A survey on awareness, knowledge and preferences toward genetic testing among the United States general public.

Aim: To understand awareness, knowledge and preferences regarding genetic testing among the USA general public. Methods: A cross-sectional online survey using a Qualtrics Panel. Results: Among 1600 respondents, 545 (34%) were White, 411 (26%) Black, 412 (26%) Hispanic or Latin(x) and 232 (15%) Asian. Most had heard of ancestry testing (87%) and genetic health risk testing (69%), but a third thought inherited genes were only a little or not at all responsible for obesity (36%) and mental health (33%). The majority preferred pre-emptive pharmacogenetic testing (n = 74%) compared with reactive testing. Statistically significant differences between racial/ethnic groups and rural-urban respondents were observed. Conclusion: Most preferred pre-emptive pharmacogenetic testing; however, about one-quarter preferred reactive testing. Preferences should be discussed during patient-clinician interactions.

What is this study about? This study presents a large online survey among the USA general public to understand their awareness, knowledge and preferences about genetic testing and how this may vary by racial/ethnic group and rural/urban status. What were the results? Most survey respondents had heard of ancestry testing (87%) and genetic health risk testing (69%). However, over a third of respondents thought that inherited genes may be only a little or not at all responsible for obesity (36%) and mental health (33%). When asked about preferences for pre-emptive compared with reactive pharmacogenetic testing, the majority preferred pre-emptive testing (n = 74%). Statistically significant differences between racial/ethnic groups as well as rural-urban respondents were seen. What do the results mean? The US general public may have a different understanding of genetic testing for different diseases, and have different preferences when it comes to the timing of testing. Appropriate educational content targeting the link between genetics and specific diseases should be prepared, and preferences for pre-emptive or reactive testing should be discussed during visits with healthcare providers.

Important Barriers to COVID-19 Vaccination Among African Americans in Black Belt Region.

BACKGROUND: To identify important barriers to COVID-19 vaccination among African Americans living in the Black Belt region. METHODS: A cross-sectional, web-based questionnaire survey was conducted using best-worst scaling case 1 (the object case). Thirty-two potential barriers to COVID-19 vaccination were identified from the literature and confirmed by an expert. A nested balanced incomplete block design was used to generate 62 sets of 16 choice tasks. Each choice task included six barriers. Participants were asked to choose the most and least important barriers to their COVID-19 vaccination in each choice task of one set. The natural logarithm of the square root of best counts divided by the worst counts of each barrier was calculated to rank the importance of barriers. RESULTS: Responses from a total of 808 participants were included. Among 32 barriers to COVID-19 vaccination, the five most important barriers were "safety concern of COVID-19 vaccines," "rapid mutation of COVID-19," "ingredients of COVID-19 vaccines," "Emergency Use Authorization (Fast-track approval) of COVID-19 vaccines," and "inconsistent information of COVID-19 vaccines." On the other hand, the five least important barriers were "religious reasons," "lack of time to get COVID-19 vaccine," "no support from my family and friends," "political reasons," and "fear of the needle." CONCLUSIONS: Important barriers to the COVID-19 vaccination for African Americans living in the Black Belt region centered around the issues that could be resolved by communication strategies.

Using a patient-centered value assessment to optimize fair prices for Inflation Reduction Act's Medicare Drug Price Negotiation Program.

In the United States, various federal agencies, institutions, and foundations, including the Centers for Medicare & Medicaid Services (CMS), have supported the incorporation of patient perspective in health care decision-making. Despite a series of patient-focused listening sessions planned as part of the Inflation Reduction Act's Medicare Drug Price Negotiation Program, the details of these sessions in the guidance developed by CMS remain unclear. CMS has not specified how patients' inputs will be used to determine the maximum fair prices (MFPs) of selected drugs for the first round of the negotiations. In this Viewpoint article, we urge CMS to use patient-centered value assessment methods to optimize MFPs in the Medicare Drug Price Negotiation Program. We focused on a stated preference method, the discrete choice experiment, which has been increasingly used to determine patient preferences and patient's willingness to pay for drugs. We discussed an example using a discrete choice experiment as a patient-centered method to assess the value of Jardiance and optimize its MFP in the negotiation program.

