The Rising Costs of Alcohol-Associated Liver Disease in the United States.

INTRODUCTION: Alcohol-associated liver disease (ALD) is rising in the United States because of an increase in high-risk drinking, but population-level ALD cost is unknown. Our aim was to project the direct and indirect costs associated with ALD in the US population through 2040. METHODS: We used a previously validated microsimulation model of alcohol consumption and ALD with model parameters estimated from publicly available data sources, including the National Epidemiologic Survey Alcohol and Related Conditions-III, the Center for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research, the Bureau of Labor Statistics, and published studies informing the impact of alcohol consumption on ALD severity in the United States resident population. The simulated scenario included current and projected ALD-associated costs. RESULTS: From 2022 to 2040, the ALD is projected to cost $880 billion, $355 billion in direct healthcare-related costs, and $525 billion in lost labor and economic consumption. The annual cost of ALD is projected to increase from $31 billion in 2022 to $66 billion (118% increase) in 2040. Although the female population makes up 29% of these costs in 2022, by 2040 on a per annum basis, female costs would be 43% of the total annual expenditure. DISCUSSION: Increased consumption of alcohol in the US population, especially in females, will cause a steep rise in the economic burden of ALD in the United States. These findings highlight the need for planners and policymakers to plan for the increased impact of liver disease in the United States.

Telemental Health Utilization in Commercial Health Insurance Plans in the United States From 2010 Through 2019.

Objective: We sought to characterize patterns of utilization of telemental health among commercially insured individuals over the decade preceding COVID-19.Methods: We developed telemental health service groups from the US PharMetrics Plus database, using diagnostic codes to identify those diagnosed with mental health conditions and procedure codes to capture mental health visits delivered via telehealth sessions. We analyzed 2 indicators of utilization between January 1, 2010, and December 31, 2019: (1) the percentage of patients with mental health needs who used telemental health services and (2) the percentage of all mental health services provided via telehealth. We stratified our analyses by year, patient gender, patient age, and geographic region.Results: The proportion of mental health visits delivered via telemental health increased from 0.002% to 0.162% between 2010 and 2019. A larger proportion of males received telemental health services as compared to females; however, the proportion of mental health visits delivered via telehealth was higher for females than for males. Patients aged 18 to 34 years and those in the western US had the highest utilization compared to other age groups and geographic regions.Conclusions: Telemental health utilization comprised a small fraction of overall mental health services and beneficiaries in the IQVIA PharMetrics Plus claims data, but increased over time, with differences documented in utilization based on patient gender, patient age, geographic region, and type of telemental health claim. Evidence from this study may serve as a pre-pandemic baseline for comparison against future evaluations of telehealth expansion policies.

Interpersonal Primary Care Continuity for Chronic Conditions Is Associated with Fewer Hospitalizations and Emergency Department Visits Among Medicaid Enrollees.

BACKGROUND: Interpersonal primary care continuity or chronic condition continuity (CCC) is associated with improved health outcomes. Ambulatory care-sensitive conditions (ACSC) are best managed in a primary care setting, and chronic ACSC (CACSC) require management over time. However, current measures do not measure continuity for specific conditions or the impact of continuity for chronic conditions on health outcomes. The purpose of this study was to design a novel measure of CCC for CACSC in primary care and determine its association with health care utilization. METHODS: We conducted a cross-sectional analysis of continuously enrolled, nondual eligible adult Medicaid enrollees with a diagnosis of a CACSC using 2009 Medicaid Analytic eXtract files from 26 states. We conducted adjusted and unadjusted logistic regression models of the relationship between patient continuity status and emergency department (ED) visits and hospitalizations. Models were adjusted for age, sex, race/ethnicity, comorbidity, and rurality. We defined CCC for CACSC as at least 2 outpatient visits with any primary care physician for a CACSC in the year, and (2) more than 50% of outpatient CACSC visits with a single PCP. RESULTS: There were 2,674,587 enrollees with CACSC and 36.3% had CCC for CACSC visits. In fully adjusted models, enrollees with CCC were 28% less likely to have ED visits compared with those without CCC (aOR = 0.71, 95% CI = 0.71 - 0.72) and were 67% less likely to have hospitalization than those without CCC (aOR = 0.33, 95% CI = 0.32-0.33). CONCLUSIONS: CCC for CACSCs was associated with fewer ED visits and hospitalizations in a nationally representative sample of Medicaid enrollees.

