Cost-effectiveness of flexible take-home buprenorphine-naloxone versus methadone for treatment of prescription-type opioid use disorder.

BACKGROUND: Our objective was to examine the cost-effectiveness of flexible take-home buprenorphine-naloxone (BNX) versus methadone alongside the OPTIMA trial in Canada. METHODS: The OPTIMA study was a pragmatic, open-label, noninferiority, two-arm randomized controlled trial, to assess the comparative effectiveness of flexible take-home BNX vs. methadone in routine clinical care for individuals with prescription-type opioid use disorder. We evaluated cost-effectiveness using a semi-Markov cohort model. Probabilities of overdose were calibrated, accounting for fentanyl prevalence and other overdose risk factors such as naloxone availability. We considered health sector and societal cost perspectives, including costs (2020 CAD) for treatment, health resource use, criminal activity, and health state-specific preference weights as outcomes to calculate incremental cost-effectiveness ratios. Six-month and lifetime (3% annual discount rate) time-horizons were explored. RESULTS: Over a lifetime time horizon, individuals accumulated -0.144 [CI: -0.302, -0.025] incremental quality-adjusted life years (QALYs) in BNX compared with methadone. Incremental costs were -$2047 [CI: -$39,197, $24,250] from a societal perspective, and -$4549 [CI: -$6332, -$3001] from a health sector perspective. Over a six-month time-horizon, individuals accumulated 0.002 [credible interval (CI): -0.011, 0.016] incremental QALYs in BNX compared with methadone. Incremental costs were -$307 [CI: -$10,385, $8466] from a societal perspective and -$1111 [CI: -$1517, -$631] from a health sector perspective. BNX was dominated (costlier, less effective) in 49.7% of simulations when adopting a societal perspective over a lifetime time horizon. CONCLUSIONS: Flexible take-home BNX was not cost-effective versus methadone over a lifetime time horizon, resulting from better treatment retention in methadone compared to BNX.

Estimated cost-effectiveness of point-of-care testing in community pharmacies vs. self-testing and standard laboratory testing for HIV.

OBJECTIVE: Point-of-care-testing (POCT) for HIV at community pharmacies can enhance care linkage compared with self-tests and increase testing uptake relative to standard lab testing. While the higher test uptake may increase testing costs, timely diagnosis and treatment can reduce downstream HIV treatment costs and improve health outcomes. This study provides the first evidence on the cost-effectiveness of pharmacist-led POCT vs. HIV self-testing and standard lab testing. DESIGN: Dynamic transmission model. METHODS: We compared three HIV testing strategies: POCT at community pharmacies; self-testing using HIV self-test kits; and standard lab testing. Analyses were conducted from the Canadian health system perspective over a 30-year time horizon for all individuals aged 15-64 years in Canada. Costs were measured in 2021 Canadian dollars and effectiveness was captured using quality-adjusted life-years (QALYs). RESULTS: Compared with standard lab testing, POCT at community pharmacies would save $885 million in testing costs over 30 years. Though antiretroviral treatment costs would increase by $190 million with POCT as more persons living with HIV are identified and treated, these additional costs would be partly offset by their lower downstream healthcare utilization (savings of $150 million). POCT at community pharmacies would also yield over 5000 additional QALYs. Compared with HIV self-testing, POCT at community pharmacies would generate both higher costs and higher QALYs and would be cost-effective with an incremental cost-effectiveness ratio of $47 475 per QALY gained. CONCLUSIONS: Offering POCT at community pharmacies can generate substantial cost savings and improve health outcomes compared with standard lab testing. It would also be cost-effective vs. HIV self-testing.

Incremental expenditures attributable to daily dispensation and witnessed ingestion for opioid agonist treatment in British Columbia: 2014-20.