Service-level barriers to and facilitators of accessibility to treatment for problematic alcohol use: a scoping review.

Introduction: Services to treat problematic alcohol use (PAU) should be highly accessible to optimize treatment engagement. We conducted a scoping review to map characteristics of services for the treatment of PAU that have been reported in the literature to be barriers to or facilitators of access to treatment from the perspective of individuals with PAU. Methods: A protocol was developed a priori, registered, and published. We searched MEDLINE®, Embase, the Cochrane Library, and additional grey literature sources from 2010 to April 2022 to identify primary qualitative research and surveys of adults with current or past PAU requiring treatment that were designed to identify modifiable characteristics of PAU treatment services (including psychosocial and pharmacologic interventions) that were perceived to be barriers to or facilitators of access to treatment. Studies of concurrent PAU and other substance use disorders were excluded. Study selection was performed by multiple review team members. Emergent barriers were coded and mapped to the accessibility dimensions of the Levesque framework of healthcare access, then descriptively summarized. Results: One-hundred-and-nine included studies reported an extensive array of unique service-level barriers that could act alone or together to prevent treatment accessibility. These included but were not limited to lack of an obvious entry point, complexity of the care pathway, high financial cost, unacceptably long wait times, lack of geographically accessible treatment, inconvenient appointment hours, poor cultural/demographic sensitivity, lack of anonymity/privacy, lack of services to treat concurrent PAU and mental health problems. Discussion: Barriers generally aligned with recent reviews of the substance use disorder literature. Ranking of barriers may be explored in a future discrete choice experiment of PAU service users. The rich qualitative findings of this review may support the design of new or modification of existing services for people with PAU to improve accessibility. Systematic Review Registration: Open Science Framework doi: 10.17605/OSF.IO/S849R.

A Preference-Based Value Assessment of the Fear of COVID-19 Contagion.

Purpose: To assess the preference-based value of the fear of COVID-19 contagion. Patients and Methods: We conducted a web-based, cross-sectional discrete choice experiment among 544 US adults. We used a Bayesian efficient design to generate choice sets. Each choice set comprised two hypothetical COVID-19 vaccine options characterized by seven attributes: chance of COVID-19 infection, chance of having severe symptoms from COVID-19 infection, vaccine protection duration, chance of mild to moderate adverse events from vaccination, chance of serious adverse events from vaccination, chance of future exposure to COVID-19 after vaccination, and out-of-pocket cost. We used mixed logit (ML) and latent class (LC) models to analyze data. Furthermore, we calculated the willingness-to-pay for eliminating the chance of future exposure to COVID-19, shedding light on the value attributed to the fear of contagion. Results: The ML model demonstrated all attributes, including the chance of future exposure to COVID-19, were statistically significant. The participants were willing to pay approximately $13,046 to eliminate the chance of future exposure to COVID-19 or their fear of contagion when COVID-19 was still pandemic. The LC model unveiled two participant classes with distinct preference weights for the chance of future exposure to COVID-19 and out-of-pocket cost attributes. Nevertheless, the chance of future exposure to COVID-19 exposure held a significant degree of importance in both classes. Conclusion: The chance of future exposure to COVID-19 exposure or fear of contagion was a significant element in the value assessment of COVID-19 vaccines. Further studies should be conducted to verify the value of fear of contagion and include it in the value assessment of healthcare technologies for infectious diseases.

Using a discrete choice experiment to elicit patients' preferences and willingness-to-pay for knee osteoarthritis treatments in Thailand.

