Gene Therapy Versus Common Care for Eligible Individuals With Sickle Cell Disease in the United States : A Cost-Effectiveness Analysis.

BACKGROUND: Sickle cell disease (SCD) and its complications contribute to high rates of morbidity and early mortality and high cost in the United States and African heritage community. OBJECTIVE: To evaluate the cost-effectiveness of gene therapy for SCD and its value-based prices (VBPs). DESIGN: Comparative modeling analysis across 2 independently developed simulation models (University of Washington Model for Economic Analysis of Sickle Cell Cure [UW-MEASURE] and Fred Hutchinson Institute Sickle Cell Disease Outcomes Research and Economics Model [FH-HISCORE]) using the same databases. DATA SOURCES: Centers for Medicare & Medicaid Services claims data, 2008 to 2016; published literature. TARGET POPULATION: Persons eligible for gene therapy. TIME HORIZON: Lifetime. PERSPECTIVE: U.S. health care sector and societal. INTERVENTION: Gene therapy versus common care. OUTCOME MEASURES: Incremental cost-effectiveness ratios (ICERs), equity-informed VBPs, and price acceptability curves. RESULTS OF BASE-CASE ANALYSIS: At an assumed $2 million price for gene therapy, UW-MEASURE and FH-HISCORE estimated ICERs of $193 000 per QALY and $427 000 per QALY, respectively, under the health care sector perspective. Corresponding estimates from the societal perspective were $126 000 per QALY and $281 000 per QALY. The difference in results between models stemmed primarily from considering a slightly different target population and incorporating the quality-of-life (QOL) effects of splenic sequestration, priapism, and acute chest syndrome in the UW model. From a societal perspective, acceptable (>90% confidence) VBPs ranged from $1 million to $2.5 million depending on the use of alternative effective metrics or equity-informed threshold values. RESULTS OF SENSITIVITY ANALYSIS: Results were sensitive to the costs of myeloablative conditioning before gene therapy, effect on caregiver QOL, and effect of gene therapy on long-term survival. LIMITATION: The short-term effects of gene therapy on vaso-occlusive events were extrapolated from 1 study. CONCLUSION: Gene therapy for SCD below a $2 million price tag is likely to be cost-effective when applying a societal perspective at an equity-informed threshold for cost-effectiveness analysis. PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute.

Healthcare resource utilization and costs for patients with postoperative atrial fibrillation in the United States.

BACKGROUND: Postoperative atrial fibrillation (POAF) is one of the most common complications following cardiac surgery. POAF is associated with increased hospitalization costs, but its long-term economic burden is not well defined. OBJECTIVE: To assess 30-day and 1-year incremental healthcare resource utilization (HRU) and costs associated with POAF in the United States (US). METHODS: This retrospective cohort study used claims data from the IBM Watson MarketScan database. A cohort of US adults aged 55--90 years who underwent open-heart surgery between 1 January 2017 and 31 December 2018 was used to compare patients who experienced POAF versus patients who did not (controls). The outcomes of interest were incremental HRU and costs, which were assessed during the index hospitalization and 30-day and 1-year postdischarge time periods. Inverse probability weighting was used to adjust for differences in baseline characteristics. RESULTS: A total of 8,020 patients met the study inclusion criteria with 5,765 patients in the control cohort (mean age, 63.4 years) and 2,255 patients in the POAF cohort (mean age, 65.8 years). After adjustment, patients with POAF had an index hospitalization that was 1.9 days longer (99% CI, 1.3-2.4 days; p < 0.001) and cost $13,919 more (99% CI, $2,828-$25,011; p < 0.001) than for patients without POAF. POAF patients also had significantly higher HRU at 30 days and 1-year postdischarge with incremental costs of $4,649 (99% CI, $1,479-$7,819; p < 0.001) and $10,671 (99% CI, $2,407-$18,935; p < 0.001), respectively. CONCLUSION: POAF following open-heart surgery poses a significant economic burden up to 1 year postdischarge.