Cost-Effectiveness and Value-of-Information Analysis Using Machine Learning-Based Metamodeling: A Case of Hepatitis C Treatment.

BACKGROUND: Metamodels can address some of the limitations of complex simulation models by formulating a mathematical relationship between input parameters and simulation model outcomes. Our objective was to develop and compare the performance of a machine learning (ML)-based metamodel against a conventional metamodeling approach in replicating the findings of a complex simulation model. METHODS: We constructed 3 ML-based metamodels using random forest, support vector regression, and artificial neural networks and a linear regression-based metamodel from a previously validated microsimulation model of the natural history hepatitis C virus (HCV) consisting of 40 input parameters. Outcomes of interest included societal costs and quality-adjusted life-years (QALYs), the incremental cost-effectiveness (ICER) of HCV treatment versus no treatment, cost-effectiveness analysis curve (CEAC), and expected value of perfect information (EVPI). We evaluated metamodel performance using root mean squared error (RMSE) and Pearson's R2 on the normalized data. RESULTS: The R2 values for the linear regression metamodel for QALYs without treatment, QALYs with treatment, societal cost without treatment, societal cost with treatment, and ICER were 0.92, 0.98, 0.85, 0.92, and 0.60, respectively. The corresponding R2 values for our ML-based metamodels were 0.96, 0.97, 0.90, 0.95, and 0.49 for support vector regression; 0.99, 0.83, 0.99, 0.99, and 0.82 for artificial neural network; and 0.99, 0.99, 0.99, 0.99, and 0.98 for random forest. Similar trends were observed for RMSE. The CEAC and EVPI curves produced by the random forest metamodel matched the results of the simulation output more closely than the linear regression metamodel. CONCLUSIONS: ML-based metamodels generally outperformed traditional linear regression metamodels at replicating results from complex simulation models, with random forest metamodels performing best. HIGHLIGHTS: Decision-analytic models are frequently used by policy makers and other stakeholders to assess the impact of new medical technologies and interventions. However, complex models can impose limitations on conducting probabilistic sensitivity analysis and value-of-information analysis, and may not be suitable for developing online decision-support tools.Metamodels, which accurately formulate a mathematical relationship between input parameters and model outcomes, can replicate complex simulation models and address the above limitation.The machine learning-based random forest model can outperform linear regression in replicating the findings of a complex simulation model. Such a metamodel can be used for conducting cost-effectiveness and value-of-information analyses or developing online decision support tools.

Cervical cancer geographical burden analyzer: An interactive, open-access tool for understanding geographical disease burden in patients with recurrent or metastatic cervical cancer.

OBJECTIVE: Cervical cancer (CC) disproportionately affects women based on socioeconomic status and racial/ethnic background. There is limited research in quantifying and visualizing whether substantial geographical disparities in the US exist with respect to CC burden, and especially with respect to recurrent or metastatic CC (r/mCC) disease burden. Identifying regions with higher r/mCC burden may help inform effective healthcare resource allocation and navigating patients to appropriate care. METHODS: We conducted a retrospective analysis of the 2015-2020 MarketScan® Commercial and Supplemental Medicare claims data; r/mCC burden was estimated as the number of patients initiating r/mCC systemic therapy over CC-diagnosed patients for each of the 410 metropolitan statistical areas (MSAs) considered. We developed a public, web-based tool, the Cervical Cancer Geographical Disease Burden Analyzer (Cervical Cancer Geo-Analyzer, http://www.geo-analyzer.org), that allows users to visualize r/mCC burden across MSAs over multiple years. RESULTS: There was considerable variation in r/mCC burden across MSAs, with a range of 0-83.3%. Burden increased in Boston-Cambridge-Newton, MA (r/mCC to CC ratio: 41% in 2018 to 50% in 2020), and Sacramento-Roseville-Arden-Arcade, CA (33% in 2018 to 50% in 2020). On the other hand, while r/mCC burden remained high, it decreased in Grand Rapids, MI (55% in 2018 to 31% in 2020) and San Francisco-Oakland-Hayward, CA (40% in 2018 to 26% in 2020). There were regions with sparse or no data, suggesting a need for more representative data capture. CONCLUSION: The Cervical Geo-Analyzer is a tool to visualize areas with high need for CC interventions. It also builds the foundation for further work to understand local risk factors of disease burden, identify populations of interest, characterize health disparities of CC or r/mCC and inform targeted interventions.