Osteoarthritis is the most common type of joint disease among elderly patients around the world. In response to the need for patient-centered care, patients' and physicians' preferences for knee osteoarthritis treatments have been studied in multiple countries, but not in Thailand. The objective of this study was to investigate Thai patients' preferences and their willingness to pay (WTP) for knee osteoarthritis treatments by using a discrete choice experiment (DCE). Six knee osteoarthritis treatment attributes, including pain relief, delayed disease progression, gastrointestinal side effects, kidney side effects, cardiovascular side effects, and cost, were used to develop a paper-based, DCE questionnaire survey. Patients with knee osteoarthritis, who were at least 18 years old and who provided written informed consent, were recruited from the orthopedic department in a tertiary care hospital in Thailand via convenience sampling. The conditional logit model was used to determine patients' preferences and WTP. The Institutional Review Board at Chulalongkorn University approved this study before it started. A total of 232 patients were collected and analyzed in this study. Patients preferred treatments with a higher efficacy (pain relief and delayed disease progression), a lower probability of side effects (gastrointestinal, kidney, and cardiovascular side effects), and a lower cost. Regarding efficacy and side effects, the patients weighted the importance of a 1% change in cardiovascular side effects (- 0.08) more heavily than 1% changes in kidney (- 0.07) and gastrointestinal (- 0.02) side effects, delayed disease progression (0.02), and pain relief (0.01). Patients were willing to pay 29.56 Thai Baht (THB) and 41.84 THB per month for every 1% increase in pain relief and delayed disease progression, respectively. Conversely, patients were willing to pay 52.04 THB, 145.18 THB and 164.23 THB per month for every 1% decrease in gastrointestinal, kidney, and cardiovascular side effects, respectively. In conclusion, pain relief, delayed disease progression, gastrointestinal side effects, kidney side effects, cardiovascular side effects, and the cost of treatment were significant factors among patients undergoing knee osteoarthritis treatment. Additionally, patients had a higher WTP for delayed disease progression than pain relief and a higher WTP for a reduced probability of cardiovascular side effects than gastrointestinal and kidney side effects. These findings could be used to support treatment decisions for knee osteoarthritis patients in Thailand.

Current published evidence on barriers and proposed strategies for genetic testing implementation in health care settings: A scoping review.

BACKGROUND: The slow uptake of genetic testing in routine clinical practice warrants the attention of researchers and practitioners to find effective strategies to facilitate implementation. OBJECTIVES: This study aimed to identify the barriers to and strategies for pharmacogenetic testing implementation in a health care setting from published literature. METHODS: A scoping review was conducted in August 2021 with an expanded literature search using Ovid MEDLINE, Web of Science, International Pharmaceutical Abstract, and Google Scholar to identify studies reporting implementation of pharmacogenetic testing in a health care setting, from a health care system's perspective. Articles were screened using DistillerSR and findings were organized using the 5 major domains of Consolidated Framework for Implementation Research (CFIR). RESULTS: A total of 3536 unique articles were retrieved from the above sources, with only 253 articles retained after title and abstract screening. Upon screening the full texts, 57 articles (representing 46 unique practice sites) were found matching the inclusion criteria. We found that most reported barriers and their associated strategies to the implementation of pharmacogenetic testing surrounded 2 CFIR domains: intervention characteristics and inner settings. Factors relating to cost and reimbursement were described as major barriers in the intervention characteristics. In the same domain, another major barrier was the lack of utility studies to provide evidence for genetic testing uptake. Technical hurdles, such as integrating genetic information to medical records, were identified as an inner settings barrier. Collaborations and lessons from early implementers could be useful strategies to overcome majority of the barriers across different health care settings. Strategies proposed by the included implementation studies to overcome these barriers are summarized and can be used as guidance in future. CONCLUSION: Barriers and strategies identified in this scoping review can provide implementation guidance for practice sites that are interested in implementing genetic testing.

Understanding patient cost-sharing thresholds for diabetes treatment attributes via a discrete choice experiment.