BACKGROUND AND AIM: While daily witnessed opioid agonist treatment (OAT) ingestion is common in British Columbia (BC), Canada, and elsewhere, sparse evidence supports this resource-intensive practice. Many settings across North America relaxed restrictions for take-home dosing during the COVID-19 pandemic and have reported consistent or improved patient outcomes. This study measured excess expenditures attributed to daily witnessed pharmacy dispensing compared with weekly or biweekly dispensation schedules. DESIGN, SETTING AND PARTICIPANTS: This study was a population-level retrospective analysis. We included all methadone, buprenorphine/naloxone and slow-release oral morphine dispensations in BC from 1 January 2014 to 30 December 2020. A total of 24 357 107 OAT dispensations among 51 195 unique individuals with 122 793 person-years of follow-up were included during the study period. MEASUREMENTS: Total expenditures for each person-week of OAT with an estimated expenditure under two scenarios are as follows: (1) a weekly dispensation scenario and (2) a biweekly dispensation scenario. FINDINGS: We estimated excess expenditures attributable to current dispensing practices of between $38 million (2014) and $47.4 million (2018) compared with a hypothetical weekly dispensing schedule, and $43.9 million (2014) to $54.9 million (2018) compared with biweekly dispensing. The majority of these expenditures (58-64%) were attributed to pharmacy dispensing fees ($23 million in 2014 to $30 million in 2018 compared with weekly dispensing; $26.6 million in 2014 to $34.7 million in 2018 compared with biweekly dispensing). CONCLUSION: Daily witnessed opioid agonist treatment ingestion results in more than $30 million in excess expenditures annually in the province of British Columbia, Canada compared with the costs of weekly or biweekly dispensation schedules.

Translating and disseminating a localised economic model to support implementation of the 'Ending the HIV Epidemic' initiative to public health policymakers.

Background: Despite significant progress in HIV treatment and prevention, the US remains far from its goal of 'Ending the HIV Epidemic' by 2030. Economic models using local data can synthesise the evidence to help policymakers allocate HIV resources efficiently, but persistent research-to-practice gaps remain. Little is known about how to facilitate the use of economic modelling data among local public health policymakers in real-world settings. Aims and objectives: To explore the dissemination of results from a locally-calibrated economic model for HIV prevention and treatment and identify the factors influencing potential uptake of the model for public health decision making at the local level. Methods: Four virtual focus groups with 26 local health department policymakers in Baltimore, Miami, Seattle, and New York City were held between July 2020 and May 2021. Qualitative content analysis of transcripts identified key themes around using the localised economic model in policy decisions. Results: Participants were interested in using local data in their decisions to allocate resources for HIV prevention/treatment. Six themes emerged: 1) importance of understanding local policy context; 2) health equity considerations; 3) using evidence to support current priorities; 4) difficulty of changing strategies, even incrementally; 5) bang for the incremental buck (efficiency) vs. previous impact; and 6) community values. Conclusion and relevance: To optimise acceptance and use of results from economic models, researchers should engage with local community members and public health decision makers early to understand budgetary and community priorities. Participants prioritised evidence that supports their existing strategies, considers budgets and funding streams, and improves health equity; however, real-world budget constraints and conflicting interests serve as barriers to implementing model recommendations and reaching national goals.

Improving health equity and ending the HIV epidemic in the USA: a distributional cost-effectiveness analysis in six cities.