Comparing Patient and Provider Priorities Around Amputation Level Outcomes Using Multiple Criteria Decision Analysis.

BACKGROUND: Patients with chronic limb threatening ischemia may require a transmetatarsal amputation (TMA) or a transtibial amputation. When making an amputation-level decision, these patients face a tradeoff-a TMA preserves more limb and may provide better mobility but has a lower probability of primary wound healing and may therefore result in additional same or higher level amputation surgeries with an associated negative impact on function. Understanding differences in how patients and providers prioritize these tradeoffs and other outcomes may enhance shared decision-making. OBJECTIVES: Compare patient priorities with provider perceptions of patient priorities using Multiple Criteria Decision Analysis (MCDA). METHODS: The MCDA Analytic Hierarchy Process was chosen due to its low cognitive burden and ease of implementation. We included 5 criteria (outcomes): ability to walk, healing after amputation surgery, rehabilitation program intensity, limb length, and ease of use of prosthetic/orthotic device. A national sample of dysvascular lower-limb amputees and providers were recruited from the Veterans Health Administration with the MCDA administered online to providers and telephonically to patients. RESULTS: Twenty-six dysvascular amputees and 38 providers participated. Fifty percent of patients had undergone a TMA; 50%, a transtibial amputation. When compared to providers, patients placed higher value on TMA (72% vs. 63%). Patient versus provider priorities were ability to walk (47% vs. 42%), healing (18% vs. 28%), ease of prosthesis use (17% vs. 13%), limb length (11% vs. 13%), and then rehabilitation intensity (7% vs. 6%). LIMITATIONS: Our sample may not generalize to other populations. CONCLUSIONS: Provider perceptions aligned with patient values on amputation level but varied around the importance of each outcome. IMPLICATIONS: These findings illuminate some differences between patients' values and provider perceptions of patient values, suggesting a role for shared decision-making. Embedding this MCDA framework into a future decision aid may facilitate these discussions.

Long-term survival with sickle cell disease: a nationwide cohort study of Medicare and Medicaid beneficiaries.

To our knowledge, we report the first population-based period life table, the expected lifetime survival for Medicare and Medicaid beneficiaries with sickle cell disease (SCD), and the disparities in survival by insurance types in the United States. We constructed a retrospective cohort of individuals with diagnosed SCD receiving common care (any real-world patterns of care except transplant) based on nationwide Medicare and Medicaid claim data (2008-2016), covering beneficiaries in all 50 states. We analyzed lifetime survival probabilities using Kaplan-Meier curves and projected life expectancies at various ages for all, stratified by sex and insurance types. Our analysis included 94 616 individuals with SCD that have not undergone any transplant. Life expectancy at birth was 52.6 years (95% confidence interval: 51.9-53.4). Compared with the adults covered by Medicaid only, those covered by Medicare for disabilities or end-stage renal disease and those dually insured by Medicare and Medicaid had significantly worse life expectancy. Similarly, for beneficiaries aged ≥65 years, these 2 insurance types were associated with significantly shorter life expectancy than those enrolled in Medicare old age and survivor's insurance. Our study underscores the persistent life expectancy shortfall for patients with SCD, the burden of premature mortality during adulthood, and survival disparities by insurance status.

Lifetime medical costs attributable to sickle cell disease among nonelderly individuals with commercial insurance.

