 55 Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977; 33: 159-174
  • 56 Gamer M, Fellows J, Lemon I. et al. 2019. Package “irr.” Various coefficients of interrater reliability and agreement. https://cran.r-project.org/web/packages/irr/irr.pdf Accessed: Dec. 5, 2019
  • 57 Flockhart DA. Dietary restrictions and drug interactions with monoamine oxidase inhibitors: an update. J Clin Psychiatry 2012; 73 Suppl 1 17-24
  • 58 Abarca J, Colon LR, Wang VS. et al. Evaluation of the performance of drug-drug interaction screening software in community and hospital pharmacies. J Manag Care Pharm 2006; 12: 383-389
  • 59 Vitry A. Comparative assessment of four drug interaction compendia. Br J Clin Pharmacol 2007; 63: 709-714
  • 60 Wang LM, Wong M, Lightwood JM. et al. Black box warning contraindicated comedications: concordance among three major drug interaction screening programs. Ann Pharmacother 2010; 44: 28-34
  • 61 Acton EK, Willis AW, Gelfand MA. et al. Poor concordance among drug compendia for proposed interactions between enzyme-inducing antiepileptic drugs and direct oral anticoagulants. Pharmacoepidemiol Drug Saf 2019; 28: 1534-1538
  • 62 Ekstein D, Tirosh M, Eyal Y. et al. 2015; Drug interactions involving antiepileptic drugs: assessment of the consistency among three drug compendia and FDA-approved labels. Epilepsy Behav 2015 44: 218-224
  • 63 Liu X, Hatton RC, Zhu Y. et al. Consistency of psychotropic drug-drug interactions listed in drug monographs. J Am Pharm Assoc 2017; 57: 698-703
  • 64 Schjøtt J, Schjøtt P, Assmus J. Analysis of consensus among drug interaction databases with regard to combinations of psychotropics. Basic Clin Pharmacol Toxicol 2020; 126: 126-132
  • 65 Bykov K, Gagne JJ. Generating evidence of clinical outcomes of drug-drug interactions. Drug Saf 2017; 40: 101-103
  • 66 Schrieber SJ, Pfuma-Fletcher E, Wang X. et al. Considerations for biologic product drug-drug interactions: a regulatory perspective. Clin Pharmacol Ther 2019; 105: 1332-1334
  • 67 Sutherland JJ, Daly TM, Liu X. et al. Co-prescription trends in a large cohort of subjects predict substantial drug-drug interactions. PLoS One 2015; 10: e0118991
  • 68 Roblek T, Vaupotic T, Mrhar A. et al. Drug-drug interaction software in clinical practice: a systematic review. Eur J Clin Pharmacol 2015; 71: 131-142
  • 69 Boyce RD, Collins C, Clayton M. et al. Inhibitory metabolic drug interactions with newer psychotropic drugs: inclusion in package inserts and influences of concurrence in drug interaction screening software. Ann Pharmacother 2012; 46: 1287-1298
  • 70 Coletti DJ, Stephanou H, Mazzola N. et al. Patterns and predictors of medication discrepancies in primary care. J Eval Clin Pract 2015; 21: 831-839
  • 71 Linsky A, Simon SR. Medication discrepancies in integrated electronic health records. BMJ Qual Saf 2013; 22: 103-109
  • 72 Albano ME, Bostwick JR, Ward KM. et al. Discrepancies identified through a telephone-based, student-led initiative for medication reconciliation in ambulatory psychiatry. J Pharm Pract 2018; 31: 304-311
  • 73 Dornquast C, Tomzik J, Reinhold T. et al. To what extent are psychiatrists aware of the comorbid somatic illnesses of their patients with serious mental illnesses? – a cross-sectional secondary data analysis. BMC Health Serv Res 2017; 17: 162
  • 74 Madden JM, Lakoma MD, Rusinak D. et al. Missing clinical and behavioral health data in a large electronic health record (EHR) system. J Am Med Inform Assoc 2016; 23: 1143-1149
  • 75 O'Neill B, Kalia S, Aliarzadeh B. et al. Agreement between primary care and hospital diagnosis of schizophrenia and bipolar disorder: a cross-sectional, observational study using record linkage. PLoS One 2019; 14: e0210214
  • 76 Bauer R, Glenn T, Alda M. et al. Antidepressant dosage taken by patients with bipolar disorder: factors associated with irregularity. Int J Bipolar Disord 2013; 1: 26
  • 77 Pilhatsch M, Glenn T, Rasgon N. et al. Regularity of self-reported daily dosage of mood stabilizers and antipsychotics in patients with bipolar disorder. Int J Bipolar Disord 2018; 6: 10
