Cost-Effectiveness of Increasing Access to Colorectal Cancer Diagnosis: Analysis From Thailand.

OBJECTIVES: The purpose of this study is to evaluate the cost-effectiveness of increasing access to colorectal cancer (CRC) diagnosis, considering resource limitations in Thailand. METHODS: We analyzed the cost-effectiveness of increasing access to fecal immunochemical test screening (strategy I), symptom evaluation (strategy II), and their combination through healthcare and societal perspectives using Colo-Sim, a simulation model of CRC care. We extended our analysis by adding a risk-stratification score (RS) to the strategies. We analyzed all strategies under the currently limited annual colonoscopy capacity and sufficient capacity. We estimated quality-adjusted life-years (QALYs) and costs over 2023 to 2047 and performed sensitivity analyses. RESULTS: Annual costs for CRC care will increase over 25 years in Thailand, resulting in a cumulative cost of 323B Thai baht (THB). Each strategy results in higher QALYs gained and additional costs. With the current colonoscopy capacity and willingness-to-pay threshold of 160 000 THB, strategy I with and without RS is not cost-effective. Strategy II + RS is the most cost-effective, resulting in 0.68 million QALYs gained with additional costs of 66B THB. Under sufficient colonoscopy capacity, all strategies are deemed cost-effective, with the combined approach (strategy I + II + RS) being the most favorable, achieving the highest QALYs (1.55 million) at an additional cost of 131 billion THB. This strategy also maintains the highest probability of being cost-effective at any willingness-to-pay threshold above 96 000 THB. CONCLUSIONS: In Thailand, fecal immunochemical test screening, symptom evaluation, and RS use can achieve the highest QALYs; however, boosting colonoscopy capacity is essential for cost-effectiveness.

Inclusion of marginalized populations in HPV vaccine modeling: A systematic review.

OBJECTIVE: Models simulating the potential impacts of Human Papillomavirus (HPV) vaccine have been used globally to guide vaccination policies and programs. We sought to understand how and why marginalized populations have been incorporated into HPV vaccine simulation models. METHODS: We conducted a systematic search of PubMed, CINAHL, Scopus, and Embase to identify studies using simulation models of HPV vaccination incorporating one or more marginalized population through stratification or subgroup analysis. We extracted data on study characteristics and described these overall and by included marginalized groups. RESULTS: We identified 36 studies that met inclusion criteria, which modeled vaccination in 21 countries. Models included men who have sex with men (MSM; k = 16), stratification by HIV status (k = 9), race/ethnicity (k = 6), poverty (k = 5), rurality (k = 4), and female sex workers (k = 1). When evaluating for a marginalized group (k = 10), HPV vaccination was generally found to be cost-effective, including for MSM, individuals living with HIV, and rural populations. In studies evaluating equity in cancer prevention (k = 9), HPV vaccination generally advanced equity, but this was sensitive to differences in HPV vaccine uptake and use of absolute or relative measures of inequities. Only one study assessed the impact of an intervention promoting HPV vaccine uptake. DISCUSSION: Incorporating marginalized populations into decision models can provide valuable insights to guide decision making and improve equity in cancer prevention. More research is needed to understand the equity impact of HPV vaccination on cancer outcomes among marginalized groups. Research should emphasize implementation - including identifying and evaluating specific interventions to increase HPV vaccine uptake.

Personalizing age of gastric cancer screening based on comorbidity in China: Model estimates of benefits, affordability and cost-effectiveness optimization.

The benefits of gastric cancer screening are related to age and comorbidity status, but reliable estimates are lacking in China. This study aimed to estimate the benefits and affordability of the gastric cancer screening strategy by level of comorbidity to inform decisions to screening age. We assessed six current gastric cancer screening strategies in China using a microsimulation model with different starting and stopping ages and comorbidity profiles, for a total of 378 strategies. 1,000,000 individuals were simulated in the model and followed the alternative strategies. Primary outcomes included gastric cancer incidence, the number of endoscopy and complications, life-years, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. Future costs and QALYs are discounted by 5% per year. Sensitivity analyses were used to evaluate model uncertainty. Strategies with longer screening durations were associated with higher benefits of life-year gained and gastric cancer deaths averted, but were also accompanied by a large number of endoscopy screening, and complication events. Using the threshold of US$18,575 per QALY gained, at the no, moderate, and severe comorbidity level, the leading cost-effectiveness strategies were the new gastric cancer screening scoring system strategy (NGCS) screening from age 40 years to 60 years (40-60), 40-55-NGCS, and 40-55-NGCS strategy, respectively. The results are robust in sensitivity analyses. Our study illustrates the importance of considering comorbidity conditions and age when determining the starting and stopping screening age for gastric cancer and informs the discussion on personalizing decisions. The trade-off between benefits and harms can also be referenced when necessary.