BACKGROUND: In the USA, Black and Hispanic or Latinx individuals continue to be disproportionately affected by HIV. Applying a distributional cost-effectiveness framework, we estimated the cost-effectiveness and epidemiological impact of two combination implementation approaches to identify the approach that best meets the dual objectives of improving population health and reducing racial or ethnic health disparities. METHODS: We adapted a dynamic, compartmental HIV transmission model to characterise HIV micro-epidemics in six US cities: Atlanta, Baltimore, Los Angeles, Miami, New York, and Seattle. We considered combinations of 16 evidence-based interventions to diagnose, treat, and prevent HIV transmission according to previously documented levels of scale-up. We then identified optimal combination strategies for each city, with the distribution of each intervention implemented according to existing service levels (proportional services approach) and the racial or ethnic distribution of new diagnoses (between Black, Hispanic or Latinx, and White or other ethnicity individuals; equity approach). We estimated total costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios of strategies implemented from 2020 to 2030 (health-care perspective; 20-year time horizon; 3% annual discount rate). We estimated three measures of health inequality (between-group variance, index of disparity, Theil index), incidence rate ratios, and rate differences for the selected strategies under each approach. FINDINGS: In all cities, optimal combination strategies under the equity approach generated more QALYs than those with proportional services, ranging from a 3·1% increase (95% credible interval [CrI] 1·4-5·3) in New York to more than double (101·9% [75·4-134·6]) in Atlanta. Compared with proportional services, the equity approach delivered lower costs over 20 years in all cities except Los Angeles; cost reductions ranged from $22·9 million (95% CrI 5·3-55·7 million) in Seattle to $579·8 million (255·4-940·5 million) in Atlanta. The equity approach also reduced incidence disparities and health inequality measures in all cities except Los Angeles. INTERPRETATION: Equity-focused HIV combination implementation strategies that reduce disparities for Black and Hispanic or Latinx individuals can significantly improve population health, reduce costs, and drive progress towards Ending the HIV Epidemic goals in the USA. FUNDING: National Institute on Drug Abuse.

Cost-Effectiveness Analysis in Implementation Science: a Research Agenda and Call for Wider Application.

PURPOSE OF REVIEW: Cost-effectiveness analysis (CEA) can help identify the trade-offs decision makers face when confronted with alternative courses of action for the implementation of public health strategies. Application of CEA alongside implementation scientific studies remains limited. We aimed to identify areas for future development in order to enhance the uptake and impact of model-based CEA in implementation scientific research. RECENT FINDINGS: Important questions remain about how to broadly implement evidence-based public health interventions in routine practice. Establishing population-level implementation strategy components and distinct implementation phases, including planning for implementation, the time required to scale-up programs, and sustainment efforts required to maintain them, can help determine the data needed to quantify each of these elements. Model-based CEA can use these data to determine the added value associated with each of these elements across systems, settings, population subgroups, and levels of implementation to provide tailored guidance for evidence-based public health action. There is a need to integrate implementation science explicitly into CEA to adequately capture diverse real-world delivery contexts and make detailed, informed recommendations on the aspects of the implementation process that provide good value. We describe examples of how model-based CEA can integrate implementation scientific concepts and evidence to help tailor evaluations to local context. We also propose six distinct domains for methodological advancement in order to enhance the uptake and impact of model-based cost-effectiveness analysis in implementation scientific research.

The Potential Epidemiological Impact of Coronavirus Disease 2019 (COVID-19) on the Human Immunodeficiency Virus (HIV) Epidemic and the Cost-effectiveness of Linked, Opt-out HIV Testing: A Modeling Study in 6 US Cities.

BACKGROUND: Widespread viral and serological testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may present a unique opportunity to also test for human immunodeficiency virus (HIV) infection. We estimated the potential impact of adding linked, opt-out HIV testing alongside SARS-CoV-2 testing on the HIV incidence and the cost-effectiveness of this strategy in 6 US cities. METHODS: Using a previously calibrated dynamic HIV transmission model, we constructed 3 sets of scenarios for each city: (1) sustained current levels of HIV-related treatment and prevention services (status quo); (2) temporary disruptions in health services and changes in sexual and injection risk behaviors at discrete levels between 0%-50%; and (3) linked HIV and SARS-CoV-2 testing offered to 10%-90% of the adult population in addition to Scenario 2. We estimated the cumulative number of HIV infections between 2020-2025 and the incremental cost-effectiveness ratios of linked HIV testing over 20 years. RESULTS: In the absence of linked, opt-out HIV testing, we estimated a total of a 16.5% decrease in HIV infections between 2020-2025 in the best-case scenario (50% reduction in risk behaviors and no service disruptions), and a 9.0% increase in the worst-case scenario (no behavioral change and 50% reduction in service access). We estimated that HIV testing (offered at 10%-90% levels) could avert a total of 576-7225 (1.6%-17.2%) new infections. The intervention would require an initial investment of $20.6M-$220.7M across cities; however, the intervention would ultimately result in savings in health-care costs in each city. CONCLUSIONS: A campaign in which HIV testing is linked with SARS-CoV-2 testing could substantially reduce the HIV incidence and reduce direct and indirect health care costs attributable to HIV.