Sickle cell disease (SCD) is a severe monogenic disease associated with high morbidity, mortality, and a disproportionate burden on Black and Hispanic communities. Our objective was to estimate the total healthcare costs and out-of-pocket (OOP) costs attributable to SCD among commercially insured individuals over their nonelderly lifetimes (0 to 64 years of age). We constructed a retrospective cohort of individuals with diagnosed SCD using Truven Health Marketscan commercial claims data from 2007 through 2018, compared with matched control subjects from the Medical Expenditure Panel Survey. We estimated Kaplan-Meier sample average costs using previously reported survival curves for SCD and control subjects. Individuals with SCD (20 891) and control subjects (33 588) were included in our analysis. The SCD sample had a mean age of 25.7 (standard deviation, 17.4) years; 58.0% were female. Survival-adjusted costs of SCD peaked at age 13 to 24 years and declined at older ages. There was no significant difference in total medical costs or OOP costs between the sexes. SCD-attributable costs over 0 to 64 years of age were estimated to be $1.6 million (95% confidence interval [CI], $1.3M-$1.9M) and $1.7 million (95% CI, $1.4M-$2.1M) for females and males with SCD, respectively. The corresponding OOP estimates were $42 395 (95% CI, $34 756-$50 033) for females and $45 091 (95% CI, $36 491-$53 691) for males. These represent a 907% and 285% increase in total medical and OOP costs over control subjects, respectively. Although limited to the commercially insured population, these results indicate that the direct economic burden of SCD is substantial and peaks at younger ages, suggesting the need for curative and new medical therapies.

A Scoping Review of the Use of Machine Learning in Health Economics and Outcomes Research: Part 1-Data From Wearable Devices.

OBJECTIVES: With the emerging use of machine learning (ML) techniques, there has been particular interest in using wearable data for health economics and outcomes research (HEOR). We aimed to understand the emerging patterns of how ML has been applied to wearable data in HEOR. METHODS: We identified studies published in PubMed between January 2016 and March 2021. Studies that included at least 1 HEOR-related Medical Subject Headings term, applied an ML, and used wearable data were eligible for inclusion. Two reviewers abstracted information including ML application types and data on which ML was applied and analyzed them using descriptive analyses. RESULTS: A total of 148 studies were identified from PubMed, among which 32 studies met the inclusion criteria. There has been an increase over time in the number of ML studies using wearable data. ML has been more frequently used for monitoring events in real time (78%) than to predict future events (22%). There has been a wide range of outcomes examined, ranging from general physical or mental health (24%) to more disease-specific outcomes (eg, disease incidence [19%] and progression [13%]) and treatment-related outcomes (eg, treatment adherence [9%] and outcomes [9%]). Data for ML models were more often derived from wearable devices with specific medical purposes (60%) than those without (40%). CONCLUSION: There has been a wide range of applications of ML to wearable data. Both medical and nonmedical wearable devices have been used as a data source, showing the potential for providing rich data for ML studies in HEOR.

The Development and Pilot Study of a Multiple Criteria Decision Analysis (MCDA) to Compare Patient and Provider Priorities around Amputation-Level Outcomes.

Background. Patients with chronic limb-threatening ischemia who are facing a lower-limb amputation often require a transmetatarsal amputation (TMA) or a transtibial amputation (TTA). A TMA preserves more of the patient's limb and may provide better mobility but has a lower probability of primary wound healing relative to a TTA and may result in additional amputation surgeries. Understanding the differences in how patients and providers prioritize key outcomes may enhance the amputation decisional process. Purpose. To develop and pilot test a multiple criteria decision analysis (MCDA) tool to elicit patient values around amputation-level selection and compare those with provider perceptions of patient values. Methods. We conducted literature reviews to identify and measure the performance of criteria important to patients. Because the quantitative literature was sparse, we developed a Sheffield elicitation framework exercise to elicit criteria performance from subject matter experts. We piloted our MCDA among patients and providers to understand tool acceptability and preliminarily assess differences in patient and provider priorities. Results. Five criteria of importance were identified: ability to walk, healing after amputation surgery, rehabilitation intensity, limb length, and prosthetic/orthotic device ease. Patients and providers successfully completed the MCDA and identified challenges in doing so. We propose potential solutions to these challenges. The results of the pilot test suggest differences in patient and provider outcome priorities. Limitations. The pilot test study enrolled a small sample of providers and patients. Conclusions. We successfully implemented the pilot study to patients and providers, received helpful feedback, and identified solutions to improve the tool. Implications. Once modified, our MCDA tool will be suitable for wider rollout. Highlights: Patients and providers have successfully completed our MCDA, and patients feel the MCDA may be useful in clinical practice.We encountered several methodologic challenges and identified approaches to ease participant burden.When data are sparse, using the Sheffield elicitation framework is helpful in creating a performance matrix, although patients relied largely on their amputation experiences to complete the exercise. Blinding the alternatives may help patients better understand the process.