The long-term effectiveness and cost-effectiveness of public health interventions; how can we model behavior? A review.

The effectiveness and cost of a public health intervention is dependent on complex human behaviors, yet health economic models typically make simplified assumptions about behavior, based on little theory or evidence. This paper reviews existing methods across disciplines for incorporating behavior within simulation models, to explore what methods could be used within health economic models and to highlight areas for further research. This may lead to better-informed model predictions. The most promising methods identified which could be used to improve modeling of the causal pathways of behavior-change interventions include econometric analyses, structural equation models, data mining and agent-based modeling; the latter of which has the advantage of being able to incorporate the non-linear, dynamic influences on behavior, including social and spatial networks. Twenty-two studies were identified which quantify behavioral theories within simulation models. These studies highlight the importance of combining individual decision making and interactions with the environment and demonstrate the importance of social norms in determining behavior. However, there are many theoretical and practical limitations of quantifying behavioral theory. Further research is needed about the use of agent-based models for health economic modeling, and the potential use of behavior maintenance theories and data mining.

Mortality, incarceration and cost implications of fentanyl felonization laws: A modeling study.

BACKGROUND: Opioid overdose continues to be a major cause of death in the United States. One effort to control opioid use has been to implement policies that enhance criminalization of opioid possession. Laws to further criminalize possession of fentanyl have been enacted or are under consideration across the country, including at the national level. OBJECTIVE: Estimate the long-term effects on opioid death and incarceration resulting from increasingly strict fentanyl possession laws . DESIGN: We built a Markov simulation model to explore the potential outcomes of a 2022 Colorado law which made possession of >1 g of drug with any amount of fentanyl a Level 4 drug felony (and escalation of the previous law, where >4 g of any drug with any amount of fentanyl in possession was considered a felony). The model simulates a cohort of people with fentanyl possession moving through the criminal justice system, exploring the probability of overdose and incarceration under different scenarios, including various fentanyl possession policies and potential interventions. SETTING: Colorado PARTICIPANTS: A simulated cohort of people in possession of fentanyl. MEASUREMENTS: Number of opioid overdose deaths, people incarcerated, and associated costs over 5 years. RESULTS: When >4 g of a drug containing any amount of fentanyl is considered a felony in Colorado, the model predicts 5460 overdose deaths (95% CrI 410-9260) and 2,740 incarcerations for fentanyl possession (95% CrI: 230-10,500) over 5 years. When the policy changes so that >1 g possession of drug with fentanyl is considered a felony, opioid overdose deaths increase by 19% (95% CRI: 16-38%) and incarcerations for possession increase by 98% (CrI: 85-98%). Diversion programs and MOUD in prison help alleviate some of the increases in death and incarceration, but do not completely offset them. LIMITATIONS: The mathematical model is meant to offer broad assessment of the impact of these policies, not forecast specific and exact numerical outcomes. CONCLUSIONS: Our model shows that lowering thresholds for felony possession of fentanyl containing drugs can lead to more opioid overdose deaths and incarceration.

An Insurance Value Modeling Approach That Captures the Wider Value of a Novel Antimicrobial to Health Systems, Patients, and the Population.