Prioritizing Additional Data Collection to Reduce Decision Uncertainty in the HIV/AIDS Response in 6 US Cities: A Value of Information Analysis.

OBJECTIVES: The ambitious goals of the US Ending the HIV Epidemic initiative will require a targeted, context-specific public health response. Model-based economic evaluation provides useful guidance for decision making while characterizing decision uncertainty. We aim to quantify the value of eliminating uncertainty about different parameters in selecting combination implementation strategies to reduce the public health burden of HIV/AIDS in 6 US cities and identify future data collection priorities. METHODS: We used a dynamic compartmental HIV transmission model developed for 6 US cities to evaluate the cost-effectiveness of a range of combination implementation strategies. Using a metamodeling approach with nonparametric and deep learning methods, we calculated the expected value of perfect information, representing the maximum value of further research to eliminate decision uncertainty, and the expected value of partial perfect information for key groups of parameters that would be collected together in practice. RESULTS: The population expected value of perfect information ranged from $59 683 (Miami) to $54 108 679 (Los Angeles). The rank ordering of expected value of partial perfect information on key groups of parameters were largely consistent across cities and highest for parameters pertaining to HIV risk behaviors, probability of HIV transmission, health service engagement, HIV-related mortality, health utility weights, and healthcare costs. Los Angeles was an exception, where parameters on retention in pre-exposure prophylaxis ranked highest in contributing to decision uncertainty. CONCLUSIONS: Funding additional data collection on HIV/AIDS may be warranted in Baltimore, Los Angeles, and New York City. Value of information analysis should be embedded into decision-making processes on funding future research and public health intervention.

Ending the HIV Epidemic Among Persons Who Inject Drugs: A Cost-Effectiveness Analysis in Six US Cities.

BACKGROUND: Persons who inject drugs (PWID) are at a disproportionately high risk of HIV infection. We aimed to determine the highest-valued combination implementation strategies to reduce the burden of HIV among PWID in 6 US cities. METHODS: Using a dynamic HIV transmission model calibrated for Atlanta, Baltimore, Los Angeles, Miami, New York City, and Seattle, we assessed the value of implementing combinations of evidence-based interventions at optimistic (drawn from best available evidence) or ideal (90% coverage) scale-up. We estimated reduction in HIV incidence among PWID, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs) for each city (10-year implementation; 20-year horizon; 2018 $ US). RESULTS: Combinations that maximized health benefits contained between 6 (Atlanta and Seattle) and 12 (Miami) interventions with ICER values ranging from $94 069/QALY in Los Angeles to $146 256/QALY in Miami. These strategies reduced HIV incidence by 8.1% (credible interval [CI], 2.8%-13.2%) in Seattle and 54.4% (CI, 37.6%-73.9%) in Miami. Incidence reduction reached 16.1%-75.5% at ideal scale. CONCLUSIONS: Evidence-based interventions targeted to PWID can deliver considerable value; however, ending the HIV epidemic among PWID will require innovative implementation strategies and supporting programs to reduce social and structural barriers to care.

"Ending the Epidemic" Will Not Happen Without Addressing Racial/Ethnic Disparities in the United States Human Immunodeficiency Virus Epidemic.

We estimated human immunodeficiency virus incidence and incidence rate ratios (IRRs) for black and Hispanic vs white populations in 6 cities in the United States (2020-2030). Large reductions in incidence are possible, but without elimination of disparities in healthcare access, we found that wide disparities persisted for black compared with white populations in particular (lowest IRR, 1.69 [95% credible interval, 1.19-2.30]).