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.

Increasing Utilization of Emergency Department Neuroimaging From 2007 Through 2017.

BACKGROUND. The volume of emergency department (ED) visits and the number of neuroimaging examinations have increased since the start of the century. Little is known about this growth in the commercially insured and Medicare Advantage populations. OBJECTIVE. The purpose of our study was to evaluate changing ED utilization of neuroimaging from 2007 through 2017 in both commercially insured and Medicare Advantage enrollees. METHODS. Using patient-level claims from Optum's deidentified Clinformatics Data Mart database, which annually includes approximately 12-14 million commercial and Medicare Advantage health plan enrollees, annual ED utilization rates of head CT, head MRI, head CTA, neck CTA, head MRA, neck MRA, and carotid duplex ultrasound (US) were assessed from 2007 through 2017. To account for an aging sample population, utilization rates were adjusted using annual relative proportions of age groups and stratified by patient demographics, payer type, and provider state. RESULTS. Between 2007 and 2017, age-adjusted ED neuroimaging utilization rates per 1000 ED visits increased 72% overall (compound annual growth rate [CAGR], 5%). This overall increase corresponded to an increase of 69% for head CT (CAGR, 5%), 67% for head MRI (CAGR, 5%), 1100% for head CTA (CAGR, 25%), 1300% for neck CTA (CAGR, 27%), 36% for head MRA (CAGR, 3%), and 52% for neck MRA (CAGR, 4%) and to a decrease of 8% for carotid duplex US (CAGR, -1%). The utilization of head CT and CTA of the head and neck per 1000 ED visits increased in enrollees 65 years old or older by 48% (CAGR, 4%) and 1011% (CAGR, 24%). CONCLUSION. Neuroimaging utilization in the ED grew considerably between 2007 and 2017, with growth of head and neck CTA far outpacing the growth of other modalities. Unenhanced head CT remains by far the dominant ED neuroimaging examination. CLINICAL IMPACT. The rapid growth of head and neck CTA observed in the fee-for-service Medicare population is also observed in the commercially insured and Medicare Advantage populations. The appropriateness of this growth should be monitored as the indications for CTA expand.

Assessment of Incidence of and Surveillance Burden for Hepatocellular Carcinoma Among Patients With Hepatitis C in the Era of Direct-Acting Antiviral Agents.

Importance: In the US, hepatocellular carcinoma (HCC), primarily associated with hepatitis C virus (HCV) infection, is the fastest rising cause of cancer-related death. Wider use of highly effective direct-acting antiviral agents (DAAs) substantially reduces the burden of chronic HCV infection, but the subsequent impacts with HCV-associated HCC remain unknown. Objective: To assess projected changes in the incidence rate of and surveillance burden for HCC in the era of DAA treatment for HCV. Design, Setting, and Participants: This decision analytical model study was performed from January 2019 to February 2020, using an individual-level state-transition simulation model to simulate disease progression, screening, and different waves of antiviral treatments for HCV in the US from 2012 to 2040. Interventions: Current clinical management for chronic HCV infection. Main Outcomes and Measures: Model outcomes were projected temporal trends and age distribution of incident HCC cases and candidates for HCC surveillance among patients with viremia and patients with virologically cured HCV. Results: The simulation model projected that the annual incidence of HCC among patients with viremia and patients with virologically cured HCV will continue increasing to 24 000 (95% uncertainty interval [UI], 18 000-31 000) cases until 2021. In patients with virologically cured HCV, incident HCC cases are projected to increase from 1000 (95% UI, 500-2100) in 2012 to the peak of 7000 (95% UI, 5000-9600) in 2031 with a subsequent decrease to 6000 (95% UI, 4300-8300) by 2040. The proportion of incident HCC cases that occur in individuals with virologically cured HCV is estimated to increase from 5.3% in 2012 to 45.8% in 2040. The number of candidates for HCC surveillance in the population with virologically cured HCV is projected to increase from 106 000 (95% UI, 70 000-178 000) in 2012 to the peak of 649 000 (95% UI, 512 000-824 000) in 2030 and decrease to 539 000 (95% UI, 421 000-687 000) by 2040, while the proportion of all candidates for surveillance who are virologically cured is estimated to increase from 8.5% to 64.6% during the same period. The average age of HCC incidence and surveillance candidates is estimated to increase from 55 in 2012 to 72 and 71, respectively, by 2040. Conclusions and Relevance: The results of this study suggest that the burden of HCC will shift from patients with viremia to patients with virologically cured HCV, and to older populations. Appropriate management may be warranted for early detection of HCC in patients who may no longer be receiving specialty care for liver conditions.

