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ORAL ABSTRACTS: APPLIED HEALTH ECONOMICS AND PUBLIC HEALTH
Method: Our semi-Markov model captures the chronic, recurrent nature of opioid dependence, capturing periods of treatment, incarceration (defined as time spent in jail or prison), relapse (defined by opioid use outside of treatment), opioid abstinence and death. Hypothetical cohorts of prescription opioid (PO) and heroin users entered the model in either detoxification or maintenance treatment with the latter available in both strategies in subsequent treatment attempts. We used linked state-wide administrative data on drug treatment, criminal justice and incarceration, supplemented with other published data, to populate our model. We allowed for subsequent episodes of treatment and relapse to differ in duration, controlling for individuals being under legal supervision (parole or probation) or not. We compared an ‘actual practice’ scenario based on the observed distribution of PO and heroin users across detoxification and maintenance at first treatment to the hypothetical scenario of all treatment entrants initiating maintenance. One-way and probabilistic sensitivity analyses were executed for a range of alternate scenarios.
Result: Allowing access to maintenance-oriented treatment to OAT-naïve individuals was found to be a dominant strategy at 1-year, 5-year and lifetime horizons, resulting in lower total costs and higher quality-adjusted life-year (QALY) gains. Over a lifetime horizon, individuals who initiated maintenance upon first treatment entry gained 13.0 discounted QALYs on average (vs 12.1 for those receiving the standard of care) and generated a societal cost of $0.74 million (vs $1.02 million). Cost savings in the maintenance initiation cohort were realized primarily because of greater treatment retention and the lower costs of criminality associated with the reduced time spent out-of-treatment.
Conclusion: Synthesizing population-level data on OAT in publicly-funded drug treatment facilities in California, we found that immediate access to maintenance treatment may be more effective and less costly than the current standard of care for individuals presenting for opioid use disorder treatment.
Funding: NIDA R01DA031727;R01DA032551;P30DA016383 (PI:Hser)
Purpose: New therapies for Hepatitis C (HCV) are curative, but costly. We estimate the economic value of providing treatment for HCV in the US and compare it to the value of major federally regulated health interventions, such as the Clean Air Act.
Methods: Using a value of statistical life (VSL) and value of statistical life year (VSLY) framework, we calculate the net monetary benefit (NMB) of life-years saved if sofosbuvir-containing therapy is provided for all individuals estimated to have HCV based from the National Health and Examination Survey, 2003-2010. We assumed a VSL of 5 million USD. The VSLY is the quotient of VSL and the discounted expected remaining life-years for the general population at a mean age of 52. The NMB of therapy is the product of VSLY and the remaining life-years associated with treatment, minus the incremental cost. Outcomes are discounted at 3%. We project life expectancy and costs using the HCV Cost-Effectiveness (HCV-CE) Monte Carlo simulation model. In sensitivity analyses, we vary prices for HCV drugs (100% to 55%) to reflect potential offsets of rebates and other discounts, as well as the VSL (1 to 10 million USD). We compare valuations to those of other federally supported interventions.
Results: Treating 2.7 million individuals with HCV will result in 9.5 million life-years saved at an incremental cost of $345 billion dollars compared to no treatment. The VSLY is $274,000 dollars. The NMB of hepatitis C therapy is $2.2 trillion dollars, and ranges from $176 billion to $4.9 trillion dollars at VSL of $1 million to $10 million dollars, respectively. When we discount the price of medications by 45%, the NMB of therapy is $2.4 trillion dollars, with an incremental cost of therapy of $187 billion dollars. The NMB and cost exceed that of other federal regulations impacting health (Figure 1).
Conclusions: The economic value, and absolute cost accrued by treating HCV is on the order of the largest federal health interventions, such as the Clean Air Act. The effects are large due to the high mortality risk of HCV, the curative effect of therapy, therapy cost, and the size of the population. Concurrent efforts to expand access to and reduce the cost of therapy should be a priority at the federal level.
Purpose: Interventions to improve HIV care may vary substantially in their ability to deliver good value for money. There is an urgent need to maximize the value of health spending by prioritizing cost-effective interventions and, more broadly, identifying an optimal mix of interventions. We consider hypothetical scenarios of increased uptake of HIV testing and treatment, and improved treatment retention to identify the most cost-effective public health strategy.
Method: We used a previously-validated dynamic compartmental HIV transmission model to project the costs, benefits and epidemiological outcomes of the HIV/AIDS epidemic in BC from 2015 to 2035 under six hypothetical scenarios: (1) current practice, characterized using all available population-level epidemiologic and economic data; (2) a 10% increase in the HIV testing rate; (3) a 10% increase in treatment uptake; (4) a 25% decrease in the rate of treatment discontinuation; (5) interventions in scenarios (2)+(3); and (6) interventions in scenarios (2)+(3)+(4). In this hypothetical exercise, costs and effectiveness of the various interventions was assumed equal across HIV risk groups, the implementation of the interventions was at the provincial-level, and no budget constraint was imposed. Total HIV incidence, mortality, present-valued costs (in 2014$CDN) and quality-adjusted life years (QALYs) were estimated for each scenario, while incremental cost-effectiveness ratios (ICERs) were calculated against scenario (1), as well as the next-most resource intensive strategy in the interest of identifying the most efficient strategy. Analyses were executed from a third party payer (TPP) perspective.
Result: Scenarios (2) – (6) were all highly cost effective (<1x GDP per capita) compared to actual practice. Strategies (3) and (4) were dominated by strategies (5) and (6) respectively. We found strategy (6) remained cost-effective compared to strategy (5), with an ICER of $30,351 per QALY gained. At an additional cost of $110M over the study timeframe (5.5M/year), jointly increasing HIV testing and treatment access and improving HAART retention resulted in 531 averted HIV cases, 115 averted deaths and an overall gain of 6,469 QALYs.
