Detection of serious adverse drug reactions using diagnostic codes in the International Statistical Classification of Diseases and Related Health Problems
Main Article Content
Keywords
diagnostic codes, International Statistical Classification of Diseases and Related Health Problems, hospital, pharmacovigilance, serious adverse drug reactions
Abstract
Canadian hospitals are legally required to report serious adverse drug reactions (ADRs). This study aimed to assess the ability to detect serious ADRs from diagnostic codes and the potential benefit of adding stand-alone diagnostic codes to the regular process for detecting serious ADRs. In this descriptive study, clinical pharmacists and a reference work on drug-induced diseases allowed to identify diagnostic codes in the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10 CA), reflecting clinical manifestations related to an ADR. Records for admissions to a large urban mother–child hospital in the fiscal year 2018–2019, as coded by medical archivists, were analysed. Of 69 ICD-10-CA diagnostic codes reflecting an ADR identified, 38 were included in the detailed analysis of patient records and 18 (which appeared in 130 admissions) deemed to indicate a serious ADR. Among the 130 admissions analysed, 70 serious ADRs were identified, of which 52 were previously detected by the regular process and 18 were not, increasing the detection of serious ADRs by 34.6% (18/52). These 18 serious ADRs were newly identified from 11 of the 18 codes reflecting clinical manifestation of a serious ADR. Adding ICD-10-CA diagnostic codes not associated with external cause codes can increase the capacity to detect serious ADRs in hospitals. Over a 12-month period, the use of 11 such diagnostic codes increased the detection capacity for serious ADRs by 34.6%.
References
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15. Rault P, Necsoiu D, Desjardins I, et al. Preparing for Vanessa’s Law: Collaboration between the medical records and pharmacy departments at a Canadian hospital center. J Popul Ther Clin Pharmacol. 2019;26(2):e5–e13. https://doi. org/10.15586/jptcp.v26i2.607
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18. Kuklik N, Stausberg J, Jöckel KH. Adverse drug events in German hospital routine data: A validation of International Classification of Diseases, 10th revision (ICD-10) diagnostic codes. PLoS One. 2017 Nov;12(11):e0187510. https://doi.org/ 10.1371/journal.pone.0187510
19. Kuklik N, Stausberg J, Amiri M, et al. Improving drug safety in hospitals: A retrospective study on the potential of adverse drug events coded in routine data. BMC Health Serv Res. 2019 Aug;19(1):555. https://doi.org/10.1186/s12913-019-4381-x
20. Parameswaran Nair N, Chalmers L, Peterson GM, et al. Prospective identification versus administrative coding of adverse drug reaction- related hospitalizations in the elderly: A comparative analysis. Pharmacoepidemiol Drug Saf. 2018 Nov;27(11):1281–85. https://doi.org/10.1002/ pds.4667
21. Bellis JR, Kirkham JJ, Nunn AJ, Pirmohamed M. Clinical coding of prospectively identified paediatric adverse drug reactions – A retrospective review of patient records. BMC Pharmacol Toxicol. 2014 Dec;15:72. https://doi.org/10.1186/ 2050-6511-15-72
22. McMaster C, Liew D, Keith C, et al. A machine-learning algorithm to optimise auto-mated adverse drug reaction detection from clinical coding. Drug Saf. 2019 Jun;42(6):721–25. https://doi.org/10.1007/s40264-018-00794-y
2. Soyer J, Necsoiu D, Lebel D, et al. Codage des séjours patients par les archivistes médicaux du centre hospitalier universitaire Sainte-Justine: une source inestimable de données pour le phar-macien. Pharmactuel. 2018;51(4):237–45.
3. Ministère de la Santé et des Services sociaux du Québec. Feuille sommaire d’hospitalisation [Internet]. 2005 [cited 2020 Feb 15]. Available from: http://msssa4.msss.gouv.qc.ca/intra/formres.nsf/ c6dfb077f4130b4985256e38006a9ef0/48879ba6e-b1e905e85256ec10066c870
4. Soyer J, Necsoiu D, Lebel D, et al. Comprendre la Classification Internationale des Maladies et la Classification Canadienne des Interventions: exemples d’utilisation pour le pharmacien hos-pitalier. Abstract Presented at Congrès de l’Association des pharmaciens des établissements de santé du Québec (APES), 2018 April 25–27, Drummondville, QC.
5. Canadian Institute for Health Information. Codes and classifications [Internet]. [cited 2020 Feb 15]. Available from: https://www.cihi.ca/en/ codes-and-classifications
6. Collège de médecins du Québec. La tenue des dossiers par le médecin en centre hospitalier de soins généraux et spécialisés – Guide d’exercice [Internet]. 2005 Dec [cited 2020 Mar 30]. Available from: http://www.cmq.org/publications-pdf/p-1-2005-12-01-fr-tenue-des-dossiers-par-medecin-en-centre-hospitalier-de-soins-generaux-et-specialises.pdf
7. Canadian Institute for Health Information. Canadian coding standards for version 2018 ICD-10-CA and CCI [Internet]. Ottawa, ON; 2018 [cited 2020 Apr 2]. Available from: https:// secure.cihi.ca/free_products/CodingStandards_ v2018_EN.pdf
8. Ministère de la Santé et des Services sociaux du Québec. Cadre normatif du système MED-ÉCHO [Internet]. 1987 [revised 2019 Apr; cited 2020 Mar 23]. Available from: https://publications.msss. gouv.qc.ca/msss/fichiers/2000/00-601.pdf
9. Tisdale JE, Douglas MA. Drug-induced diseases: Prevention, detection and management. 3rd ed. Bethesda, MD: American Society of Health-System pharmacists; 2018.