Primary Care Comprehensiveness and Care Coordination in Robust Specialist Networks Results in Lower Emergency Department Utilization: A Network Analysis of Medicaid Physician Networks.

Background: Care coordination is an essential and difficult to measure function of primary care. Objective: Our objective was to assess the impact of network characteristics in primary/specialty physician networks on emergency department (ED) visits for patients with chronic ambulatory care sensitive conditions (ACSCs). Subjects and Measures: This cross-sectional social network analysis of primary care and specialty physicians caring for adult Medicaid beneficiaries with ACSCs was conducted using 2009 Texas Medicaid Analytic eXtract (MAX) files. Network characteristic measures were the main exposure variables. A negative binomial regression model analyzed the impact of network characteristics on the ED visits per patient in the panel. Results: There were 42 493 ACSC patients assigned to 5687 primary care physicians (PCPs) connected to 11 660 specialist physicians. PCPs whose continuity patients did not visit a specialist had 86% fewer ED visits per patient in their panel, compared with PCPs whose patients saw specialists. Among PCPs connected to specialists in the network, those with a higher number of specialist collaborators and those with a high degree of centrality had lower patient panel ED rates. Conclusions: PCPs providing comprehensive care (ie, without specialist consultation) for their patients with chronic ACSCs had lower ED utilization rates than those coordinating care with specialists. PCPs with robust specialty networks and a high degree of centrality in the network also had lower ED utilization. The right fit between comprehensiveness of primary care, care coordination, and adequate capacity of specialty availability in physician networks is needed to drive outcomes.

Improved Health Outcomes from Hepatitis C Treatment Scale-Up in Spain's Prisons: A Cost-Effectiveness Study.

Hepatitis C virus (HCV) is 15 times more prevalent among persons in Spain's prisons than in the community. Recently, Spain initiated a pilot program, JAILFREE-C, to treat HCV in prisons using direct-acting antivirals (DAAs). Our aim was to identify a cost-effective strategy to scale-up HCV treatment in all prisons. Using a validated agent-based model, we simulated the HCV landscape in Spain's prisons considering disease transmission, screening, treatment, and prison-community dynamics. Costs and disease outcomes under status quo were compared with strategies to scale-up treatment in prisons considering prioritization (HCV fibrosis stage vs. HCV prevalence of prisons), treatment capacity (2,000/year vs. unlimited) and treatment initiation based on sentence lengths (>6 months vs. any). Scaling-up treatment by treating all incarcerated persons irrespective of their sentence length provided maximum health benefits-preventing 10,200 new cases of HCV, and 8,300 HCV-related deaths between 2019-2050; 90% deaths prevented would have occurred in the community. Compared with status quo, this strategy increased quality-adjusted life year (QALYs) by 69,700 and costs by €670 million, yielding an incremental cost-effectiveness ratio of €9,600/QALY. Scaling-up HCV treatment with DAAs for the entire Spanish prison population, irrespective of sentence length, is cost-effective and would reduce HCV burden.

Assessment of the Feasibility and Cost of Hepatitis C Elimination in Pakistan.