Ending the HIV epidemic in the USA: an economic modelling study in six cities.

BACKGROUND: The HIV epidemic in the USA is a collection of diverse local microepidemics. We aimed to identify optimal combination implementation strategies of evidence-based interventions to reach 90% reduction of incidence in 10 years, in six US cities that comprise 24·1% of people living with HIV in the USA. METHODS: In this economic modelling study, we used a dynamic HIV transmission model calibrated with the best available evidence on epidemiological and structural conditions for six US cities: Atlanta (GA), Baltimore (MD), Los Angeles (CA), Miami (FL), New York City (NY), and Seattle (WA). We assessed 23 040 combinations of 16 evidence-based interventions (ie, HIV prevention, testing, treatment, engagement, and re-engagement) to identify combination strategies providing the greatest health benefit while remaining cost-effective. Main outcomes included averted HIV infections, quality-adjusted life-years (QALYs), total cost (in 2018 US$), and incremental cost-effectiveness ratio (ICER; from the health-care sector perspective, 3% annual discount rate). Interventions were implemented at previously documented and ideal (90% coverage or adoption) scale-up, and sustained from 2020 to 2030, with outcomes evaluated until 2040. FINDINGS: Optimal combination strategies providing health benefit and cost-effectiveness contained between nine (Seattle) and 13 (Miami) individual interventions. If implemented at previously documented scale-up, these strategies could reduce incidence by between 30·7% (95% credible interval 19·1-43·7; Seattle) and 50·1% (41·5-58·0; New York City) by 2030, at ICERs ranging from cost-saving in Atlanta, Baltimore, and Miami, to $95 416 per QALY in Seattle. Incidence reductions reached between 39·5% (26·3-53·8) in Seattle and 83·6% (70·8-87·0) in Baltimore at ideal implementation. Total costs of implementing strategies across the cities at previously documented scale-up reached $559 million per year in 2024; however, costs were offset by long-term reductions in new infections and delayed disease progression, with Atlanta, Baltimore, and Miami projecting cost savings over the 20 year study period. INTERPRETATION: Evidence-based interventions can deliver substantial public health and economic value; however, complementary strategies to overcome social and structural barriers to HIV care will be required to reach national targets of the ending the HIV epidemic initiative by 2030. FUNDING: National Institutes of Health.

The impact of localized implementation: determining the cost-effectiveness of HIV prevention and care interventions across six United States cities.

OBJECTIVE: Effective interventions to reduce the public health burden of HIV/AIDS can vary in their ability to deliver value at different levels of scale and in different epidemiological contexts. Our objective was to determine the cost-effectiveness of HIV treatment and prevention interventions implemented at previously documented scales of delivery in six US cities with diverse HIV microepidemics. DESIGN: Dynamic HIV transmission model-based cost-effectiveness analysis. METHODS: We identified and estimated previously documented scale of delivery and costs for 16 evidence-based interventions from the US CDC's Compendium of Evidence-Based Interventions and Best Practices for HIV Prevention. Using a model calibrated for Atlanta, Baltimore, Los Angeles, Miami, New York City and Seattle, we estimated averted HIV infections, quality-adjusted life years (QALY) gained and incremental cost-effectiveness ratios (healthcare perspective; 3% discount rate, 2018$US), for each intervention and city (10-year implementation) compared with the status quo over a 20-year time horizon. RESULTS: Increased HIV testing was cost-saving or cost-effective across cities. Targeted preexposure prophylaxis for high-risk MSM was cost-saving in Miami and cost-effective in Atlanta ($6123/QALY), Baltimore ($18 333/QALY) and Los Angeles ($86 117/QALY). Interventions designed to improve antiretroviral therapy initiation provided greater value than other treatment engagement interventions. No single intervention was projected to reduce HIV incidence by more than 10.1% in any city. CONCLUSION: Combination implementation strategies should be tailored to local epidemiological contexts to provide the most value. Complementary strategies addressing factors hindering access to HIV care will be necessary to meet targets for HIV elimination in the United States.