BACKGROUND: The process used to prefer certain products across drug classes for diabetes is generally focused on comparative effectiveness and cost. However, payers rarely tie patient preference for treatment attributes to formulary management resulting in a misalignment of value defined by providers, payers, and patients. OBJECTIVES: To explore patients' willingness to pay (WTP) for the predetermined high-value and low-value type 2 diabetes mellitus (T2DM) treatments within a health plan. METHODS: A cross-sectional discrete choice experiment (DCE) survey was used to determine patient preference for the benefit, risk, and cost attributes of T2DM treatments. A comprehensive literature review of patient preference studies in diabetes and a review of guidelines and medical literature identified study attributes. Patients and diabetes experts were interviewed and instructed to identify, prioritize, and comment on which attributes of diabetes treatments were most important to T2DM patients. The patients enrolled in a health plan were asked to respond to the survey. A multinomial logit model was developed to determine the relative importance and the patient's WTP of each attribute. The patients' relative values based on WTPs for T2DM treatments were calculated and compared with the treatments by a health plan. RESULTS: A total of 7 attributes were selected to develop a web-based DCE questionnaire survey. The responses from a total of 58 patients were analyzed. Almost half (48.3%) of the respondents took oral medications and injections for T2DM. The most prevalent side effects due to diabetes medications were gastrointestinal (43.1%), followed by weight gain (39.7%) and nausea (32.8%). Patients were willing to pay more for treatments with proven cardiovascular benefit and for the risk reduction of hospitalization from heart failure. On the other hand, they would pay less for treatments with higher gastrointestinal side effects. Patients were willing to pay the most for sodium-glucose cotransporter 2 inhibitor and glucagon-like peptide 1 receptor agonist agents and the least for dipeptidyl peptidase-4 inhibitors and thiazolidinediones. CONCLUSIONS: This study provides information to better align patient, provider, and payer preferences in both benefit design and value-based formulary strategy for diabetes treatments. A preferred placement of treatments with cardiovascular benefits and lower adverse gastrointestinal side effects may lead to increased adherence to medications and improved clinical outcomes at a lower overall cost to both patients and their health plan. DISCLOSURES: This study was supported by a grant from the PhRMA Foundation.

Service-level barriers to and facilitators of access to services for the treatment of alcohol use disorder and problematic alcohol use: protocol for a scoping review.

INTRODUCTION: Prior to the COVID-19 pandemic, substance use health services for treatment of alcohol use disorder and problematic alcohol use (AUD/PAU) were fragmented and challenging to access. The pandemic magnified system weaknesses, often resulting in disruptions of treatment as alcohol use during the pandemic rose. When treatment services were available, utilisation was often low for various reasons. Virtual care was implemented to offset the drop in in-person care, however accessibility was not universal. Identification of the characteristics of treatment services for AUD/PAU that impact accessibility, as perceived by the individuals accessing or providing the services, will provide insights to enable improved access. We will perform a scoping review that will identify characteristics of services for treatment of AUD/PAU that have been identified as barriers to or facilitators of service access from the perspectives of these groups. METHODS AND ANALYSIS: We will follow scoping review methodological guidance from the Joanna Briggs Institute. Using the OVID platform, we will search Ovid MEDLINE including Epub Ahead of Print and In-Process and Other Non-Indexed Citations, Embase Classic+Embase, APA PsychInfo, Cochrane Register of Controlled Trials, the Cochrane Database of Systematic Reviews and CINAHL (Ebsco Platform). Multiple reviewers will screen citations. We will seek studies reporting data collected from individuals with AUD/PAU or providers of treatment for AUD/PAU on service-level factors affecting access to care. We will map barriers to and facilitators of access to AUD/PAU treatment services identified in the relevant studies, stratified by service type and key measures of inequity across service users. ETHICS AND DISSEMINATION: This research will enhance awareness of existing evidence regarding barriers to and facilitators of access to services for the treatment of alcohol use disorder and problematic alcohol use. Findings will be disseminated through publications, conference presentations and a stakeholder meeting. As this is a scoping review of published literature, no ethics approval was required.

Measurement and valuation of the attributes of innovation of healthcare technologies: a systematic review.