Importance: Chronic hepatitis C virus (HCV) infection is a global health problem. The World Health Assembly recently pledged to eliminate HCV by 2030. However, in Pakistan, a country with one of the highest prevalence rates, the feasibility and cost of HCV elimination are not known. Objectives: To investigate whether and under what conditions HCV elimination is feasible in Pakistan and to estimate the cost of such elimination. Design, Setting, and Participants: This decision analytical model study used a microsimulation model of the HCV epidemic in Pakistan from 2015 to 2030. Using Pakistan-specific variables, the model simulated the landscape of HCV in Pakistan and evaluated the minimum required screening and treatment rates needed to eliminate HCV in Pakistan. The study used simulated individuals chronically infected with HCV from 2015 to 2030. The analysis was performed in 2018. Interventions: The status quo and 7 scenarios that can lead to HCV elimination in Pakistan by 2030, which were defined by different combinations of tests for screening, detection of viremia before treatment, and confirmation of treatment response. Main Outcomes and Measures: Temporal trends in HCV infection prevalence, mortality, and disability-adjusted life-years and total cost of HCV infection care under the status quo and scenarios that can eliminate HCV by 2030. Results: Under the status quo, from 2015 to 2030, 1.44 million people are projected to die of HCV infection; 48% of deaths would be among people younger than 50 years. To achieve HCV elimination in Pakistan, HCV testing would need to be scaled up to at least 25 million people to diagnose 900 000 persons and treatment to 700 000 people per year. Compared with the status quo, the elimination scenario would avert 323 000 liver-related deaths and 13.0 million HCV-associated disability-adjusted life-years from 2015 to 2030. The elimination scenario was associated with cost savings of $2.6 billion from 2018 to 2030 with use of a point-of-care test for population-wide antibody screening and detection of viremia and treatment response. Conclusions and Relevance: Substantial scale-up of HCV testing and treatment may be essential to eliminate HCV infection in Pakistan, and such a strategy may be associated with cost savings in the near future. Although HCV elimination in Pakistan may be ambitious, strategic planning and strong support from the government may aid in its elimination.

A population-based multistate model for diffuse large B-cell lymphoma-specific mortality in older patients.

BACKGROUND: Despite effective therapies, outcomes for diffuse large B-cell lymphoma (DLCBL) remain heterogeneous in older individuals due to comorbid diseases and variations in disease biology. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database, the authors conducted a multistate survival analysis of 11,780 patients with DLBCL who were aged ≥65 years at the time of diagnosis (2002-2009). Cox proportional hazards models were used to specify the impact of prognostic factors on overall survival and cause-specific deaths, and the Aalen-Johansen estimator was used to project the course of DLBCL over time with or without standard therapy with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). RESULTS: Advanced age (hazard ratio [HR] for ages 71-75 years: 1.25; HR for ages 76-80 years: 1.46; HR for ages 81-85 years: 1.88; and HR for age ≥86 years: 2.26), DLBCL stage (HR for Ann Arbor stage II: 1.28; HR for stage III: 1.54; and HR for stage IV: 1.95), Charlson Comorbidity Index (CCI) ≥1 (HR for CCI of 1, 1.15; and HR for CCI >1, 1.37), and not being married (HR, 1.12) were associated with an increased risk of DLBCL-specific death. Being female (HR, 0.91) and of higher socioeconomic status (HR, 0.91) were associated with a lower risk of DLBCL-related mortality after therapy. For patients treated with R-CHOP (3610 patients), the risk of death due to DLBCL was 14.0% and 18.6%, respectively, at 2 and 5 years of treatment and plateaued afterward, confirming a 5-year "cure" point while receiving R-CHOP among older patients. CONCLUSIONS: Conducting a survival analysis over a large data set, the current study evaluated competing risks for death within a multistate modeling framework, and identified age, sex, and CCI as risk factors for DLBCL-specific and other causes of death.

Assessing the Effectiveness of Treatment Sequences for Older Patients With High-risk Follicular Lymphoma With a Multistate Model.