Prevalence of comorbidities associated with sickle cell disease among non-elderly individuals with commercial insurance-A retrospective cohort study.

Sickle cell disease (SCD) is a severe monogenic disease associated with high morbidity and mortality and a disproportionate burden on Black communities. Few population-based studies have examined the prevalence of comorbidities among persons with SCD. We estimated the prevalence of comorbidities experienced by individuals with SCD enrolled in employer-based health insurance plans in the US over their non-elderly lifetimes (0-64 years of age) with a retrospective cohort design using Truven Health MarketScan commercial claims data from 2007-2018. ICD-9/10 codes were used to identify individuals with SCD using a previously published algorithm. For this cohort, comorbidities associated with SCD were identified across 3 age categories (<18, 18-45, 46-64 years-old), based on the CMS Chronic Comorbidities Warehouse or SCD-specific diagnosis codes, when applicable. The total number of SCD patients available for analysis in each age category was 7,502 (<18 years), 10,183 (18-45 years) and 4,459 (46-64 years). Across all ages, vaso-occlusive pain, infections (non-specific), and fever were the most common comorbidities. Vaso-occlusive pain and infection were the most prevalent conditions for persons age <18- and 18-45-year-olds, while in the 46-54-year-old age group, infection and cardiovascular including pulmonary hypertension were most prevalent. Compared to persons <18 years old, the prevalence of vaso-occlusive pain, fever, and acute chest syndrome claims declined in older populations. The comorbidity burden of SCD is significant across all age groups. SCD patients experience comorbidities of age such as chronic pain, cardio-vascular conditions including pulmonary hypertension and renal disease at far higher rates than the general population. Novel disease modifying therapies in development have the potential to significantly reduce the comorbidity burden of SCD.

A Scoping Review of the Use of Machine Learning in Health Economics and Outcomes Research: Part 2-Data From Nonwearables.

OBJECTIVES: Despite the increasing interest in applying machine learning (ML) methods in health economics and outcomes research (HEOR), stakeholders face uncertainties in when and how ML can be used. We reviewed the recent applications of ML in HEOR. METHODS: We searched PubMed for studies published between January 2020 and March 2021 and randomly chose 20% of the identified studies for the sake of manageability. Studies that were in HEOR and applied an ML technique were included. Studies related to wearable devices were excluded. We abstracted information on the ML applications, data types, and ML methods and analyzed it using descriptive statistics. RESULTS: We retrieved 805 articles, of which 161 (20%) were randomly chosen. Ninety-two of the random sample met the eligibility criteria. We found that ML was primarily used for predicting future events (86%) rather than current events (14%). The most common response variables were clinical events or disease incidence (42%) and treatment outcomes (22%). ML was less used to predict economic outcomes such as health resource utilization (16%) or costs (3%). Although electronic medical records (35%) were frequently used for model development, claims data were used less frequently (9%). Tree-based methods (eg, random forests and boosting) were the most commonly used ML methods (31%). CONCLUSIONS: The use of ML techniques in HEOR is growing rapidly, but there remain opportunities to apply them to predict economic outcomes, especially using claims databases, which could inform the development of cost-effectiveness models.

Use of geriatric assessment in cancer clinical trials: A systematic review.