OBJECTIVE: Innovative technologies (e.g. treatments) play a pivotal role in improving patient's well-being and in consequence population health outcomes. However, there is lack of consensus and comprehensive summary what constitutes innovation. Additionally, valuing them using traditional cost-effectiveness analysis is unlikely to capture the full range of benefits of these innovative technologies. This review aims to understand how innovation attributes were measured and/or valued in healthcare. MATERIALS AND METHODS: We systemically searched four databases, PubMed, Embase, PsycINFO, and Econlit, from inception to April 2021. Studies were included if they measured and/or valued the attributes of innovation for healthcare identified in our previous systematic review. Any other potential recommended methods to measure and/or value the innovation attributes were also extracted. RESULTS: Of 546 articles, a total of 17 articles were finally included in this review. If attributes were measured and traded-off relative to costs, then it was considered as valuation of those attributes. Two specific attributes of innovation, i.e. substantial benefits and convenience and/or adherence were measured using adherence rate and life year or QALY gain. When innovation attribute was non-specific it was described as "overall innovation" and measured using overall innovativeness scale (e.g. point/binary scale). QALY-based cost-effectiveness analysis (CEA) was commonly used to assess and value substantial benefit attribute. Other valuation approaches were (i) rating, (ii) the economic value of life year gain, (iii) multiple criteria decision analysis (MCDA), (iv) incremental net health benefit (INHB), and (v) quality-adjusted cost of care (QACC). ICER threshold adjustment and multiple-criteria decision analysis (MCDA) are two common recommended approaches to capture the innovation comprehensively. We found that MCDA approaches often promoted and discussed but were sub-optimally used to incorporate different value attributes into decision-making. CONCLUSIONS: Existing methods used by payers to measure and value the innovation component of a new product do not reflect the full range of health and cost impacts. They generally do not consider the alternative perspectives of patients, providers, caregivers, and society. Key challenges remain to appropriately measure and value innovation attributes and incorporate them into HTA decision making.

Characterizing attributes of innovation of technologies for healthcare: a systematic review.

OBJECTIVES: Characterizing and evaluating the holistic value of innovative healthcare technologies (e.g. treatments, services) constitutes a crucial goal to maximize limited resources. However, the characteristics of innovation have not been well identified. This review aims to describe the characteristics of healthcare innovation. METHODS: We performed a comprehensive systematic search using PubMed, Embase, PsycINFO, and Econlit from inception to July 2022. Articles were included if they described innovation or the characteristics of innovation of the technologies in healthcare. Characteristics or definitions of innovation directly or indirectly described as innovation were extracted from the included articles. Two independent reviewers then conceptualized the identified characteristics of innovation to generate innovation attributes in healthcare. RESULTS: In total, 103 articles were included in this review. Eight attributes describing innovation, i.e. novelty, step change, substantial benefits, an improvement over existing technologies, convenience and/or adherence, added value, acceptable cost, and uncounted benefits, were conceptualized. Most of the identified innovation attributes were based on the researchers' perspective. CONCLUSIONS: This study conceptualized innovation attributes in healthcare based on the characteristics of healthcare innovation as defined in the literature. Further research is warranted to obtain a complete understanding of the perspectives of researchers and other stakeholders, including patients, healthcare providers, healthcare payers, and the pharmaceutical industry, on recognizing innovation in healthcare.KEY POINTSThis is the first systematic review to conceptualize attributes of healthcare innovation.We conceptualized eight attributes describing innovation, i.e. novelty, step change, substantial benefits, an improvement over existing technologies, convenience and/or adherence, added value, acceptable cost, and uncounted benefits based on the similar concept.In existing literature, patients' and caregivers' perspectives were less frequently found to describe the innovation attributes.Future research is needed to identify, measure, and value various stakeholders, including patients' and caregivers' perspectives on healthcare innovation.

Methodological approaches for assessing certainty of the evidence in umbrella reviews: A scoping review.

INTRODUCTION: The number of umbrella reviews (URs) that compiled systematic reviews and meta-analysis (SR-MAs) has increased dramatically over recent years. No formal guidance for assessing the certainty of evidence in URs of meta-analyses exists nowadays. URs of non-interventional studies help establish evidence linking exposure to certain health outcomes in a population. This study aims to identify and describe the methodological approaches for assessing the certainty of the evidence in published URs of non-interventions. METHODS: We searched from 3 databases including PubMed, Embase, and The Cochrane Library from May 2010 to September 2021. We included URs that included SR-MAs of studies with non-interventions. Two independent reviewers screened and extracted data. We compared URs characteristics stratified by publication year, journal ranking, journal impact factor using Chi-square test. RESULTS: Ninety-nine URs have been included. Most were SR-MAs of observational studies evaluating association of non-modifiable risk factors with some outcomes. Only half (56.6%) of the included URs assessed the certainty of the evidence. The most frequently used criteria is credibility assessment (80.4%), followed by GRADE approach (14.3%). URs published in journals with higher journal impact factor assessed certainty of evidence than URs published in lower impact group (77.1 versus 37.2% respectively, p < 0.05). However, criteria for credibility assessment used in four of the seven URs that were published in top ranking journals were slightly varied. CONCLUSIONS: Half of URs of MAs of non-interventional studies have assessed the certainty of the evidence, in which criteria for credibility assessment was the commonly used method. Guidance and standards are required to ensure the methodological rigor and consistency of certainty of evidence assessment for URs.