BACKGROUND: Disease progression within < 2 years of initial chemoimmunotherapy and patient age > 60 years have been associated with poor overall survival (OS) in follicular lymphoma (FL). No standard treatment exists for these high-risk patients, and the effectiveness of sequential therapies remains unclear. PATIENTS AND METHODS: We studied the course of FL with first-, second-, and third-line treatment. Using large population-based data, we identified 5234 patients with FL diagnosed in 2000 to 2009. Of these patients, 71% had received second-line therapy < 2 years, and 29% had received no therapy after first-line therapy, with a median OS of < 3 years. Treatment included rituximab, R-CVP (rituximab, cyclophosphamide, vincristine), R-CHOP (rituximab, cyclophosphamide, hydroxydaunorubicin, vincristine), R-Other (other rituximab-containing), and other regimens. The Aalen-Johansen estimator and Cox proportional hazards models were used to quantify the outcomes and assess the effects of the clinical and sociodemographic factors. RESULTS: R-CHOP demonstrated the most favorable 5-year OS among first- (71%), second- (55%), and third-line (61%) therapies. First-line R-CHOP improved OS (hazard ratio [HR], 0.57; 95% confidence interval [CI], 0.50-0.64) and reduced the mortality risks after first-line (HR, 0.60; 95% CI, 0.47-0.77), second-line (HR, 0.40; 95% CI, 0.29-0.53), and third-line (HR, 0.63; 95% CI, 0.53-0.76) treatments. B-symptoms, being married, and histologic grade 1/2 were associated with the use of earlier second-line therapy. Early progression from second- to third-line therapy was associated with poor OS. The repeated use of R-CHOP or R-CVP as first- and second-line treatment yielded high 2-year mortality rates (R-CHOP + R-CHOP, 17.3%; R-CVP + R-CVP, 21.1%). CONCLUSION: Our multistate approach assessed the effect of sequential therapy on the immediate and subsequent treatment-line outcomes. We found that R-CHOP in any line improved OS for patients with high-risk FL.

Cost Effectiveness of Transplanting HCV-Infected Livers Into Uninfected Recipients With Preemptive Antiviral Therapy.

BACKGROUND & AIMS: Guidelines do not recommend transplanting hepatitis C virus (HCV)-infected livers into HCV-uninfected recipients. Direct-acting antivirals (DAAs) can be used to treat donor-derived HCV infection. However, the added cost of DAA therapy is a barrier. We evaluated the cost effectiveness of transplanting HCV-positive livers into HCV-negative patients with preemptive DAA therapy. METHODS: A previously validated Markov-based mathematical model was adapted to simulate a virtual trial of HCV-negative patients on the liver transplant waitlist. The model compared long-term clinical and economic outcomes in patients willing to accept only HCV-negative livers vs those willing to accept any liver (HCV negative or HCV positive). Recipients of HCV-positive livers received 12 weeks of preemptive DAA therapy. The model incorporated data from the United Network for Organ Sharing and published sources. RESULTS: For patients with a model for end-stage liver disease (MELD) score ≥ 22, accepting any liver vs waiting for only HCV-negative livers was cost effective, with incremental cost-effectiveness ratios ranging from $56,100 to $91,700/quality-adjusted life-year. For patients with a MELD score of 28 (the median MELD score of patients undergoing transplantation in the United States), accepting any liver was cost effective at an incremental cost-effectiveness ratio of $62,600/quality-adjusted life year. In patients with low MELD scores, which may not accurately reflect disease severity, accepting any liver was cost effective, irrespective of MELD score. CONCLUSIONS: Using a Markov-based mathematical model, we found transplanting HCV-positive livers into HCV-negative patients with preemptive DAA therapy to be a cost-effective strategy that could improve health outcomes.

Cost Effectiveness of Pre- vs Post-Liver Transplant Hepatitis C Treatment With Direct-Acting Antivirals.

