Validating methods used to identify non‐adherence adverse drug events in Canadian administrative health data

Aims Medication non‐adherence is a type of adverse drug event that can lead to untreated and exacerbated chronic illness, and that drives healthcare utilization. Research using medication claims data has attempted to identify instances of medication non‐adherence using the proportion of days covered...

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Bibliographic Details
Published in:British journal of clinical pharmacology 2024-05, Vol.90 (5), p.1240-1246
Main Authors: Wickham, Maeve E., McGrail, Kimberlyn M., Law, Michael R., Cragg, Amber, Hohl, Corinne M.
Format: Article
Language:English
Subjects:
Administrative Claims, Healthcare - statistics & numerical data
administrative data
Adult
adverse drug event
Aged
British Columbia
Databases, Factual - statistics & numerical data
drug safety
Drug-Related Side Effects and Adverse Reactions - diagnosis
Drug-Related Side Effects and Adverse Reactions - epidemiology
Female
Humans
Male
Medication Adherence - statistics & numerical data
medication non‐adherence
medication non‐persistence
Middle Aged
pharmacovigilance
Prospective Studies
Retrospective Studies
Sensitivity and Specificity
Young Adult
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Summary:Aims Medication non‐adherence is a type of adverse drug event that can lead to untreated and exacerbated chronic illness, and that drives healthcare utilization. Research using medication claims data has attempted to identify instances of medication non‐adherence using the proportion of days covered or by examining gaps between medication refills. We sought to validate these measures compared to a gold standard diagnosis of non‐adherence made in hospital. Methods This was a retrospective analysis of adverse drug events diagnosed during three prospective cohorts in British Columbia between 2008 and 2015 (n = 976). We linked prospectively identified adverse drug events to medication claims data to examine the sensitivity and specificity of typical non‐adherence measures. Results The sensitivity of the non‐adherence measures ranged from 22.4% to 37.5%, with a proportion of days covered threshold of 95% performing the best; the non‐persistence measures had sensitivities ranging from 10.4% to 58.3%. While a 7‐day gap was most sensitive, it classified 61.2% of the sample as non‐adherent, whereas only 19.6% were diagnosed as such in hospital. Conclusions The methods used to identify non‐adherence in administrative databases are not accurate when compared to a gold standard diagnosis by healthcare providers. Research that has relied on administrative data to identify non‐adherent patients both underestimates the magnitude of the problem and may label patients as non‐adherent who were in fact adherent.
ISSN:0306-5251
1365-2125
DOI:10.1111/bcp.16014