BACKGROUND: Older adults are underrepresented in cancer clinical trials despite accounting for most of the disease burden. Geriatric assessment (GA) could be used in clinical trials of cancer drugs for older adults to improve the clinical evidence for cancer drug use among older adults. OBJECTIVE: To examine patterns of use of GA in cancer clinical trials. METHODS: We undertook a systematic review of the studies reporting use of GA in a clinical trial setting for all cancer types and published between January 2010 and January 2020. Characteristics of GA use were extracted for each study, along with study phase, cancer type, and participant age (PROSPERO: CRD42020170584). RESULTS: We identified 320 studies and 63 studies met the final inclusion criteria. Among 74 purposes of GA use, the most common was to examine the association between impairments in GA domains and clinical outcomes (28/74, 38%). Among 258 GA domains assessed across 63 studies, physical status (59/258, 23%) and comorbidities (50/258, 19%) were most often evaluated. There was significant heterogeneity in the instruments used to assess physical function (n = 16) and mood disorders (n = 7). Most studies were phase 2 (32/63, 51%). CONCLUSIONS: GA is most often used in clinical trial settings to examine associations between GA-identified deficits and clinical outcomes. Significant heterogeneity exists in the GA instruments used across trials. Comprehensive and consistent incorporation of GA into future cancer clinical trial designs could help collect more older adult-specific clinical information and adjust trial eligibility criteria to increase representation by older adults.

Development of a conceptual model for evaluating new non-curative and curative therapies for sickle cell disease.

BACKGROUND: Sickle cell disease (SCD) is a clinically heterogeneous disease with many acute and chronic complications driven by ongoing vaso-occlusion and hemolysis. It causes a disproportionate burden on Black and Hispanic communities. Our objective was to follow the SMDM/ISPOR Task Force recommendations for good practices and create a conceptual model of the progression of SCD under current clinical practice to inform cost-effectiveness analyses (CEA) of promising curative therapies in the pipeline over a lifetime horizon. METHODS: We used consultations with experts, providers, and patients to identify acute events and chronic conditions in the conceptual model. We compared our model structure to previous CEA models of interventions for SCD, assessed the prevalence of the identified disease attributes in Medicaid and Medicare claims databases, and identified relevant outcomes following the 2nd Panel in CEA. We determined an appropriate modeling technique and relevant data sources for parameterizing the model. RESULTS: The conceptual model structure included four dimensions of disease: chronic pain, acute events, chronic conditions, and treatment complications, spanning 26 disease attributes with significant impacts on health-related quality of life and resource. We modeled chronic pain separately to reflect its importance to patients and interaction with all other disease attributes. We identified additional data sources for health state utilities and non-medical costs and benefits of SCD. We will use a microsimulation model with age- and sex-specific transitions between health states predicted by patient demographic characteristics and disease history. CONCLUSION: Developing the model structure through an explicit process of model conceptualization can increase the transparency and accuracy of results. We will populate the conceptual model with the data sources described and evaluate the cost-effectiveness of curative therapies.

Medical and Non-medical Costs of Sickle Cell Disease and Treatments from a US Perspective: A Systematic Review and Landscape Analysis.

BACKGROUND: Sickle cell disease (SCD) is a complex genetic disorder that manifests in infancy and progresses throughout life in the form of acute and chronic complications. As the upfront costs of potentially curative, genetic therapies will likely be high, an assessment and comprehensive characterization of the medical and non-medical cost burden will inform future decision making. OBJECTIVE: We sought to systematically summarize the existing literature surrounding SCD medical and non-medical costs. METHODS: We searched MEDLINE and EMBASE (2008-2020) and identified US-based studies that detailed medical or non-medical costs. Eligible studies provided empirical estimates about any aspect of cost or SCD individuals of all ages and their caregivers. Study quality was assessed using the Newcastle-Ottawa Scale, and costs were adjusted to 2019 US$. RESULTS: Search queries returned 479 studies, with 342 from medical burden searches and 137 from non-medical burden searches, respectively. Herein, we report the results of the 40 studies that contained relevant cost information: 39 detailed medical costs and 1 detailed non-medical costs. Costs were higher for SCD patients when compared with non-SCD individuals (cost difference range: $6636-$63,436 annually). The highest medical cost component for SCD patients was inpatient ($11,978-$59,851 annually), followed by outpatient and then pharmacy. No studies characterized the cost burden throughout the lifetime disease trajectory of an SCD individual, and no studies captured caregiver or productivity costs. CONCLUSION: Our results reveal an incomplete characterization of medical and non-medical costs within SCD. A deeper understanding of the medical and non-medical cost burden requires completion of additional studies that capture the burden across the patient's lifetime, in addition to expression of the impact of existing and emergent health technologies on disease trajectory.