  • 78 Bauer M, Glenn T, Alda M. et al. Trajectories of adherence to mood stabilizers in patients with bipolar disorder. Int J Bipolar Disord 2019; 7: 19
  • 79 Sutherland JJ, Daly TM, Jacobs K. et al. Medication exposure in highly adherent psychiatry patients. ACS Chem Neurosci 2018; 9: 555-562
  • 80 Ereshefsky L. Drug-drug interactions with the use of psychotropic medications. Interview by Diane M. Sloan. CNS Spectr 2009; 14 (8 Suppl Q and A Forum) 1-8
  • 81 Eguale T, Buckeridge DL, Verma A. et al. Association of off-label drug use and adverse drug events in an adult population. JAMA Intern Med 2016; 176: 55-63
  • 82 Vijay A, Becker JE, Ross JS. Patterns and predictors of off-label prescription of psychiatric drugs. PLoS One 2018; 13: e0198363
  • 83 Wong J, Motulsky A, Abrahamowicz M. et al. Off-label indications for antidepressants in primary care: descriptive study of prescriptions from an indication based electronic prescribing system. BMJ 2017; 356: j603
  • 84 Hayward J, Thomson F, Milne H. et al. Too much, too late: mixed methods multi-chanel video recording study of computerized decision support systems and GP prescribing. J. Am Med Inform Assoc 2013; 20: e76-e84
  • 85 Slight SP, Eguale T, Amato MG. et al. The vulnerabilities of computerized physician order entry systems: a qualitative study. J Am Med Inform Assoc 2016; 23: 311-316
  • 86 Bryant AD, Fletcher GS, Payne TH. Drug interaction alert override rates in the Meaningful Use era: no evidence of progress. Appl. Clin. Inform 2014; 5: 802-813
  • 87 Kuperman GJ, Bobb A, Payne TH. et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc 2007; 14: 29-40
  • 88 Armahizer MJ, Kane-Gill SL, Smithburger PL. Comparing drug-drug interaction severity ratings between bedside clinicians and proprietary databases. ISRN Critical Care 2013; Article ID 347346 DOI: 10.5402/2013/347346 Accessed: Dec. 5, 2019.
  • 89 Phillips KA, Citrome L. Inaccurate prescribing warnings in electronic medical record systems: results from an American Society of Clinical Psychopharmacology membership survey. J. Clin. Psychiatry 2018; 80: 18ac12536
  • 90 Baysari MT, Tariq A, Day RO. et al. Alert override as a habitual behavior – a new perspective on a persistent problem. J Am Med Inform Assoc 2017; 24: 409-412
  • 91 Lyell D, Magrabi F, Raban MZ. et al. Automation bias in electronic prescribing. BMC Med Inform Decis Mak 2017; 17: 28
  • 92 Glassman PA, Simon B, Belperio P. et al. Improving recognition of drug interactions: benefits and barriers to using automated drug alerts. Med Care 2002; 40: 1161-1171
  • 93 Ko Y, Malone DC, Skrepnek GH. et al. Prescribers’ knowledge of and sources of information for potential drug-drug interactions: a postal survey of US prescribers. Drug Saf 2008; 31: 525-536
  • 94 FDA. Approved Drug Products with Therapeutic Equivalence Evaluations (Orange Book). 2019 https://www.fda.gov/drugs/drug-approvals-and-databases/approved-drug-products-therapeutic-equivalence-evaluations-orange-book Accessed: Dec. 5, 2019
  • 95 FDA. Purple Book: Lists of Licensed Biological Products with Reference Product Exclusivity and Biosimilarity or Interchangeability Evaluations. 2019 https://www.fda.gov/drugs/therapeutic-biologics-applications-bla/purple-book-lists-licensed-biological-products-reference-product-exclusivity-and-biosimilarity-or Accessed: Dec. 5, 2019
  • 96 Bauer M, Glenn T, Conell J. et al. Common use of dietary supplements for bipolar disorder: A naturalistic, self-reported study. Int J Bipolar Disord 2015; 3: 29
  • 97 Ridgely MS, Greenberg MD. Too many alerts, too much liability. St. Louis University Journal of Health Law & Policy. 2012; 5: 257-296
  • 98 Monteith S, Glenn T. Searching online to buy commonly prescribed psychiatric drugs. Psychiatry Res 2018; 260: 248-254
  • 99 Monteith S, Glenn T, Bauer R. et al Availability of prescription drugs for bipolar disorder at online pharmacies. J Affect Disord 2016; 193: 59-65