Genetic biomarkers in multiple sclerosis: An umbrella review of meta-analyses of observational studies.

BACKGROUND: Multiple sclerosis (MS) is multifactorial in nature, with both genetic and environmental factors contributing to disease risk. In this umbrella review, we aimed to summarize various non-HLA genes that have been investigated for their association with MS risk in meta-analyses (MAs) of observational studies. METHODS: Medline, Embase, Epistemonikos, and Cochrane Database of Systematic Reviews were searched for MAs up to July 2021. Evidence of association was ranked according to established criteria as follows: convincing, highly suggestive, suggestive, weak, or not significant. RESULTS: From 1,533 publications, 85 full-text articles were evaluated for eligibility, and 15 articles were selected that described 114 genetic associations. No associations were supported by convincing evidence. One association between the rs2104286 (A vs G contrast) polymorphism of the interleukin 2RA (IL2RA) gene and increased MS susceptibility was initially supported by highly suggestive evidence (OR 1.17; 95% CI 1.10-1.25) but it was downgraded to suggestive in the sensitivity and subgroup analyses. We also found six associations supported by suggestive evidence in the main analysis. CONCLUSION: The findings of this study imply that the cytokines genes interleukin IL2RA and IL7R may play a role in the development of MS. Data from more and better-designed studies are needed to establish robust evidence.

Accounting for Preference Heterogeneity in Discrete-Choice Experiments: An ISPOR Special Interest Group Report.

OBJECTIVES: Discrete choice experiments (DCEs) are increasingly used to elicit preferences for health and healthcare. Although many applications assume preferences are homogenous, there is a growing portfolio of methods to understand both explained (because of observed factors) and unexplained (latent) heterogeneity. Nevertheless, the selection of analytical methods can be challenging and little guidance is available. This study aimed to determine the state of practice in accounting for preference heterogeneity in the analysis of health-related DCEs, including the views and experiences of health preference researchers and an overview of the tools that are commonly used to elicit preferences. METHODS: An online survey was developed and distributed among health preference researchers and nonhealth method experts, and a systematic review of the DCE literature in health was undertaken to explore the analytical methods used and summarize trends. RESULTS: Most respondents (n = 59 of 70, 84%) agreed that accounting for preference heterogeneity provides a richer understanding of the data. Nevertheless, there was disagreement on how to account for heterogeneity; most (n = 60, 85%) stated that more guidance was needed. Notably, the majority (n = 41, 58%) raised concern about the increasing complexity of analytical methods. Of the 342 studies included in the review, half (n = 175, 51%) used a mixed logit with continuous distributions for the parameters, and a third (n = 110, 32%) used a latent class model. CONCLUSIONS: Although there is agreement about the importance of accounting for preference heterogeneity, there are noticeable disagreements and concerns about best practices, resulting in a clear need for further analytical guidance.

The Economic Burden of Multiple Sclerosis in the United States: Estimate of Direct and Indirect Costs.