A landscape analysis and discussion of value of gene therapies for sickle cell disease.

INTRODUCTION: Sickle cell disease (SCD) is a rare genetic disease with limited therapeutic options. Gene-based therapies are being investigated in clinical trials to evaluate their curative potential. The expected life-long benefits of one-time administration of genetically corrected stem cells present uncharted challenges in estimating value of these treatments. Our objective is to conduct a landscape analysis of clinical trials and prompt a discussion estimating the value of gene therapy as a therapeutic option for SCD. AREAS COVERED: We searched Clinicaltrials.gov to identify and characterize clinical trials in gene therapies for SCD. We report available results and discuss current concerns and elements of value necessary to consider as these products come to market. EXPERT OPINION: Gene therapies could represent a major advance in SCD treatment. Although clinical trials are ongoing, reports of serious adverse events have led to pause of these trials, emphasizing the need to prove long-term tolerability. Measured using the methods of health economic evaluation, we anticipate high up-front costs may be offset by potential life-long benefits of these treatments. During development and after treatment approval, attention should be focused on ensuring adequate availability and equitable access to emerging therapies in underserved areas and low-middle-income countries (LMIC).

Implementation of pharmacogenomic clinical decision support for health systems: a cost-utility analysis.

We constructed a cost-effectiveness model to assess the clinical and economic value of a CDS alert program that provides pharmacogenomic (PGx) testing results, compared to no alert program in acute coronary syndrome (ACS) and atrial fibrillation (AF), from a health system perspective. We defaulted that 20% of 500,000 health-system members between the ages of 55 and 65 received PGx testing for CYP2C19 (ACS-clopidogrel) and CYP2C9, CYP4F2 and VKORC1 (AF-warfarin) annually. Clinical events, costs, and quality-adjusted life years (QALYs) were calculated over 20 years with an annual discount rate of 3%. In total, 3169 alerts would be fired. The CDS alert program would help avoid 16 major clinical events and 6 deaths for ACS; and 2 clinical events and 0.9 deaths for AF. The incremental cost-effectiveness ratio was $39,477/QALY. A PGx-CDS alert program was cost-effective, under a willingness-to-pay threshold of $100,000/QALY gained, compared to no alert program.

Assessing Payers' Preferences for Real-World Evidence in the United States: A Discrete Choice Experiment.

OBJECTIVES: To rank the US payers' preferences for attributes of real-world evidence (RWE) studies in the context of chronic disease and to quantify trade-offs among them. METHODS: We conducted a discrete choice experiment in which 180 employees from payer organizations were tasked to choose between 2 RWE studies assuming they were assessing evidence to inform formulary decisions for chronic disease treatment. Each RWE study was characterized by 7 attributes with 3 levels each: very informative, moderately informative, and not measured. We used a D-optimal main-effects design. Survey data were fitted to a conditional logit model to obtain a relative measure of the ranking of importance for each attribute. RESULTS: Clinical outcomes were the most preferred attribute. It was 4.68 times as important as productivity outcomes-the least preferred attribute. It was followed by health-related quality of life (2.78), methodologic rigor (2.09), resource utilization (1.71), and external validity (1.56). CONCLUSIONS: This study provides a quantification of the value payers place on key RWE attributes. Across attributes, payers have higher preferences for clinical and health-related quality of life outcomes than the other attributes. Between attributes' levels, payers prefer high levels of information in clinical outcomes and methodologic rigor but are indifferent in other attributes. Our results bridge the gap between the information that payers seek and the attributes that RWE studies prioritize and effectively guide future research design.

Health State Utilities for Sickle Cell Disease: A Catalog Prepared From a Systematic Review.

