A five-year study of distribution and determinants of high-cost users of prescription drugs in Côte d’Ivoire

A small proportion of people account for a significant share of prescription drug expenditures. These individuals, commonly referred to as high-cost users (HCUs), are a key focus of initiatives designed to control expenditures. This study aimed to describe the distribution of prescription drug expenditures and investigate the determinants of HCUs at the Mutual Health Insurance Company for Civil Servants of Côte d’Ivoire (Mutuelle Générale des Fonctionnaires et Agents de l’État de Côte d’Ivoire (MUGEFCI)). We conducted a retrospective analysis using MUGEFCI data. Beneficiaries who received reimbursement for at least one medication between January 1, 2014, and December 31, 2018 were included. HCUs were defined as individuals whose annual drug expenditure exceeded the 95th percentile. Generalized estimating equations (GEEs) were used to analyse the determinants. The median ± interquartile range (IQR) expenditure for HCUs varied from 210,145 ± 47,899 to 269,617.5 ± 50,085 French speaking West African countries currency (XOF). HCUs accounted for between 30.84% and 32.31% of total medicine expenditures. Compared with people aged 15–25, those aged 55–65, 65–75, and over 75 years were 1.47 (odds ratio (OR) = 1.47 [1.41–1.54], P < 0.001), 1.73 (OR = 1.73 [1.64–1.82], P < 0.001), and 1.5 (OR = 1.5 [1.38–1.63], P < 0.001) times more likely to be HCUs, respectively. Those taking cardiovascular and anticancer medicines were 18.59 (OR = 18.59 [18.55–19.23], P < 0.001) and 78.37 (OR = 78.17 [68.85–89.21], P < 0.001) times more likely to be HCUs, respectively. Beneficiaries consulting a level 3 facility were 2.73 (OR = 2.73 [2.67–2.79], P < 0.001) times more likely to be HCUs. Older age, use of cardiovascular or anticancer drugs, and consultation with a level 3 facility were the major determinants of HCUs. It is necessary to promote rational medicine use and enhance prevention of cardiovascular diseases and cancer. • HCU expenditure represented 30.84% to 32.31% of total drug expenditures. • People aged 65 and over represented 1.5% to 15.8% of HCUs. • Compared with those aged 15–25 years, people aged 55-65 years, 65–75 years, and over 75 years were more likely to be HCU. • People taking cardiovascular and anticancer medicines were 18.59 and 78.37 times more likely to be HCUs, respectively.

Authors

Institutions

Publication Details

Journal
Pharmacoeconomics and Policy
Published
2025-12-01
DOI
https://doi.org/10.1016/j.pharp.2026.01.001
Primary Topic
Medication Adherence and Compliance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A five-year study of distribution and determinants of high-cost users of prescription drugs in Côte d’Ivoire

Desquith Aka, Kouamé Koffi, A.R. Attia-Konan, Paul Yapo Yapi et al.
Pharmacoeconomics and Policy
Medication Adherence and Compliance
article

A five-year study of distribution and determinants of high-cost users of prescription drugs in Côte d’Ivoire

Desquith Aka, Kouamé Koffi, A.R. Attia-Konan, Paul Yapo Yapi, Serge Oga, Jérôme Kouame, Marie-Laure Tiade
article en

Abstract

A small proportion of people account for a significant share of prescription drug expenditures. These individuals, commonly referred to as high-cost users (HCUs), are a key focus of initiatives designed to control expenditures. This study aimed to describe the distribution of prescription drug expenditures and investigate the determinants of HCUs at the Mutual Health Insurance Company for Civil Servants of Côte d’Ivoire (Mutuelle Générale des Fonctionnaires et Agents de l’État de Côte d’Ivoire (MUGEFCI)). We conducted a retrospective analysis using MUGEFCI data. Beneficiaries who received reimbursement for at least one medication between January 1, 2014, and December 31, 2018 were included. HCUs were defined as individuals whose annual drug expenditure exceeded the 95th percentile. Generalized estimating equations (GEEs) were used to analyse the determinants. The median ± interquartile range (IQR) expenditure for HCUs varied from 210,145 ± 47,899 to 269,617.5 ± 50,085 French speaking West African countries currency (XOF). HCUs accounted for between 30.84% and 32.31% of total medicine expenditures. Compared with people aged 15–25, those aged 55–65, 65–75, and over 75 years were 1.47 (odds ratio (OR) = 1.47 [1.41–1.54], P < 0.001), 1.73 (OR = 1.73 [1.64–1.82], P < 0.001), and 1.5 (OR = 1.5 [1.38–1.63], P < 0.001) times more likely to be HCUs, respectively. Those taking cardiovascular and anticancer medicines were 18.59 (OR = 18.59 [18.55–19.23], P < 0.001) and 78.37 (OR = 78.17 [68.85–89.21], P < 0.001) times more likely to be HCUs, respectively. Beneficiaries consulting a level 3 facility were 2.73 (OR = 2.73 [2.67–2.79], P < 0.001) times more likely to be HCUs. Older age, use of cardiovascular or anticancer drugs, and consultation with a level 3 facility were the major determinants of HCUs. It is necessary to promote rational medicine use and enhance prevention of cardiovascular diseases and cancer. • HCU expenditure represented 30.84% to 32.31% of total drug expenditures. • People aged 65 and over represented 1.5% to 15.8% of HCUs. • Compared with those aged 15–25 years, people aged 55-65 years, 65–75 years, and over 75 years were more likely to be HCU. • People taking cardiovascular and anticancer medicines were 18.59 and 78.37 times more likely to be HCUs, respectively.

Pharmacoeconomics and PolicyVol. 1(4)
Institut Pasteur de Côte d'Ivoire (CI), Université Félix Houphouët-Boigny (CI)
Openalex Percentile: Top 24%
Medication Adherence and Compliance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.