BACKGROUND AND OBJECTIVES: A recent report estimated that approximately 1 million adults were living with multiple sclerosis (MS) in the United States. Although MS is rarely the direct cause of death, its debilitating effects on normal body functions can result in considerable disruption to daily living and life roles including work, physical independence, mobility, social interaction, and participation in leisure activities. This study estimated the total economic burden of MS in the United States in 2019. METHODS: This study used a prevalence-based approach to estimate the national economic burden of MS. Claims from 3 sources (Medicare Current Beneficiary Survey, Medicare Standard Analytical File, and Optum de-identified Normative Health Information System) were used to obtain direct costs and a survey was developed to collect indirect costs (e.g., labor market productivity losses, costs of paid and unpaid caregivers, home modification) from 946 patients with MS (PwMS). Direct medical costs reflected the difference in the total average annual amount paid for PwMS vs matched controls without MS. Future earnings loss due to premature death attributable to MS was calculated using Centers for Disease Control and Prevention mortality data and Medicare claims data. RESULTS: The estimated total economic burden was $85.4 billion, with a direct medical cost of $63.3 billion and indirect and nonmedical costs of $22.1 billion. Retail prescription medication (54%); clinic-administered drugs, medication, and administration (12%); and outpatient care (9%) were the 3 largest components of the direct costs. The average excess per-person annual medical costs for PwMS was $65,612; at $35,154 per person, disease-modifying therapies (DMTs) accounted for the largest proportion of this cost. The cost per DMT user ranged from $57,202 to $92,719, depending on sex-age strata. The average indirect and nonmedical costs were $18,542 per PwMS and $22,875 per PwMS if caregivers' costs were included. Lost earnings due to premature death, presenteeism, and absenteeism losses were the largest indirect cost components. DISCUSSION: MS is a costly chronic disease, with direct costs of prescription drugs and indirect productivity loss being important cost drivers. Our findings suggested that the burden of MS in the United States has been underestimated.

Patients' Preferences for Sodium-Glucose Cotransporter 2 Inhibitors and Glucagon-Like Peptide-1 Receptor Agonists.

Purpose: To determine patients' preferences for sodium-glucose cotransporter 2 inhibitors (SGLT-2is) and glucagon-like peptide-1 receptor agonists (GLP-1RAs). Patients and Methods: A cross-sectional, web-based discrete choice experiment was conducted among US adults with type 2 diabetes mellitus (T2DM) in May 2021. Six attributes-the route and frequency of administration, the chance of reaching target HbA1c in six months, the percentage reduction in the risk of major adverse cardiovascular events (MACE), the chance of gastrointestinal side effects, the chance of genital infection, and out-of-pocket cost per month-were identified from literature review and consultation with patients and clinicians. A Bayesian efficient design was used to generate choice sets. Each choice set contained two hypothetical SGLT-2i and GLP-1 RA alternatives described by the attributes and an opt-out alternative. A total of 176 patients were asked to select the most preferred option from each choice set. Mixed logit (ML) and latent class (LC) models were developed. The conditional relative importance of each attribute was determined. Results: The ML model showed the out-of-pocket cost had the highest conditional relative importance, followed by the chance of reaching the target HbA1c. The best LC model revealed two patient classes. All attributes were significantly important to the patients in both classes, except the chance of genital infection in class 2. Compared to the patients in class 2, the patients in class 1 were older (approximately 65 vs 56 years) and had a higher number of comorbidities (approximately three vs two). Conclusion: T2DM patients placed different preference weights or importance across SGLT-2i and GLP-1 RA attributes. Preference heterogeneity was found among patients with different ages and numbers of comorbidities.

Using Machine Learning Approaches to Predict Short-Term Risk of Cardiotoxicity Among Patients with Colorectal Cancer After Starting Fluoropyrimidine-Based Chemotherapy.