OBJECTIVES: Sickle cell disease (SCD) is a complex, chronic condition that impairs health-related quality of life of affected individuals and their caregivers. As curative therapies emerge, comprehensive cost-effectiveness models will inform their value. These models will require descriptions of health states and their corresponding utility values that accurately reflect health-related quality of life over the disease trajectory. The objectives of this systematic review were to develop a catalog of health state utility (HSU) values for SCD, identify research gaps, and provide future directions for preference elicitation. METHODS: Records were identified through searches of PubMed and Embase, Tufts Medical Center Cost-Effectiveness Analysis Registry, reference lists of relevant articles, and consultation with SCD experts (2008-2020). We removed duplicate records and excluded ineligible studies. For included studies, we summarized the study characteristics, methods used for eliciting HSUs, and HSU values. RESULTS: Five studies empirically elicited utilities using indirect methods (EQ-5D) (n = 3) and Short Form-6 Dimension (n = 2); these represent health states associated with general SCD (n = 1), SCD complications (n = 2), and SCD treatments (n = 3). Additionally, we extracted HSUs from 7 quality-adjusted life-years-based outcome research studies. The HSU among patients with general SCD without specifying complications ranged from 0.64 to 0.887. Only 36% of the HSUs used in the quality-adjusted life-year-based outcomes research studies were derived from individuals with SCD. No study estimated HSUs in caregivers. CONCLUSIONS: There is a dearth of literature of HSUs for use in SCD models. Future empirical studies should elicit a comprehensive set of HSUs from individuals with SCD and their caregivers.

Spillover Effects of Mental Health Disorders on Family Members' Health-Related Quality of Life: Evidence from a US Sample.

OBJECTIVES: This study aims to characterize the spillover effects of selected mental health disorders (episodic mood disorder (EMD), anxiety, substance use disorder (SUD), schizophrenia, attention-deficit/hyperactivity disorder (ADHD), and dementia) on family members' health-related quality of life and to compare the magnitude of spillover effects across these types. METHODS: Using the 2000-2015 Medical Expenditure Panel Survey, households having individuals with mental health disorders were identified. The SF-12 and EQ-5D surveys were used to acquire utility and health status scores for household members. The outcomes in households including an individual with a mental health disorder were compared to those of the control group (absence of individuals with mental health disorders in the household). We also compared a total of 15 pairs of diseases based on the SF-6D scores. A beta generalized estimating equation model was employed. RESULTS: Average scores of utility and health status among individuals living with a member with a mental health disorder in the household were statistically lower than those of the control group and; for the SF-6D, met the minimally important difference for SUD, schizophrenia, and dementia. Differences in the SF-6D scores were statistically significant for 5 pairs of the mental health disorders: EMD-anxiety, EMD-ADHD, dementia-anxiety, dementia-ADHD, and schizophrenia-ADHD. CONCLUSIONS: This study provides evidence of family spillover effects in mental illness using both utility and health status measures from a US representative sample. Integrating this evidence into clinical and policy decision making as well as economic evaluations would allow for a more comprehensive valuation of the societal benefits of mental and behavioral health interventions.

US private payers' perspectives on insurance coverage for genome sequencing versus exome sequencing: A study by the Clinical Sequencing Evidence-Generating Research Consortium (CSER).

PURPOSE: There is limited payer coverage for genome sequencing (GS) relative to exome sequencing (ES) in the U.S. Our objective was to assess payers' considerations for coverage of GS versus coverage of ES and requirements payers have for coverage of GS. The study was conducted by the NIH-funded Clinical Sequencing Evidence-Generating Research Consortium (CSER). METHODS: We conducted semi-structured interviews with representatives of private payer organizations (payers, N = 12) on considerations and evidentiary and other needs for coverage of GS and ES. Data were analyzed using thematic analysis. RESULTS: We described four categories of findings and solutions: demonstrated merits of GS versus ES, enhanced methods for evidence generation, consistent laboratory processes/sequencing methods, and enhanced implementation/care delivery. Payers see advantages to GS vs. ES and are open to broader GS coverage but need more proof of these advantages to consider them in coverage decision-making. Next steps include establishing evidence of benefits in specific clinical scenarios, developing quality standards, ensuring transparency of laboratory methods, developing clinical centers of excellence, and incorporating the role of genetic professionals. CONCLUSION: By comparing coverage considerations for GS and ES, we identified a path forward for coverage of GS. Future research should explicitly address payers' conditions for coverage.