Geographic variation in the costs of medical care for people living with HIV in British Columbia, Canada.

BACKGROUND: Regional variation in medical care costs can indicate heterogeneity in clinical practice, inequities in access, or inefficiencies in service delivery. We aimed to estimate regional variation in medical costs for people living with HIV (PLHIV), adjusting for demographics and case-mix. METHODS: We conducted a retrospective cohort study using linked health administrative databases of PLHIV, from 2010 to 2014, in British Columbia (BC), Canada. Quarterly health care costs (2018 CAD) were derived from inpatient, outpatient, prescription drugs, antiretroviral therapy (ART), and HIV diagnostics. We used a two-part model with a logit link for the probability of incurring costs, and a log link and gamma distribution for observations with positive costs. We also estimated quarterly utilization rates for hospitalization-, physician billing- and prescription drug-days. Primary variables were indicators of individuals' Health Service Delivery Area (HSDA). We adjusted cost and utilization estimates for demographic characteristics, HIV-disease progression, and comorbidities. RESULTS: Our cohort included 9577 PLHIV (median age 45.5 years, 80% male). Adjusted total quarterly costs for all 16 HSDAs were within 20% of the provincial mean, 8/16 for hospitalization costs, 16/16 for physician billing costs and 10/16 for prescription drug costs. Northern Interior and Northeast HSDAs had 38 and 44% lower quarterly non-ART prescription drug costs, and 2 and 5% higher quarterly inpatient costs, respectively. CONCLUSIONS: We observed limited variation in medical care costs and utilization among PLHIV in BC. However, lower levels of outpatient care and higher levels of inpatient care indicate possible barriers to accessing care among PLHIV in the most rural regions of the province.

Combined estimation of disease progression and retention on antiretroviral therapy among treated individuals with HIV in the USA: a modelling study.

BACKGROUND: Accurately estimating HIV disease progression and retention on antiretroviral therapy (ART) can help inform interventions to control HIV microepidemics and mathematical models used to inform health-resource allocation decisions. Our objective was to estimate the monthly probabilities of on-ART CD4 T-cell count progression, mortality, ART dropout, and ART reinitiation using a continuous-time multistate Markov model. We also aimed to validate health-state transition probability estimates to ensure they accurately reproduced the regional HIV microepidemics across the USA. METHODS: In our modelling study, we considered a cohort of patients from the HIV Research Network, a consortium of 17 adult and paediatric HIV-care providers located in the northeastern (n=8), southern (n=5), and western (n=4) regions of the USA. Individuals aged 15 years or older who were in HIV care (defined as one CD4 test and one HIV-care visit in a calendar year period) with at least one ART prescription between Jan 1, 2010, and Dec 31, 2015, were included in the analysis. We used continuous-time multistate Markov models to estimate transitions between CD4 strata and between on-ART and off-ART states. We examined and adjusted for differences in probability of transition by region, race or ethnicity, sex, HIV risk group, and other baseline clinical indicators. FINDINGS: The median age of the 32 242 individuals included in the analysis was 44 years (interquartile range 35-51). Over a median follow-up of 4·9 years (2·6-6·0), 8614 (26·7%) of 32 242 people interrupted ART and 1325 (4·1%) of 32 242 people died. Women, men who have sex with men, and individuals with no previous ART experience had greater increases in CD4 cell counts, whereas black people and people who inject drugs had increased probabilities of ART dropout and faster disease progression. Regardless of CD4 strata, individuals had increased hazard for ART dropout if they were from the south (adjusted hazard ratio [aHR] range from 1·91, 95% CI 1·71-2·13, to 2·45, 2·29-2·62) or the west (aHR range from 1·29, 1·10-1·51, to 1·66, 1·51-1·82) of the USA, compared with individuals from the northeast USA. INTERPRETATION: Our results show heterogeneities in disease progression during ART and probability of ART retention across race and ethnicity, HIV risk groups, and regions. These differences should be viewed as targets for intervention and should be incorporated in mathematical models of regional HIV microepidemics in the USA. FUNDING: US National Institutes of Health, Agency for Healthcare Research and Quality, and Health Resources and Services Administration.