Background: Traditional health economic evaluations of antimicrobials currently underestimate their value to wider society. They can be supplemented by additional value elements including insurance value, which captures the value of an antimicrobial in preventing or mitigating impacts of adverse risk events. Despite being commonplace in other sectors, constituents of the impacts and approaches for estimating insurance value have not been investigated. Objectives: This study assessed the insurance value of a novel gram-negative antimicrobial from operational healthcare, wider population health, productivity, and informal care perspectives. Methods: A novel mixed-methods approach was used to model insurance value in the United Kingdom: (1) literature review and multidisciplinary expert workshops to identify risk events for 4 relevant scenarios: ward closures, unavoidable shortage of conventional antimicrobials, viral respiratory pandemics, and catastrophic antimicrobial resistance (AMR); (2) parameterizing mitigable costs and frequencies of risk events across perspectives and scenarios; (3) estimating insurance value through a Monte Carlo simulation model for extreme events and a dynamic disease transmission model. Results: The mean insurance value across all scenarios and perspectives over 10 years in the UK was £718 million, should AMR remain unchanged, where only £134 million related to operational healthcare costs. It would be 50%-70% higher if AMR steadily increased or if a more risk-averse view (1-in-10 year downside) of future events is taken. Discussion: The overall insurance value if AMR remains at current levels (a conservative projection), is over 5 times greater than insurance value from just the operational healthcare costs perspective, traditionally the sole perspective used in health budgeting. Insurance value was generally larger for nationwide or universal (catastrophic AMR, pandemic, and conventional antimicrobial shortages) rather than localized (ward closure) scenarios, across perspectives. Components of this insurance value match previously published estimates of operational costs and mortality impacts. Conclusions: Insurance value of novel antimicrobials can be systematically modeled and substantially augments their traditional health economic value in normal circumstances. These approaches are generalizable to similar health interventions and form a framework for health systems and governments to capture broader value in health technology assessments, improve healthcare access, and increase resilience by planning for adverse scenarios.

The health and economic benefits of sugar taxation and vegetables and fruit subsidy scenarios in Canada.

A tax on sugar-sweetened beverages (SSB) has been implemented in various jurisdictions. Though research confirmed this tax to reduce sugar consumption and to prevent chronic diseases, it also revealed concerns: one concern relates to the small proportion of sugar in the diet coming from SSBs; and another concern relates to the disproportional tax burden to low-income groups. To inform public health decision makers on alternatives, we examined three 'real world' taxation and subsidy scenarios in Canada: 1) a CAD$0.75/100 g tax on SSBs; 2) a CAD$0.75/100 g tax on free sugar in all foods; and 3) a 20% subsidy on vegetables and fruit (V&F). Using national survey data and a proportional multi-state life table-based Markov model, we simulated the changes in disability-adjusted life years, healthcare costs, tax revenue, intervention costs, and incremental cost-effectiveness ratio for five income quintiles after implementing the three scenarios, over a lifetime of the 2015 Canadian adult population. The first, second and third scenario would prevent 28,921, 262,348 and 551 cases of type 2 diabetes, respectively. They would avert 752,353, 12,167,113, and 29,447 disability-adjusted life years and save CAD$12,942 million, 149,927 million, and 442 million in health care costs, respectively, over a lifetime. Combining the second and third scenarios would lead to the largest health and economic benefits. Although the lowest income quintile would bear a higher sugar tax burden (0.81% of income, CAD$120/person/year), this would be compensated by a coinciding subsidy on V&F (1.30% of income, CAD$194/person/year). These findings support policies that include a tax on all free sugar in foods and a subsidy on V&F as an effective means to reduce chronic diseases and health care costs. Although the sugar tax was financially regressive, the V&F subsidy could compensate for the tax burden of the disadvantaged groups and improve health and economic equity.

Designing Guidelines for Those Who Do Not Follow Them: The Impact of Adherence Assumptions on Optimal Screening Guidelines.

OBJECTIVES: Model-based cost-effectiveness analyses can inform decisions about screening guidelines by quantifying consequences of alternative algorithms. Although actual screening adherence is imperfect, incorporating nonadherence into analyses that aim to determine optimal screening may affect the policy recommendations. We evaluated the impact of nonadherence assumptions on the optimal cervical cancer screening in Norway. METHODS: We used a microsimulation model of cervical carcinogenesis to project the long-term health and economic outcomes under alternative screening algorithms and adherence patterns. We compared 18 algorithms involving primary human papillomavirus testing (5-yearly) that varied follow-up management of different human papillomavirus results. We considered 12 adherence scenarios: perfect adherence, 8 high- and low-coverage "random-complier" scenarios, and 3 "systematic-complier" scenarios that reflect conditional screening behavior over a lifetime. We calculated incremental cost-effectiveness ratios and considered a strategy with the highest incremental cost-effectiveness ratio < 55 000 US dollars/quality-adjusted life-year as "optimal." RESULTS: Under perfect adherence, the least intensive screening strategy was optimal; in contrast, assuming any nonadherence resulted in a more intensive optimal strategy. Accounting for lower adherence resulted in both lower costs and health benefits, which allowed for a more intensive strategy to be considered optimal, but more harms for women who screen according to guidelines (ie, up to 41% more colposcopies when comparing the optimal strategy in the lowest-adherence scenario with the optimal strategy under perfect adherence). CONCLUSIONS: Assuming nonadherence in analyses designed to inform national guidelines may lead to a relatively more intensive recommendation. Designing guidelines for those who do not adhere to them may lead to over-screening of those who do.