BACKGROUND & AIMS: Oral direct-acting antivirals (DAAs) for hepatitis C virus (HCV) treatment offer new hope to both pre- and post-liver transplant (LT) patients. However, whether to treat HCV patients before vs after LT is not clear because treatment can improve liver function but could reduce the chance of receiving an LT while on the waiting list. Our objective was to evaluate the cost effectiveness of pre-LT vs post-LT HCV treatment with oral DAAs in decompensated cirrhotic patients on the LT waiting list. METHODS: We used a validated mathematical model that simulated a virtual trial comparing long-term clinical and cost outcomes of pre-LT vs post-LT HCV treatment with oral DAAs. Model parameters were estimated from United Network for Organ Sharing data, SOLAR-1 and 2 trials, and published studies. For each strategy, we estimated the quality-adjusted life-year, life expectancy, cost, and the incremental cost-effectiveness ratio. RESULTS: For lower MELD scores, quality-adjusted life-years were higher with pre-LT HCV treatment compared with post-LT treatment. Pre-LT HCV treatment was cost saving in patients with MELD scores of 15 or less, and cost effective in patients with MELD scores of 16 to 21. In contrast, post-LT HCV treatment was cost effective in patients with MELD scores of 22 to 29 and cost saving if MELD scores were 30 or higher. Results varied by drug prices and by United Network for Organ Sharing regions. CONCLUSIONS: For cirrhotic patients awaiting LT, pre-LT HCV treatment with DAAs is cost effective/saving in patients with MELD scores of 21 or lower, whereas post-LT HCV treatment is cost effective/saving in patients with MELD scores of 22 or higher.

Exploring the potential cost-effectiveness of precision medicine treatment strategies for diffuse large B-cell lymphoma.

Activated B-cell-like (ABC) diffuse large B-cell lymphoma (DLBCL) is associated with worse survival after standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (RCHOP) chemoimmunotherapy compared to germinal center B-cell-like (GCB) subtype. Preliminary evidence suggests that benefits from novel agents may vary by subtype. Hypothesizing that treatment stratified by DLBCL subtype could be potentially cost-effective, we developed micro-simulation models to compare three first-line treatment strategies: (1) standard RCHOP for all patients (2) subtype testing followed by RCHOP for GCB and novel treatment for ABC DLBCL, and (3) novel treatment for all patients. Based on phase 2 evidence, we used lenalidomide + RCHOP as a surrogate novel treatment. The subtype-based approach showed a favorable incremental cost-effectiveness ratio of $15,015/quality-adjusted life year compared with RCHOP. Although our exploratory analyses demonstrated a wide range of conditions where subtype-based treatment remained cost-effective, data from phase 3 trials are needed to validate our models' findings and draw definitive conclusions.

Age-based differences in the predictive accuracy of a one-size-fits-all risk-cutoff value in prenatal integrated screening for Down syndrome.

OBJECTIVE: The objective of this study is to assess variation in detection and false positive rates and adverse pregnancy outcomes across different age groups when a one-size-fits-all risk-cutoff value, such as 1/270, is used in integrated screening for Down syndrome. METHOD: A Monte Carlo simulation was utilized to estimate the detection and false positive rates as well as adverse pregnancy outcomes. RESULTS: Using a one-size-fits-all risk-cutoff value, such as 1/270, can result in considerably high variations in detection and false positive rates across maternal ages and lead to a higher than the minimum possible total number of adverse outcomes. CONCLUSION: Our findings indicate that the one-size-fits-all risk-cutoff value of 1/270, commonly used in DS screening, should be revisited and alternative (possibly age-based) cutoff values and strategies should be considered. © 2017 John Wiley & Sons, Ltd.

Bevacizumab for Metastatic Colorectal Cancer: A Global Cost-Effectiveness Analysis.

BACKGROUND: In the U.S., the addition of bevacizumab to first-line chemotherapy in metastatic colorectal cancer (mCRC) has been demonstrated to provide 0.10 quality-adjusted life years (QALYs) at an incremental cost-effectiveness ratio (ICER) of $571,000/QALY. Due to variability in pricing, value for money may be different in other countries. Our objective was to establish the cost-effectiveness of bevacizumab in mCRC in the U.S., U.K., Canada, Australia, and Israel. METHODS: We performed the analysis using a previously established Markov model for mCRC. Input data for efficacy, adverse events, and quality of life were considered to be generalizable and therefore identical for all countries. We used country-specific prices for medications, administration, and other health service costs. All costs were converted from local currency to U.S. dollars at the exchange rates in March 2016. We conducted one-way and probabilistic sensitivity analyses (PSA) to assess the model robustness across parameter uncertainties. RESULTS: Base case results demonstrated that the highest ICER was in the U.S. ($571,000/QALY) and the lowest was in Australia ($277,000/QALY). In Canada, the U.K., and Israel, ICERs ranged between $351,000 and $358,000 per QALY. PSA demonstrated 0% likelihood of bevacizumab being cost-effective in any country at a willingness to pay threshold of $150,000 per QALY. CONCLUSION: The addition of bevacizumab to first-line chemotherapy for mCRC consistently fails to be cost-effective in all five countries. There are large differences in cost-effectiveness between countries. This study provides a framework for analyzing the value of a cancer drug from the perspectives of multiple international payers. IMPLICATIONS FOR PRACTICE: The cost-effectiveness of bevacizumab varies significantly between multiple countries. By conventional thresholds, bevacizumab is not cost-effective in metastatic colon cancer in the U.S., the U.K., Australia, Canada, and Israel.