The Use of Cost-Effectiveness Analysis in Sickle Cell Disease: A Critical Review of the Literature.

Novel interventions for sickle cell disease (SCD) bring hope to patients, yet concern about the associated economic costs exists. Cost-effectiveness analysis (CEA) uses standardized methods, with robust underpinnings in health economics, to estimate the value of these interventions compared with usual care. However, because of the complexity and lifetime trajectory of SCD, CEAs are challenging to conduct. The objectives of this rapid review were to summarize the main characteristics, components, and results of published CEAs of existing interventions for SCD, identify research gaps, and provide directions for future analyses. We identified records through searches of bibliographic databases, from reference lists of relevant review articles, and through consultation with experts. A total of 13 CEAs met our inclusion criteria and were qualitatively synthesized. These evaluated blood transfusions (n = 2), hematopoietic stem cell transplantation (n = 1), pharmaceuticals (n = 2), hypothetical cell or genetic therapy (n = 1), screening programs (n = 4), and interventions for SCD treatment complications (n = 3). A limited number of potential SCD and treatment complications were evaluated. No study adopted a societal perspective in the base case, six studies examined lifetime cost-effectiveness, seven studies employed a Markov or discrete-event simulation model, and eight studies used an outcome metric that captured both quality and length of life. To better compare the value of emerging and current therapies, future CEAs should adopt a societal perspective incorporating both medical and nonmedical costs, comprehensively model SCD complexity using robust health economic simulation models over the patient's entire lifespan, and capture the intervention's effect on both survival and quality of life.

Healthcare Resource Utilization and Costs in Patients with Geographic Atrophy Secondary to Age-Related Macular Degeneration.

PURPOSE: Geographic atrophy (GA) is an advanced form of nonexudative age-related macular degeneration (AMD) that lacks treatment options. With considerable interpatient variability in the rate of GA progression due to lesion characteristics, information characterizing the disease burden is limited. The aim of this study was to describe the healthcare resource utilization (HCRU) and costs associated with increasing severity levels of GA. PATIENTS AND METHODS: A retrospective analysis was conducted using claims data from IQVIA's PharMetrics Plus database. Patients with a prevalent GA diagnosis were identified between October 1, 2016 and June 30, 2017 and classified by disease severity and laterality. Disease-specific HCRU and costs by disease severity were assessed during the 12-month follow-up period, with multivariable analyses performed adjusting for baseline characteristics. RESULTS: A total of 28,773 GA cases were identified (mean age = 68.7; 58.5% female), of which 24% and 76% had unilateral and bilateral GA, respectively, with varying levels of recorded severity (in increasing order): early or intermediate (EI) AMD, GA without subfoveal involvement (GAwoSF), and GA with subfoveal involvement (GAwSF). Patients with greater baseline severity in the bilateral group had a significantly higher number of outpatient (OP) visits per year (1.98 EI AMD; 2.57 for GAwoSF; 2.63 for GAwSF). Increasing disease severity was associated with higher patient-related costs in the outpatient setting (mean [SD] of $82 [$157], $110 [$559] for unilateral EI AMD and GAwSF, respectively, and $56 [$94], $64 [$97], $59 [$85] for bilateral EI AMD, GAwoSF, GAwSF, respectively). Similarly, higher payer-related costs were seen in patients with bilateral GAwSF compared to bilateral EI AMD (mean [SD] $280 [$325]; $198 [$262]). CONCLUSION: Study findings demonstrate that patients, with more severe GA at baseline, experience greater HCRU and costs in the outpatient setting. Further research should explore specific contributing factors to the long-term economic burden of GA.