Sensitivity and specificity of International Classification of Diseases algorithms (ICD-9 and ICD-10) used to identify opioid-related overdose cases: A systematic review and an example of estimation using Bayesian latent class models in the absence of gold standards.

Autor: Mbutiwi FIN; Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada.; Département de médecine sociale et préventive, École de santé publique, Université de Montréal, Montréal, Québec, Canada.; Faculty of Medicine, University of Kikwit, Kikwit, Kwilu, Democratic Republic of the Congo.; Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Saint-Hyacinthe, Québec, Canada.; Centre de recherche en santé publique de l'Université de Montréal et du CIUSSS du Centre-sud-de-l'île-de-Montréal (CReSP), Montréal, Québec, Canada., Yapo APJ; Département de médecine sociale et préventive, École de santé publique, Université de Montréal, Montréal, Québec, Canada., Toirambe SE; Département de médecine sociale et préventive, École de santé publique, Université de Montréal, Montréal, Québec, Canada., Rees E; Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada.; National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada.; Centre for Surveillance and Applied Research, Health Promotion and Chronic Disease Prevention Branch, Public Health Agency of Canada, Ottawa, Ontario, Canada.; Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Saint-Hyacinthe, Québec, Canada., Plouffe R; Centre for Surveillance and Applied Research, Health Promotion and Chronic Disease Prevention Branch, Public Health Agency of Canada, Ottawa, Ontario, Canada., Carabin H; Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada. helene.carabin@umontreal.ca.; Département de médecine sociale et préventive, École de santé publique, Université de Montréal, Montréal, Québec, Canada. helene.carabin@umontreal.ca.; Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Saint-Hyacinthe, Québec, Canada. helene.carabin@umontreal.ca.; Centre de recherche en santé publique de l'Université de Montréal et du CIUSSS du Centre-sud-de-l'île-de-Montréal (CReSP), Montréal, Québec, Canada. helene.carabin@umontreal.ca.
Jazyk: angličtina
Zdroj: Canadian journal of public health = Revue canadienne de sante publique [Can J Public Health] 2024 Oct; Vol. 115 (5), pp. 770-783. Date of Electronic Publication: 2024 Jul 31.
DOI: 10.17269/s41997-024-00915-4
Abstrakt: Objectives: This study aimed to summarize validity estimates of International Classification of Diseases (ICD) codes in identifying opioid overdose (OOD) among patient data from emergency rooms, emergency medical services, inpatient, outpatient, administrative, medical claims, and mortality, and estimate the sensitivity and specificity of the algorithms in the absence of a perfect reference standard.
Methods: We systematically reviewed studies published before December 8, 2023, and identified with Medline and Embase. Studies reporting sufficient details to recreate a 2 × 2 table comparing the ICD algorithms to a reference standard in diagnosing OOD-related events were included. We used Bayesian latent class models (BLCM) to estimate the posterior sensitivity and specificity distributions of five ICD-10 algorithms and of the imperfect coroner's report review (CRR) in detecting prescription opioid-related deaths (POD) using one included study.
Results: Of a total of 1990 studies reviewed, three were included. The reported sensitivity estimates of ICD algorithms for OOD were low (range from 25.0% to 56.8%) for ICD-9 in diagnosing non-fatal OOD-related events and moderate (72% to 89%) for ICD-10 in diagnosing POD. The last included study used ICD-9 for non-fatal and fatal and ICD-10 for fatal OOD-related events and showed high sensitivity (i.e. above 97%). The specificity estimates of ICD algorithms were good to excellent in the three included studies. The misclassification-adjusted ICD-10 algorithm sensitivity estimates for POD from BLCM were consistently higher than reported sensitivity estimates that assumed CRR was perfect.
Conclusion: Evidence on the performance of ICD algorithms in detecting OOD events is scarce, and the absence of bias correction for imperfect tests leads to an underestimation of the sensitivity of ICD code estimates.
(© 2024. The Author(s).)
Databáze: MEDLINE
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