Cost-effectiveness of hepatitis C treatment using generic direct-acting antivirals available in India.

BACKGROUND & AIMS: Availability of directly-acting antivirals (DAAs) has changed the treatment landscape of hepatitis C virus (HCV) infection. The high price of DAAs has restricted their use in several countries. However, in some countries such as India, generic DAAs are available at much cheaper price. This study examined whether generic DAAs could be cost-saving and how long it would take for the treatment to become cost-saving/effective. METHODS: A previously-validated, mathematical model was adapted to the HCV-infected population in India to compare the outcomes of no treatment versus treatment with DAAs. Model parameters were estimated from published studies. Cost-effectiveness of HCV treatment using available DAAs was calculated, using a payer's perspective. We estimated quality-adjusted life years (QALYs), disability-adjusted life years (DALYs), total costs, and incremental cost-effectiveness ratio of DAAs versus no treatment. One-way and probabilistic sensitivity analyses were conducted. RESULTS: Compared with no treatment, the use of generic DAAs in Indian HCV patients would increase the life expectancy by 8.02 years, increase QALYs by 3.89, avert 19.07 DALYs, and reduce the lifetime healthcare costs by $1,309 per-person treated. Treatment became cost-effective within 2 years, and cost-saving within 10 years of its initiation overall and within 5 years in persons with cirrhosis. Treating 10,000 HCV-infected persons could prevent 3400-3850 decompensated cirrhosis, 1800-2500 HCC, and 4000-4550 liver-related deaths. The results were sensitive to the costs of DAAs, pre- and post-treatment diagnostic tests and management of cirrhosis, and quality of life after sustained virologic response. CONCLUSIONS: Treatment with generic DAAs available in India will improve patient outcomes, provide a good value for money within 2 years, and be ultimately cost-saving. Therefore, in this and similar settings, HCV treatment should be a priority from a public health as well an economic perspective.

From Data to Improved Decisions: Operations Research in Healthcare Delivery.

BACKGROUND: The Operations Research Interest Group (ORIG) within the Society of Medical Decision Making (SMDM) is a multidisciplinary interest group of professionals that specializes in taking an analytical approach to medical decision making and healthcare delivery. ORIG is interested in leveraging mathematical methods associated with the field of Operations Research (OR) to obtain data-driven solutions to complex healthcare problems and encourage collaborations across disciplines. This paper introduces OR for the non-expert and draws attention to opportunities where OR can be utilized to facilitate solutions to healthcare problems. METHODS: Decision making is the process of choosing between possible solutions to a problem with respect to certain metrics. OR concepts can help systematically improve decision making through efficient modeling techniques while accounting for relevant constraints. Depending on the problem, methods that are part of OR (e.g., linear programming, Markov Decision Processes) or methods that are derived from related fields (e.g., regression from statistics) can be incorporated into the solution approach. This paper highlights the characteristics of different OR methods that have been applied to healthcare decision making and provides examples of emerging research opportunities. EXAMPLES: We illustrate OR applications in healthcare using previous studies, including diagnosis and treatment of diseases, organ transplants, and patient flow decisions. Further, we provide a selection of emerging areas for utilizing OR. CONCLUSIONS: There is a timely need to inform practitioners and policy makers of the benefits of using OR techniques in solving healthcare problems. OR methods can support the development of sustainable long-term solutions across disease management, service delivery, and health policies by optimizing the performance of system elements and analyzing their interaction while considering relevant constraints.