10. Régie de l’assurance maladie du Québec (RAMQ). Facturation: Répertoire des diagnostics [Internet]. [cited 2020 Feb 15]. Available from: https://www. ramq.gouv.qc.ca/fr/professionnels/medecins-spe-cialistes/facturation/repertoire-diagnostics/Pages/ repertoire-diagnostics.aspx
11. Canadian Institute for Health Information. International statistical classification of diseases and related health problems, tenth revision (ICD-10-CA) – Volume 1, Tabular List [Internet]. Ottawa, ON; 2009 [cited 2020 Apr 7]. Available from: http://sda.chass.utoronto.ca/sdaweb/cihi/ 2009to2011/clin/more_doc/version_2009_icd-10-ca_tabular_list_volume_1.pdf
12. Naranjo CA, Busto U, Sellers EM, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther. 1981;30(2): 239–45. https://doi.org/10.1038/clpt.1981.154
13. Skalli S, Lebel D, Bussières J-F. Classification internationale des maladies et pharmacovigilance: passage de la révision 9 à la révision 10 en étab-lissement de santé. Pharmactuel. 2011;44(1):42–7.
14. Soyer J, Necsoiu D, Desjardins I, et al. Identification of discrepancies between adverse drug reactions coded by medical records technicians and those reported by the pharmacovigilance team in pediatrics: An intervention to improve identification, reporting and coding. Arch Pediatr. 2019;26(7):400–06. https://doi.org/ 10.1016/j.arcped.2019.09.004
15. Rault P, Necsoiu D, Desjardins I, et al. Preparing for Vanessa’s Law: Collaboration between the medical records and pharmacy departments at a Canadian hospital center. J Popul Ther Clin Pharmacol. 2019;26(2):e5–e13. https://doi. org/10.15586/jptcp.v26i2.607
16. Hohl CM, Karpov A, Reddekopp L, et al. ICD-10 codes used to identify adverse drug events in administrative data: A systematic review. J Am Med Inform Assoc. 2014 May–Jun;21(3):547–57. https://doi.org/10.1136/amiajnl-2013-002116
17. Du W, Pearson SA, Buckley NA, et al. Diagnosis-based and external cause-based criteria to identify adverse drug reactions in hospital ICD-coded data: Application to an Australia population-based study. Public Health Res Pract. 2017;27(2):2721716. https://doi.org/10.17061/phrp 2721716
18. Kuklik N, Stausberg J, Jöckel KH. Adverse drug events in German hospital routine data: A validation of International Classification of Diseases, 10th revision (ICD-10) diagnostic codes. PLoS One. 2017 Nov;12(11):e0187510. https://doi.org/ 10.1371/journal.pone.0187510
19. Kuklik N, Stausberg J, Amiri M, et al. Improving drug safety in hospitals: A retrospective study on the potential of adverse drug events coded in routine data. BMC Health Serv Res. 2019 Aug;19(1):555. https://doi.org/10.1186/s12913-019-4381-x
20. Parameswaran Nair N, Chalmers L, Peterson GM, et al. Prospective identification versus administrative coding of adverse drug reaction- related hospitalizations in the elderly: A comparative analysis. Pharmacoepidemiol Drug Saf. 2018 Nov;27(11):1281–85. https://doi.org/10.1002/ pds.4667
21. Bellis JR, Kirkham JJ, Nunn AJ, Pirmohamed M. Clinical coding of prospectively identified paediatric adverse drug reactions – A retrospective review of patient records. BMC Pharmacol Toxicol. 2014 Dec;15:72. https://doi.org/10.1186/ 2050-6511-15-72
22. McMaster C, Liew D, Keith C, et al. A machine-learning algorithm to optimise auto-mated adverse drug reaction detection from clinical coding. Drug Saf. 2019 Jun;42(6):721–25. https://doi.org/10.1007/s40264-018-00794-y
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Jul 23, 2020
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Gosselin, A., Chabut, C., Duhamel, A., Desjardins, I., Lebel, D., & Bussières, J.-F. (2020). Detection of serious adverse drug reactions using diagnostic codes in the International Statistical Classification of Diseases and Related Health Problems. Journal of Population Therapeutics and Clinical Pharmacology, 27(3), e35-e48. https://doi.org/10.15586/jptcp.v27i3.705
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How to Cite
Gosselin, A., Chabut, C., Duhamel, A., Desjardins, I., Lebel, D., & Bussières, J.-F. (2020). Detection of serious adverse drug reactions using diagnostic codes in the International Statistical Classification of Diseases and Related Health Problems. Journal of Population Therapeutics and Clinical Pharmacology, 27(3), e35-e48. https://doi.org/10.15586/jptcp.v27i3.705