Cost-effectiveness of office-based buprenorphine treatment for opioid use disorder.

AIM: To assess the effectiveness and cost-effectiveness of office-based buprenorphine treatment (OBBT) in the U.S. DESIGN SETTING AND PARTICIPANTS: We performed a model-based analysis of buprenorphine treatment provided in a primary care setting for the U.S. population with OUD. INTERVENTION: Buprenorphine treatment provided in a primary care setting. MEASUREMENTS: Fatal and nonfatal overdoses and deaths over five years, discounted lifetime quality-adjusted life years (QALYs), costs. FINDINGS: For a cohort of 100,000 untreated individuals who enter OBBT, approximately 9350 overdoses would be averted over five years; of these, approximately 900 would have been fatal. OBBT compared to no treatment would yield 1.07 incremental lifetime QALYs per person at an incremental cost of $17,000 per QALY gained when using a healthcare perspective. If OBBT is half as effective and twice as expensive as assumed in the base case, the incremental cost when using a healthcare perspective is $25,500 per QALY gained. Using a limited societal perspective that additionally includes patient costs and criminal justice costs, OBBT is cost-saving compared to no treatment even under pessimistic assumptions about efficacy and cost. CONCLUSIONS: Expansion of OBBT would be highly cost-effective compared to no treatment when considered from a healthcare perspective, and cost-saving when reduced criminal justice costs are included. Given the continuing opioid crisis in the U.S., expansion of this care option should be a high priority.

Modeling the impact of a long-term horizon and multiple treatment episodes on estimates of the cost-effectiveness of alcohol treatment in the United States.

BACKGROUND: Most clinical studies of alcohol use disorder (AUD) treatment have short follow-up periods, underestimating the full benefits of alcohol treatment. Furthermore, clinical studies only consider one treatment cycle and do not account for the need for multiple episodes to treat a chronic recurrent condition. METHODS: A validated microsimulation model of the long-term drinking patterns of people with AUD in the United States simulated 10,000 individuals resembling those from a large clinical trial. The model was used to assess the impact of (1) 1-year, 5-year, and lifetime horizon on alcohol treatment cost-effectiveness estimates and (2) no, one, two, four, and unlimited additional treatment episodes on alcohol treatment cost-effectiveness estimates. Model outcomes included healthcare costs, crime costs, labor market productivity, life expectancy, quality-adjusted life years (QALYs), alcohol-related hospitalizations, and deaths. Cost-effectiveness analyses were conducted for two perspectives: a healthcare perspective that included costs from hospitalization and AUD treatment, and a broader societal perspective that also included crime costs and productivity. RESULTS: The incremental cost per additional QALY gained for alcohol treatment compared with no treatment decreased from $55,590 after 1 year to $78 when healthcare costs and QALYs were tracked over the lifetime, that is, treatment became more cost effective. Treatment was cost saving for any time frame when the impacts on crime and labor productivity were also accounted for in a societal perspective. Access to multiple treatment episodes dominated (i.e., it was more effective and less costly) than no-treatment and one-episode scenarios. From a healthcare perspective, incremental costs per additional QALY for increasing from a maximum of two to four treatment episodes was $499 and from four to unlimited episodes was $5049. The unlimited treatment scenario dominated all others from a societal perspective. Results were robust in sensitivity analyses. CONCLUSIONS: A long-term perspective and multiple episodes of alcohol treatment improve cost-effectiveness estimates. When societal impacts are included, alcohol treatment is cost saving. Results support the value of alcohol treatment.

The Cost-effectiveness of a Mass Media Campaign to Promote Smartphone Apps for Weight Loss: Updated Modeling Study.

