Cost-effectiveness of drug consumption rooms in France: a modelling study

Abstract

Background: People who inject drugs (PWID) experience many health problems which result in a heavy economic and public health burden. To tackle this issue, France opened two drug consumption rooms (DCRs) in Paris and Strasbourg in 2016. This study assessed their long-term health benefits, costs and cost-effectiveness.

Methods: We developed a model to simulate two fictive cohorts for each city (n=2,997 in Paris and n=2,971 in Strasbourg) i) PWID attending a DCR over the period 2016-2026, ii) PWID attending no DCR. The model accounted for HIV and HCV infections, skin abscesses and related infective endocarditis, drug overdoses and emergency department visits. We estimated the number of health events and associated costs over 2016-2026, the lifetime number of quality-adjusted life-years (QALYs) and costs, and the incremental cost-effectiveness ratio (ICER).

Results: The numbers of abscesses and associated infective endocarditis, drug overdoses, and emergency department visits decreased significantly in PWID attending DCRs (-77%, -69%, and -65%, respectively) but the impact on HIV and HCV infections was modest (-11% and -6%, respectively). This resulted in savings of €6.6 (Paris) and €5.8 (Strasbourg) millions of medical costs. The ICER of DRCs was €30,600/QALY (Paris) and €9,200/QALY (Strasbourg). In scenario analysis where drug consumption spaces are implemented inside existing harm reduction structures, these ICERs decreased to €21,400/QALY and €2,500/QALY, respectively.

Conclusions: Our findings show that DCRs are highly effective and efficient to prevent harms in PWID in France, and advocate extending this intervention to other cities by adding drug consumption spaces inside existing harm reduction centers.

Keywords: Cost-effectiveness; Harm reduction; Injecting drug users; Modelling study; Supervised injection facility.

Fig. 1

Model for a. HCV infection and chronic hepatitis C care cascade, b. HIV infection and cascade of care, c. natural history of chronic hepatitis C and d. natural history of HIV infection. ${\mathrm{\lambda }}_{\text{HCV}}(\text{i})$ = rate of infection according to whether or not injection equipment was shared within one month. ${\text{T}}_{\text{a}}$ = duration of acute hepatitis C. ${\text{p}}_{\text{Rem}}=$ probability of spontaneous remission. ${\mathrm{\delta }}_{\text{HCV}}$ = rate of HCV testing; ${\mathrm{\varphi }}_{\text{HCV}}$ = rate of linkage to care. ${\mathrm{\tau }}_{\text{HCV}}$ = rate of loss to follow-up. a_VHC = rate of initiation of treatment. ${\text{T}}_{\text{t}}$ = duration of antiviral therapy. ${\text{p}}_{\text{RVS}}$ = probability of sustained virological response. ${\mathrm{\gamma }}_{\text{F}2/3}$ rate of progression to F2/3 fibrosis. ${\mathrm{\gamma }}_{\text{F}4}$ = rate of occurrence of cirrhosis in F2/3. ${\mathrm{\gamma }}_{\text{HCC}}$ = rate of occurrence of hepatocellular carcinoma in cirrhosis. ${\mathrm{\gamma }}_{\text{DC}-\text{HCC}}$ = rate of occurrence of hepatocellular carcinoma in decompensated cirrhosis. ${\mathrm{\gamma }}_{\text{DC}}$ = rate of occurrence of decompensated cirrhosis in cirrhosis. ${\mathrm{\gamma }}_{\text{HCC}-\text{TP}}$ = rate of liver transplants with hepatocellular carcinoma. ${\mathrm{\gamma }}_{\text{DC}-\text{TP}}$ = rate of hepatic transplants with decompensated cirrhosis. ${\mathrm{\gamma }}_{\text{HCC}-\text{Death}}$ = death rate from hepatocellular carcinoma. ${\mathrm{\gamma }}_{\text{DC}-\text{Death}}$ = death rate in decompensated cirrhosis. ${\mathrm{\gamma }}_{\text{TP}-\text{Death}}$ = death rate after liver transplantation. ${\mathrm{\lambda }}_{\text{HIV}}(\text{i})$ = rate of infection by sharing or not sharing injecting equipment in the month. ${\mathrm{\delta }}_{\text{HIV}}$ = HIV testing rate. ${\mathrm{\varphi }}_{\text{HIV}}$ = rate of linkage to care. ${\mathrm{\tau }}_{\text{HIV}}$ = rate of loss to follow-up. a_HIV = rate of initiation of treatment. ${\mathrm{\mu }}_{\text{x}}$ = mortality rate at CD4 level x. ${\mathrm{\gamma }}_{\text{x}}$ = rate of decline of CD4 level to $\text{x}$. ${\mathrm{\theta }}_{\text{x}}$ = rate of improvement in CD4 level towards $\text{x}$. Abbreviations: ARV=antiretrovirals; HCV=Hepatitis C virus; HIV=Human immunodeficiency virus; SVR=Sustained Virologic Response

Fig. 2

Proportion of medical events avoided (left) and medical costs avoided (right) with the DCRs in Paris (top) and Strasbourg (bottom). Abbreviations: DCR=Drug consumption room; ED=Emergency department; HCV=Hepatitis C virus; HIV=Human immunodeficiency virus

Fig. 3

Results obtained from 1,000 Monte-Carlo simulations for the probabilistic sensitivity analysis. Each simulation is represented according to the incremental effectiveness and the incremental cost of the DCR on the cost-effectiveness plane (A). The acceptability curves represent the proportion of simulations below the willingness-to-pay threshold as a function of the latter (B). The grey short-dashed line represents one-times the French GDP per capita (€33,300); the grey long-dashed line represents three-times the French GDP per capita (€99,900). The grey dot-dashed line represents the incremental cost-effectiveness ratio of interventions adopted in France based on their cost-effectiveness (€50,900). Results are presented for Paris and Strasbourg. Abbreviations: ICER=Incremental cost-effectiveness ratio; GDP=Gross domestic product; QALY=Quality-adjusted life-year