Conclusion: Despite significant prior investment and advances in HIV care in BC, we found interventions to further improve HIV testing and care were highly cost-effective. Further research is required to aid resource allocation decisions on the margin, in real-time, using the observed costs and effectiveness of such interventions as delivered within localized settings.
Method: We conducted a population-level analysis of HRU for individuals having received a CD4 test after HIV diagnosis. All individuals in British-Columbia in the modern antiretroviral treatment-era (post-September 2006) were included. We derived from the first year following linkage ten categorical and binary indicators capturing HRU from linked comprehensive administrative health databases. Using a probabilistic model-based clustering analysis for mixed data, parameters were estimated by the method of maximum likelihood (ML) using the expectation maximization (EM) algorithm. Individuals with estimated parameters maximizing the posterior probability of belonging to a similar cluster are classified with each other, and the optimal number of clusters was estimated by the Bayesian Information Criterion (BIC). The analysis was conducted across CD4 count stratification (>200cells/mm3; <200cells/mm3).
Result: Our study included 941 individuals with at least one year follow-up (median age 40, 21% female) and with a CD4 count obtained between September 1st, 2006 and March 31st, 2011. The 215 individuals with CD4<200 clustered in 2 HRU patterns. The high cost cluster (N=58; mean $23,691 [SD: $25,443]) had costs more than four times the low cost cluster (N=157; $5,494 [$9,066]). Driving the difference in costs were lengthy HIV-related hospitalizations (62.1% with >7 days in the high cost cluster) and more frequent non-HIV-related physician visits (mean visits 92 vs. 24). The 726 individuals with CD4>200 were best classified in 3 clusters. The high cost cluster (N=146; $11,981 [$16,490]) was characterized by numerous non-HIV physician visits and ER hospitalizations (87.8% of all individuals with ≥1 day) as well as a high prevalence of mental health issues. Mean costs were more than triple that of the medium cost cluster (N=428; $2,723 [$4,170]). The low cost cluster (N=152; $1,391 [$8,360]) had almost no hospitalizations (98.7% with 0 days) and relatively few total non-HIV medication days.
Conclusion: Electronic medical records can be used to characterize heterogeneous HRU patterns in the interest of designing public health interventions to optimize clinical response and improve efficiency in medical care delivery.
Decision trees have traditionally been the modelling approach used to assess the economic value of vaccinations. However, this approach fails to capture the complexities in transmission dynamics. Alternative approaches that may handle such interactions include agent-based models (ABM) and system dynamics (SD). We compared the performance and results generated by a decision tree, ABM and SD in assessing the cost-effectiveness of two different childhood influenza vaccines.
Method:
An existing decision tree comparing intranasal live attenuated vaccine (LAIV) against injectable inactived influenza vaccine was adapted into a SD and ABM structure using the epidemiological pattern of ‘susceptible-infectious-recovered’ on AnyLogic 7.0 . The proportion of infected, expected costs and incremental cost-effectiveness ratio (ICER), as estimated by each modelling approach, were compared. Scenario analyses were conducted to relax the models’ assumptions to determine the impact of the various modelling approaches in assessing the economic value of vaccinations.
Result:
Model calibration was successful: all three modelling approaches produced similar estimates when identical parameters and assumptions were adopted. LAIV was found to be the dominant strategy. Scenario analyses revealed that disease transmission and economic value of the vaccination strategies were sensitive to: (1) the proportion and schedule of vaccination under both dynamic models; (2) the network topology, which can be more flexibly modelled in ABM and; (3) heterogeneity from age-specific parameters, which was most easily captured in the ABM.
Conclusion:
The clinical and economic estimates differ according to the modelling approach employed and its associated assumptions. ABM, an individual-level model, was the most flexible as it could capture patient heterogeneity and model individuals’ behaviours within their social network. SD, an aggregate-level model, was limited in capturing patient heterogeneity and required an assumption of random-mixing between individuals. The most rigid, though, was found to be the decision tree as it relies on a set of simplifying assumptions.
Methods: We used a Markov model to estimate the cost-effectiveness of influenza vaccination strategies over a single 10 month influenza season in persons aged ≥65. Vaccination and influenza occurred based on 5-year US monthly averages. The analysis took a societal perspective, with model parameters derived from CDC data, national databases, and medical literature sources. In the base case analysis, we assumed equal vaccine uptake between strategies and no indirect vaccination effects. Vaccine costs were: TIV $10.69, QIV $16.15, and high dose TIV $24.69. One-way and probabilistic sensitivity analyses were performed to test model robustness.
Results: In the base case, total influenza costs were $4.13 higher with TIV compared to no vaccination while gaining 0.0011 QALYs, or $3690 per QALY gained. Compared to TIV, high dose TIV cost $3.73 more and gained 0.0003 QALYS, or $12,300/QALY gained. QIV was eliminated due to extended dominance. One-way sensitivity analyses revealed a robust model: high dose TIV was favored at a $100,000/QALY threshold unless: 1) the increase in relative effectiveness of high-dose TIV compared to TIV is <11.0% (base case 24.2%), favoring QIV; or 2) TIV effectiveness falls below 9.8% (base case 39%), favoring no vaccination. QIV, with its added influenza B component, was not favored when the likelihood of influenza B types were varied in plausible ranges. In a probabilistic sensitivity analysis, varying parameters simultaneously over distributions 5000 times, high dose TIV is favored in 67% of iterations at a $50,000/QALY threshold and in 80% at $100,000/QALY.
Conclusion: High dose TIV for adults ≥65 is very likely to be an economically reasonable influenza vaccination strategy. A revision of CDC influenza vaccination recommendations for elders may be warranted.