BACKGROUND: Evidence suggests that smartphone apps can be effective in the self-management of weight. Given the low cost, broad reach, and apparent effectiveness of weight loss apps, governments may seek to encourage their uptake as a tool to reduce excess weight in the population. Mass media campaigns are 1 mechanism for promoting app use. However, the cost and potential cost-effectiveness are important considerations. OBJECTIVE: The aim of our study was to use modeling to assess the health impacts, health system costs, cost-effectiveness, and health equity of a mass media campaign to promote high-quality smartphone apps for weight loss in New Zealand. METHODS: We used an established proportional multistate life table model that simulates the 2011 New Zealand adult population over the lifetime, subgrouped by age, sex, and ethnicity (Maori [Indigenous] or non-Maori). The risk factor was BMI. The model compared business as usual to a one-off mass media campaign intervention, which included the pooled effect size from a recent meta-analysis of smartphone weight loss apps. The resulting impact on BMI and BMI-related diseases was captured through changes in health gain (quality-adjusted life years) and in health system costs. The difference in total health system costs was the net sum of intervention costs and downstream cost offsets because of altered disease rates. An annual discount rate of 3% was applied to health gains and health system costs. Multiple scenarios and sensitivity analyses were conducted, including an equity adjustment. RESULTS: Across the remaining lifetime of the modeled 2011 New Zealand population, the mass media campaign to promote weight loss app use had an estimated overall health gain of 181 (95% uncertainty interval 113-270) quality-adjusted life years and health care costs of -NZ $606,000 (-US $408,000; 95% uncertainty interval -NZ $2,540,000 [-US $1,709,000] to NZ $907,000 [US $610,000]). The mean health care costs were negative, representing overall savings to the health system. Across the outcomes examined in this study, the modeled mass media campaign to promote weight loss apps among the general population would be expected to provide higher per capita health gain for Maori and hence reduce health inequities arising from high BMI, assuming that the intervention would be as effective for Maori as it is for non-Maori. CONCLUSIONS: A modeled mass media campaign to encourage the adoption of smartphone apps to promote weight loss among the New Zealand adult population is expected to yield an overall gain in health and to be cost-saving to the health system. Although other interventions in the nutrition and physical activity space are even more beneficial to health and produce larger cost savings (eg, fiscal policies and food reformulation), governments may choose to include strategies to promote health app use as complementary measures.

Assessment of Non-Occupational 1,4-Dioxane Exposure Pathways from Drinking Water and Product Use.

1,4-Dioxane is a persistent and mobile organic chemical that has been found by the United States Environmental Protection Agency (USEPA) to be an unreasonable risk to human health in some occupational contexts. 1,4-Dioxane is released into the environment as industrial waste and occurs in some personal-care products as an unintended byproduct. However, limited exposure assessments have been conducted outside of an occupational context. In this study, the USEPA simulation modeling tool, Stochastic Human Exposure and Dose Simulator-High Throughput (SHEDS-HT), was adapted to estimate the exposure and chemical mass released down the drain (DTD) from drinking water consumption and product use. 1,4-Dioxane concentrations measured in drinking water and consumer products were used by SHEDS-HT to evaluate and compare the contributions of these sources to exposure and mass released DTD. Modeling results showed that compared to people whose daily per capita exposure came from only products (2.29 × 10-7 to 2.92 × 10-7 mg/kg/day), people exposed to both contaminated water and product use had higher per capita median exposures (1.90 × 10-6 to 4.27 × 10-6 mg/kg/day), with exposure mass primarily attributable to water consumption (75-91%). Last, we demonstrate through simulation that while a potential regulatory action could broadly reduce DTD release, the proportional reduction in exposure would be most significant for people with no or low water contamination.

Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer.

BACKGROUND: This study shows how dynamic simulation modeling can be applied in the context of the nationwide implementation of Whole Genome Sequencing (WGS) for non-small cell lung cancer (NSCLC) to inform organizational decisions regarding the use of complex and disruptive health technologies and how these decisions affect their potential value. METHODS: Using the case of the nationwide implementation of WGS into clinical practice in lung cancer in the Dutch healthcare system, we developed a simulation model to show that including service delivery features across the diagnostic pathway can provide essential insight into the affordability and accessibility of care at the systems level. The model was implemented as a hybrid Agent-Based Model and Discrete-Event Simulation model in AnyLogic and included 78 hospital agents, 7 molecular tumor board agents, 1 WGS facility agent, and 5313 patient agents each year in simulation time. RESULTS: The model included patient and provider heterogeneity, including referral patterns, capacity constraints, and diagnostic workflows. Patient preference and adoption by healthcare professionals were also modeled. The model was used to analyze a scenario in which only academic hospitals have implemented WGS. To prevent delays in the diagnostic pathway, the capacity to sequence at least 1600 biopsies yearly should be present. There is a two-fold increase in mean diagnostic pathway duration between no patients referred or all patients referred for further diagnostics. CONCLUSIONS: The systems model can complement conventional health economic evaluations to investigate how the organization of the workflow can influence the actual use and impact of WGS. Insufficient capacity to provide WGS and referral patterns can substantially impact the duration of the diagnostic pathway and thus should be considered in the implementation of WGS.