Cardiotoxicity is a severe side effect for colorectal cancer (CRC) patients undergoing fluoropyrimidine-based chemotherapy. To develop and compare machine learning algorithms to predict cardiotoxicity risk among nationally representative CRC patients receiving fluoropyrimidine, CRC Patients with at least one claim of fluoropyrimidine after their cancer diagnosis were included. The outcome was the 30-day cardiotoxicity from the first day of starting fluoropyrimidine. The machine learning models including extreme gradient boosting (XGBoost), random forest (RF), and logistic regression (LR) were developed using 2006-2011 SEER-Medicare data, and model performances were evaluated using 2012-2014 data. Precision, F1 score, and area under the receiver operating characteristics curve (AUC) were measured to evaluate model performances. Feature importance plots were obtained to quantify the predictor importance. Among 36,030 CRC patients, 18.74% of them developed cardiotoxicity within 30 days since the first fluoropyrimidine. The XGBoost approach had better prediction performance with higher precision (0.619) and F1 score (0.406) in predicting the 30-day cardiotoxicity, compared to the RF (precision, 0.607 and F1 score, 0.395) and LR (precision, 0.610 and F1 score, 0.398). According to the DeLong's test for AUC difference, the XGBoost significantly outperformed the RF and LR (XGBoost, 0.816 vs. RF, 0.804, P < 0.001; XGBoost vs. LR, 0.812, P = 0.003, respectively). Feature importance plots identified pre-existing cardiac conditions, surgery, older age as top significant risk factors for cardiotoxicity events among CRC patients after receiving fluoropyrimidine. In summary, the developed machine learning models can accurately predict the occurrence of 30-day cardiotoxicity among CRC patients receiving fluoropyrimidine-based chemotherapy.

Using latent class and quantum models to value equity in health care: a tale of 2 stories.

Cost-effectiveness analysis (CEA) with quality-adjusted life-year (QALY) was introduced to address health equity concerns in value assessment. However, QALY fails to capture patient preference. Stated preference methods (eg, discrete choice experiment [DCE]) have been increasingly used to incorporate patient preference into the value assessment framework in health care. Still, ones with a moral dimension such as health equity do not exist. The objective of this paper was to describe 2 stated preference approaches that can empirically value health equity. First, the decision-maker perceptions of the prevalence of equity dimensions in DCE choice tasks are identified. A latent class model based on random utility theory is proposed to derive the value of equity from the decision makers with different perceptions of the prevalence of equity dimensions. Second, equity attributes are incorporated in DCE choice tasks, and a quantum choice model, which can capture stochasticity during the decision process in the mind of the decision makers, is used to value the equity. These approaches will improve existing value assessment methods to address health equity adequately. DISCLOSURES: This study received no outside funding. Ngorsuraches has received research grants from Bristol Myers Squibb and through the University of Utah and PhRMA Foundation.

Using latent class and quantum models to value equity in health care: a tale of 2 stories.

Cost-effectiveness analysis (CEA) with quality-adjusted life-year (QALY) was introduced to address health equity concerns in value assessment. However, QALY fails to capture patient preference. Stated preference methods (eg, discrete choice experiment [DCE]) have been increasingly used to incorporate patient preference into the value assessment framework in health care. Still, ones with a moral dimension such as health equity do not exist. The objective of this paper was to describe 2 stated preference approaches that can empirically value health equity. First, the decision-maker perceptions of the prevalence of equity dimensions in DCE choice tasks are identified. A latent class model based on random utility theory is proposed to derive the value of equity from the decision makers with different perceptions of the prevalence of equity dimensions. Second, equity attributes are incorporated in DCE choice tasks, and a quantum choice model, which can capture stochasticity during the decision process in the mind of the decision makers, is used to value the equity. These approaches will improve existing value assessment methods to address health equity adequately. DISCLOSURES: This study received no outside funding. Ngorsuraches has received research grants from Bristol Myers Squibb and through the University of Utah and PhRMA Foundation.

Patients and Partners in Research: Patient and Caregiver Perceptions of Research Engagement and the Role of Their Psychosocial States in Participation.

Multiple sclerosis (MS) is one of the most common, nontraumatic, disabling diseases diagnosed in adults. Self-empowered patients and families are valued members of the MS research team. The objective of this study was to explore patient and family perceptions of the influence of psychosocial state on their willingness to be research partners. Researchers conducted 5 focus groups with MS patients and family from the Upper Midwest Chapter of the National Multiple Sclerosis Society. The researchers asked questions addressing psychosocial factors influencing ability and willingness to work with MS researchers as partners. Relevant themes were identified including comfort level of individuals in formulating research questions, comfort level engaging in research, understanding of the meaning of research and self-perception about skills, research training, and knowledge needs. The findings of this study support the role of MS patients' perspectives about MS, their understanding of the science of MS, and role of their psychosocial states as all these factors were patient identified as being key to their ability to be active, engaged and willing research participants.