Real-world evidence on harm reduction strategies: A multidisciplinary evaluation
Notice bibliographique
Résumé
People who inject drugs (PWID) are at elevated risks of adverse health outcomes, including overdose and HIV. To reduce these drug-related harms, several strategies have been employed, including needle and syringe programs (NSP), opioid agonist treatment (OAT), and supervised consumption sites (SCS).Skin, soft tissue, and vascular infections (SSTVI) are the leading cause of morbidity in PWID globally. However, earlier studies examining the effectiveness of NSP and SCS have overlooked these endpoints. For studies comparing OAT medications, treatment retention is the most common measure of effectiveness. Despite available evidence, no studies have unified findings from different healthcare practices to strengthen clinical treatment protocols. To address these limitations, I sought to examine the effectiveness of these harm reduction strategies from the clinical, economic, and health service utilization angles. The overall goal of my thesis was to investigate how these strategies have mitigated drug-related adverse health outcomes in PWID.First, I developed a microsimulation model to assess clinical and cost-effectiveness of NSP with respect to SSTVI compared to a counterfactual scenario without NSP. I assessed the cost-effectiveness of NSP, estimated the hazard of SSTVI mortality, and examined health service utilization patterns under the two NSP scenarios. The incremental cost-effectiveness ratio was $70,278 per quality-adjusted life years (QALY), which was due to low incremental QALY as well as high incremental costs from continued health service use and NSP costs among those who were alive. My study establishes the effectiveness of NSP while capturing the real-world complexities surrounding individuals’ unique clinical pathways and interactions with the healthcare system to treat SSTVI.Second, I conducted a systematic review of randomized controlled trials (RCT) comparing treatment retention percentage between four medications prescribed as OAT: buprenorphine, methadone, naltrexone, and slow-release oral morphine (SROM). I ran a Bayesian network meta-analysis to enable direct and indirect comparison of the medications and rank them based on the likelihood of treatment retention. Methadone was ranked the highest, while the non-pharmacotherapeutic control group was ranked the lowest. Due to a small number of high-quality trials, confidence in the network estimates of treatment pairs involving naltrexone and SROM remains low. Additional high-quality RCT are needed to estimate more accurately the extent of efficacy of naltrexone and SROM relative to other medications.Third, I conducted a quasi-experimental study to assess the effect of Montreal’s four SCS on the incidence of SSTVI among PWID in the city. I ran an interrupted time series analysis that accounted for autocorrelation and seasonality. After the opening of the four SCS in 2017, there was a level increase with positive time trend in outpatient visits. During the same post-intervention period, there was a moderate decline in time trend in emergency department visits and hospitalizations. The findings from my study demonstrate that SCS resulted in increased healthcare service use while mitigating more serious cases of SSTVI.Findings from my thesis shed light on important additional benefits of harm reduction interventions beyond cost savings and number of infections averted. The use of state-of-the-art methods drawn from decision science, biostatistics, and econometrics enabled rigorous examination of NSP, OAT, and SCS. The results of my thesis have broad applications not only to opioid prescribing physicians who seek to establish clinical best practice but also to public health stakeholders who wish to expand existing services
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,093 | 0,181 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,009 | 0,025 |
| Bibliométrie | 0,006 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,005 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».