Modeling the cost-effectiveness and impact on fatal overdose and initiation of buprenorphine-naloxone treatment at syringe service programs.

AIM: To estimate the number of treatment initiations, averted fatal opioid overdoses and the cost-effectiveness associated with offering buprenorphine-naloxone (buprenorphine) treatment on-site within existing syringe service programs (SSPs) in Massachusetts, USA. DESIGN, SETTING AND PARTICIPANTS: This was a cohort-based mathematical model and cost-effectiveness analysis. We derived model inputs from state and national surveillance data, clinical trials and observational cohort studies. We compared an intervention scenario where 30% of SSP clients initiated buprenorphine treatment on-site at least once annually to a status quo scenario where no buprenorphine was available on-site among community treatment providers in Massachusetts, 2020-30. In individuals with opioid use disorder (OUD) we assumed that 80% of SSP clients had recently injected drugs and that treatment within SSPs would have similar or improved retention compared with standard-of-care buprenorphine programs, but higher rates of active opioid use while in treatment. MEASUREMENTS: Number of treatment initiations (i.e. individuals began treatment on a medication for opioid use disorder or entered medically managed withdrawal), averted fatal opioid overdoses, quality-adjusted life-years (QALYs) and life-time discounted costs from a health sector and a limited societal perspective. FINDINGS: The status quo scenario resulted in 23 051 fatal overdoses and 1 511 613 treatment initiations over a 10-year simulation period. An intervention scenario with on-site SSP buprenorphine treatment averted 4797 (-20.8%) fatal opioid overdoses and resulted in 129 359 (+8.6%) additional treatment initiations compared with the status quo. The intervention scenario was the dominating scenario: providing OUD treatment through Massachusetts SSPs cost less (-$3612 per person) with patients accumulating more QALYs (0.2 per person) compared with the status quo scenario. CONCLUSIONS: Offering buprenorphine treatment on-site within syringe service programs has the potential to decrease fatal overdoses substantially, improve treatment engagement and save on costs.

Population-level impact of initiating pharmacotherapy and linking to care people with opioid use disorder at inpatient medically managed withdrawal programs: an effectiveness and cost-effectiveness analysis.

BACKGROUND AND AIMS: Medications for opioid use disorder (MOUD) are shown to reduce opioid use and the risk of overdose. People with opioid use disorder (OUD) who exit inpatient medically managed withdrawal programs (detox) without initiating MOUD and linking to outpatient care have high rates of overdose. While detox encounters provide a theoretical opportunity for MOUD initiation, this is not ubiquitous in the United States. We used simulation modeling to estimate the population-level health effects and cost-effectiveness of a policy encouraging MOUD initiation during inpatient detox encounters. DESIGN, SETTING AND PARTICIPANTS: We employed a dynamic population state-transition model to evaluate the effectiveness and cost-effectiveness of using detox programs as venues for initiating MOUD in Massachusetts, United States. We compared standard of care, where no detox patients initiate MOUD or link to outpatient MOUD providers, to strategies of offering MOUD to detox patients and linking those patients to outpatient MOUD. MEASURES: Budgetary impact to the Massachusetts health-care sector, incremental cost-effectiveness ratios (ICER) and total counts and percentage differences of fatal overdoses prevented. FINDINGS: Initiating MOUD in detox with perfect linkage to outpatient MOUD would reduce fatal overdoses by 4.5% [95% confidence interval (CI) = 2.3-5.9], at an ICER of $56 000 per quality-adjusted life-year (QALY) gained, compared with the standard of care. With moderate linkage, fatal overdoses would be reduced by 2.3% (95% CI= 1.2-3.1) with an ICER of $78 500 per QALY gained, compared with standard of care. Budgetary increase to Massachusetts health-care spending ranged from 0.5-1%. CONCLUSION: A simulation model indicates that initiation of medications for opioid use disorder and linkage policies among detox patients in Massachusetts, USA could prevent fatal opioid overdoses in the opioid use disorder population and would be cost-effective from a health-care sector perspective.

Duration and cost-effectiveness of hepatocellular carcinoma surveillance in hepatitis C patients after viral eradication.