Identifying mental health and substance use disorders using emergency department and hospital records: a population-based retrospective cohort study of diagnostic concordance and disease attribution.

OBJECTIVES: Administrative data are increasingly being used for surveillance and monitoring of mental health and substance use disorders (MHSUD) across Canada. However, the validity of the diagnostic codes specific to MHSUD is unknown in emergency departments (EDs). Our objective was to determine the concordance, and individual-level and hospital-level factors associated with concordance, between diagnosis codes assigned in ED and at discharge from hospital for MHSUD-related conditions. DESIGN: Population-based retrospective cohort study. SETTING: EDs and hospitals within Vancouver Coastal Health Authority (VCH), British Columbia, Canada. PARTICIPANTS: 16 926 individuals who were admitted into a VCH hospital following an ED visit from 1 April 2009 to 31 March 2017, contributing to 48 116 pairs of ED and hospital discharge diagnoses. PRIMARY AND SECONDARY OUTCOME MEASURES: We examined concordance in identifying MHSUD between the primary discharge diagnosis codes based on the International Statistical Classification of Diseases, 9th and 10th Revisions (Canada) assigned in the ED and those assigned in the hospital among all ED visits resulting in a hospital admission. We calculated the percent overall agreement, positive agreement, negative agreement and Cohen's kappa coefficient. We performed multiple regression analyses to identify factors independently associated with discordance. RESULTS: We found a high level of concordance for broad categories of MH conditions (overall agreement=0.89, positive agreement=0.74 and kappa=0.67), and a fair level of concordance for SUDs (overall agreement=0.89, positive agreement=0.31 and kappa=0.27). SUDs were less likely to be indicated as the primary cause in ED as opposed to in hospital (3.8% vs 11.7%). In multiple regression analyses, ED visits occurring during holidays, weekends and overnight (21:00-8:59 hours) were associated with increased odds of discordance in identifying MH conditions (adjusted OR 1.47, 95% CI 1.11 to 1.93; 1.27, 95% CI 1.16 to 1.40; 1.30, 95% CI 1.19 to 1.42, respectively). CONCLUSIONS: ED data could be used to improve surveillance and monitoring of MHSUD. Future efforts are needed to improve screening for individuals with MHSUD and subsequently connect them to treatment and follow-up care.

Structural Design and Data Requirements for Simulation Modelling in HIV/AIDS: A Narrative Review.

Born out of a necessity for fiscal sustainability, simulation modeling is playing an increasingly prominent role in setting priorities for combination implementation strategies for HIV treatment and prevention globally. The design of a model and the data inputted into it are central factors in ensuring credible inferences. We executed a narrative review of a set of dynamic HIV transmission models to comprehensively synthesize and compare the structural design and the quality of evidence used to support each model. We included 19 models representing both generalized and concentrated epidemics, classified as compartmental, agent-based, individual-based microsimulation or hybrid in our review. We focused on four structural components (population construction; model entry, exit and HIV care engagement; HIV disease progression; and the force of HIV infection), and two analytical components (model calibration/validation; and health economic evaluation, including uncertainty analysis). While the models we reviewed focused on a variety of individual interventions and their combinations, their structural designs were relatively homogenous across three of the four focal components, with key structural elements influenced by model type and epidemiological context. In contrast, model entry, exit and HIV care engagement tended to differ most across models, with some health system interactions-particularly HIV testing-not modeled explicitly in many contexts. The quality of data used in the models and the transparency with which the data was presented differed substantially across model components. Representative and high-quality data on health service delivery were most commonly not accessed or were unavailable. The structure of an HIV model should ideally fit its epidemiological context and be able to capture all efficacious treatment and prevention services relevant to a robust combination implementation strategy. Developing standardized guidelines on evidence syntheses for health economic evaluation would improve transparency and help prioritize data collection to reduce decision uncertainty.