BACKGROUND & AIMS: Successful treatment of chronic hepatitis C with oral direct-acting antivirals (DAAs) leads to virological cure, however, the subsequent risk of hepatocellular carcinoma (HCC) persists. Our objective was to evaluate the cost-effectiveness of biannual surveillance for HCC in patients cured of hepatitis C and the optimal age to stop surveillance. METHODS: We developed a microsimulation model of the natural history of HCC in individuals with hepatitis C and advanced fibrosis or cirrhosis who achieved virological cure with oral DAAs. We used published data on HCC incidence, tumor progression, real-world HCC surveillance adherence, and costs and utilities of different health states. We compared biannual HCC surveillance using ultrasound and alpha-fetoprotein for varying durations of surveillance (from 5 years to lifetime) vs. no surveillance. RESULTS: In virologically cured patients with cirrhosis, the incremental cost-effectiveness ratio (ICER) of biannual surveillance remained below $150,000 per additional quality-adjusted life year (QALY) (range: $79,500-$94,800) when surveillance was stopped at age 70, irrespective of the starting age (40-65). Compared with no surveillance, surveillance detected 130 additional HCCs in 'very early'/early stage and yielded 51 additional QALYs per 1,000 patients with cirrhosis. In virologically cured patients with advanced fibrosis, the ICER of biannual surveillance remained below $150,000/QALY (range: $124,600-$129,800) when surveillance was stopped at age 60, irrespective of the starting age (40-50). Compared with no surveillance, surveillance detected 24 additional HCCs in 'very early'/early stage and yielded 12 additional QALYs per 1,000 patients with advanced fibrosis. CONCLUSION: Biannual surveillance for HCC in patients cured of hepatitis C is cost-effective until the age of 70 for patients with cirrhosis, and until the age of 60 for patients with stable advanced fibrosis. LAY SUMMARY: Individuals who are cured of hepatitis C using oral antiviral drugs remain at risk of developing liver cancer. The value of lifelong screening for liver cancer in these individuals is not known. By simulating the life course of hepatitis C cured individuals, we found that ultrasound-based biannual screening for liver cancer is cost-effective up to age 70 in those with cirrhosis and up to age 60 in those with stable advanced fibrosis.

Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities.

BACKGROUND: Simulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities. We aim to disaggregate one type of Markov macro-simulation model, the proportional multistate lifetable, ensuring that under business-as-usual (BAU) the sum of deaths across disaggregated strata in each time step returns the same as the initial non-disaggregated model. We then demonstrate the application by deprivation quintiles for New Zealand (NZ), for: hypothetical interventions (50% lower all-cause mortality, 50% lower coronary heart disease mortality) and a dietary intervention to substitute 59% of sodium with potassium chloride in the food supply. METHODS: We developed a disaggregation algorithm that iteratively rescales mortality, incidence and case-fatality rates by time-step of the model to ensure correct total population counts were retained at each step. To demonstrate the algorithm on deprivation quintiles in NZ, we used the following inputs: overall (non-disaggregated) all-cause mortality & morbidity rates, coronary heart disease incidence & case fatality rates; stroke incidence & case fatality rates. We also obtained rate ratios by deprivation for these same measures. Given all-cause and cause-specific mortality rates by deprivation quintile, we derived values for the incidence, case fatality and mortality rates for each quintile, ensuring rate ratios across quintiles and the total population mortality and morbidity rates were returned when averaged across groups. The three interventions were then run on top of these scaled BAU scenarios. RESULTS: The algorithm exactly disaggregated populations by strata in BAU. The intervention scenario life years and health adjusted life years (HALYs) gained differed slightly when summed over the deprivation quintile compared to the aggregated model, due to the stratified model (appropriately) allowing for differential background mortality rates by strata. Modest differences in health gains (HALYs) resulted from rescaling of sub-population mortality and incidence rates to ensure consistency with the aggregate population. CONCLUSION: Policy makers ideally need to know the effect of population interventions estimated both overall, and by socioeconomic and other strata. We demonstrate a method and provide code to do this routinely within proportional multistate lifetable simulation models and similar Markov models.

Risk Stratification in Cost-Effectiveness Analyses of Cancer Screening: Intervention Eligibility, Strategy Choice, and Optimality.

INTRODUCTION: There is increasing interest in risk-stratified approaches to cancer screening in cost-effectiveness analysis (CEA). Current CEA practice regarding risk stratification is heterogeneous and guidance on the best approach is lacking. This article suggests how stratification in CEA can be improved. METHODS: I use a simple example of a hypothetical screening intervention with 3 potential recipient risk strata. The screening intervention has 6 alternative intensities, each with different costs and effects, all of which vary between strata. I consider a series of alternative stratification approaches, demonstrating the consequences for estimated costs, effects, and the choice of optimal strategy. I supplement this analysis with applied examples from the literature. RESULTS: Adopting the same screening policy for all strata yields the least efficient strategies, where efficiency is understood as the volume of net health benefit generated across a range of cost-effectiveness threshold values. Basic stratification that withholds screening from lower-risk strata while adopting a common strategy for those screened increases efficiency. Greatest efficiency is achieved when different strata receive separate strategies. While complete optimization can be achieved within a single analysis by considering all possible policy combinations, the resulting number of strategy combinations may be inconveniently large. Optimization with separate strata-specific analyses is simpler and more transparent. Despite this, there can be good reasons to simulate all strata together in a single analysis. CONCLUSIONS: If the benefits of risk stratification are to be fully realized, policy makers need to consider the extent to which stratification is feasible, and modelers need to simulate those choices adequately. It is hoped this analysis will clarify those policy and modeling choices and therefore lead to improved population health outcomes.

Cost-effectiveness analysis of the 2019 American Society for Colposcopy and Cervical Pathology Risk-Based Management Consensus Guidelines for the management of abnormal cervical cancer screening tests and cancer precursors.

BACKGROUND: The guidelines for managing abnormal cervical cancer screening tests changed from a results-based approach in 2012 to a risk-based approach in 2019. OBJECTIVE: We estimated the cost-effectiveness of the 2019 management guidelines and the changes in resource utilization moving from 2012 to 2019 guidelines. STUDY DESIGN: We utilized a previously published model of cervical cancer natural history and screening to estimate and compare the lifetime costs and the number of screens, colposcopies, precancer treatments, cancer cases, and cancer deaths associated with the 2012 vs 2019 management guidelines. We assessed these guidelines under the scenarios of observed screening practice and perfect screening adherence to 3-year cytology starting at age 21, with a switch to either 3-year or 5-year cytology plus human papillomavirus cotesting at age 30. In addition, we estimated the lifetime costs and life years to determine the cost-effectiveness of shifting to the 2019 management guidelines. RESULTS: Under the assumptions of both observed screening practice and perfect screening adherence with a strategy of 3-year cytology at ages 21 to 29 and switching to 3-year cotesting at age 30, the management of the screening tests according to the 2019 guidelines was less costly and more effective than the 2012 guidelines. For 3-year cytology screening at ages 21 to 29 and switching to 5-year cotesting at age 30, the 2019 guidelines were more cost-effective at a willingness-to-pay threshold of $100,000 per life year gained. Across all scenarios, the 2019 management guidelines were associated with fewer colposcopies and cancer deaths. CONCLUSION: Our model-based analysis suggests that the 2019 guidelines are more effective overall and also more cost-effective than the 2012 guidelines, supporting the principle of "equal management of equal risks."

A benefit-cost analysis of different response scenarios to COVID-19: A case study.

BACKGROUND: This paper compares the direct benefits to the State of Western Australia from employing a "suppression" policy response to the COVID-19 pandemic rather than a "herd immunity" approach. METHODS: An S-I-R (susceptible-infectious-resolved) model is used to estimate the likely benefits of a suppression COVID-19 response compared to a herd immunity alternative. Direct impacts of the virus are calculated on the basis of sick leave, hospitalizations, and fatalities, while indirect impacts related to response actions are excluded. RESULTS: Preliminary modeling indicates that approximately 1700 vulnerable person deaths are likely to have been prevented over 1 year from adopting a suppression response rather than a herd immunity response, and approximately 4500 hospitalizations. These benefits are valued at around AUD4.7 billion. If a do nothing policy had been adopted, the number of people in need of hospitalization is likely to have overwhelmed the hospital system within 50 days of the virus being introduced. Maximum hospital capacity is unlikely to be reached in either a suppression policy or a herd immunity policy. CONCLUSION: Using early international estimates to represent the negative impact each type of policy response is likely to have on gross state product, results suggest the benefit-cost ratio for the suppression policy is slightly higher than that of the herd immunity policy, but both benefit-cost ratios are less than one.