Heterogeneity in the costs of medical care among people living with HIV/AIDS in the United States.

OBJECTIVE: The costs of medical care for people with HIV/AIDS (PWH) vary substantially across demographic groups, stages of disease progression and regionally across the United States. We aimed to estimate medical costs for PWH and examine the heterogeneity in costs within key patient groups typically distinguished in cost-effectiveness analyses. DESIGN: Retrospective cohort study using health administrative databases for diagnosed PWH in care at 17 HIV Research Network sites across the United States. METHODS: We estimated mean quarterly costs for key patient groups using multivariable generalized linear mixed effects models. We used quantile regression to highlight differences in the effect of covariates within each patient group (difference between covariate estimates at the mean versus the 90th percentile of quarterly costs), identifying covariates with a larger effect among the highest cost PWH, or generating greater uncertainty in mean cost estimates. RESULTS: Our sample included 40 022 patients with a median age of 39 years. Mean quarterly costs were highest for people who inject drugs with advanced disease progression and for PWH on antiretroviral treatment (ART). Within patient groups, we found the most heterogeneity at different levels of resource use for PWH on ART and PWH off ART with CD4 cell counts less than 200 cells/µl, people who inject drugs, as well as PWH in the South. CONCLUSION: The study quantifies heterogeneity in costs both across and within key PWH patient groups. Our results highlight the need for sensitivity analysis on cost estimates and may inform decisions on model structure in cost-effectiveness analyses on HIV/AIDS treatment and prevention strategies.

Why Maximizing Quality-Adjusted Life Years, rather than Reducing HIV Incidence, Must Remain Our Objective in Addressing the HIV/AIDS Epidemic.

With efficacious behavioral, biomedical, and structural interventions available, combination implementation strategies are being implemented to combat HIV/AIDS across settings internationally. However, priority statements from national and international bodies make it unclear whether the objective should be the reduction in HIV incidence or the maximization of health, most commonly measured with quality-adjusted life years (QALYs). Building off a model-based evaluation of HIV care interventions in British Columbia, Canada, we compare the optimal sets of interventions that would be identified using HIV infections averted, and QALYs as the primary outcome in a cost-effectiveness analysis. We found an explicit focus on averting new infections undervalues the health benefits derived from antiretroviral therapy, resulting in suboptimal and potentially harmful funding recommendations.

Developing a patient-reported experience questionnaire with and for people who use drugs: A community engagement process in Vancouver's Downtown Eastside.

People who use drugs (PWUD) frequently have complex health care needs, yet face multiple barriers to accessing services. Involving PWUD in health service design and evaluation can enhance the quality of data collected and ensure policy and practice improvements reflect the expressed needs of the population. However, PWUD remain largely excluded from the evaluation of health services that directly affect their lives, including development of patient-reported experience measures (PREMS) that have gained prominence in health services research and clinical practice. Detailed descriptions of PWUD participation in survey design are notably absent in the literature. In this commentary, we present a case that demonstrates how PWUD can contribute meaningfully to the development of questionnaires that assess patient-reported health care experiences. We describe the development, implementation and outcomes of a process to engage local drug user organizations in the evaluation of a redesign and reorientation of health service delivery in the Downtown Eastside (DTES) neighborhood of Vancouver, Canada. Through this process, participants contributed critical elements to the design of a patient-reported experience measure, including: (1) identifying unmet service needs in the neighborhood; (2) identifying local barriers and facilitators to care; (3) formulating questions on cultural safety; and (4) improving structure, language and clarity of the questionnaire. We highlight lessons learned from the process, reflecting on the strengths, challenges and ethical considerations associated with community-based approaches to questionnaire development. The workshop model presented here illustrates one flexible and promising approach to enabling meaningful participation of PWUD in questionnaire development.