United States

Background
The under-reporting of subject demographics and race disparities in ophthalmic clinical trials have been documented in the past. The Final Rule for Clinical Trials Registration and Results Information Submission conditionally requires race and ethnicity disclosure for studies whose primary completion date is on or after January 18, 2017. We examined the change in the enrollment and demographic disclosure rate among US-based ophthalmic clinical trials after the implementation of the Final Rule.

Methods
ClinicalTrials.gov was queried for “eye,” “eye diseases,” and “ocular.” US-based trials with a completed status and enrollment greater than or equal to 50 subjects were included (n=872). Trials with a primary completion date on or after 1/18/2017, and results first submitted on or after 4/18/2017 (Final Rule compliance date) were categorized as “post-requirement” (n=314) trials. Trials prior to these dates were categorized as “pre-requirement” (n=558) trials. Primary outcomes included the disclosure rate and enrollment of each race/ethnicity category. The disclosure rate before and after the implementation of the Final Rule was compared with Pearson’s chi-square test. The enrollment before and after the implementation of the Final Rule was compared with the Mann-Whitney U-test.

Results
The race disclosure rate, as defined by the proportion of studies disclosing any race information, significantly increased (p&lt;0.0001) among post-requirement trials (84.39%) compared to pre-requirement trials (26.16%). The ethnicity disclosure rate, as defined by the proportion of studies disclosing any ethnicity information, significantly increased (p&lt;0.0001) among post-requirement trials (55.73%) compared to pre-requirement trials (16.85%). The disclosure rate of all race/ethnicity categories increased significantly among post-requirement trials (p&lt;0.0001) compared to pre-requirement trials. There was no significant change in enrollment of any race/ethnicity category between all pre- and post-requirement trials. White subject enrollment was higher and Hispanic subject enrollment was lower in non-NIH-funded trials versus NIH-funded trials both before (White subjects, p=0.0022; Hispanic/Latino subjects, p=0.0495) and after (White subjects, p=0.0002; Hispanic/Latino subjects, p=0.0168) the implementation of the Final Rule.

Conclusion
While the disclosure rate of race in clinical trials approximately increased by a factor of 3, the enrollment of minorities demonstrated no change after the implementation of the Final Rule. White subject enrollment was higher, and Hispanic subject enrollment was lower in non-NIH-funded trials compared to NIH-funded trials after the implementation of the Final Rule, which has not been previously reported. Stronger legislation that requires the enrollment of minority groups and subsequent demographic information reporting is needed to improve diversity in ophthalmic clinical trials.

AMA Research Challenge 2023

Demographic Disclosure Rate and Enrollment Before and After the Final Rule in Ophthalmic Clinical Trials

Background
The under-reporting of subject demographics and race disparities in ophthalmic clinical trials have been documented in the past. The Final Rule for Clinical Trials Registration and Results Information Submission conditionally requires race and ethnicity disclosure for studies whose primary completion date is on or after January 18, 2017. We examined the change in the enrollment and demographic disclosure rate among US-based ophthalmic clinical trials after the implementation of the Final Rule.

Methods
ClinicalTrials.gov was queried for “eye,” “eye diseases,” and “ocular.” US-based trials with a completed status and enrollment greater than or equal to 50 subjects were included (n=872). Trials with a primary completion date on or after 1/18/2017, and results first submitted on or after 4/18/2017 (Final Rule compliance date) were categorized as “post-requirement” (n=314) trials. Trials prior to these dates were categorized as “pre-requirement” (n=558) trials. Primary outcomes included the disclosure rate and enrollment of each race/ethnicity category. The disclosure rate before and after the implementation of the Final Rule was compared with Pearson’s chi-square test. The enrollment before and after the implementation of the Final Rule was compared with the Mann-Whitney U-test.

Results
The race disclosure rate, as defined by the proportion of studies disclosing any race information, significantly increased (p<0.0001) among post-requirement trials (84.39%) compared to pre-requirement trials (26.16%). The ethnicity disclosure rate, as defined by the proportion of studies disclosing any ethnicity information, significantly increased (p<0.0001) among post-requirement trials (55.73%) compared to pre-requirement trials (16.85%). The disclosure rate of all race/ethnicity categories increased significantly among post-requirement trials (p<0.0001) compared to pre-requirement trials. There was no significant change in enrollment of any race/ethnicity category between all pre- and post-requirement trials. White subject enrollment was higher and Hispanic subject enrollment was lower in non-NIH-funded trials versus NIH-funded trials both before (White subjects, p=0.0022; Hispanic/Latino subjects, p=0.0495) and after (White subjects, p=0.0002; Hispanic/Latino subjects, p=0.0168) the implementation of the Final Rule.

Conclusion
While the disclosure rate of race in clinical trials approximately increased by a factor of 3, the enrollment of minorities demonstrated no change after the implementation of the Final Rule. White subject enrollment was higher, and Hispanic subject enrollment was lower in non-NIH-funded trials compared to NIH-funded trials after the implementation of the Final Rule, which has not been previously reported. Stronger legislation that requires the enrollment of minority groups and subsequent demographic information reporting is needed to improve diversity in ophthalmic clinical trials.

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Background
Performing ptosis surgery in an office-based setting is less costly to the health system relative to an operating room. However, 90% of US ptosis surgeries are performed in the less economical operating room. This study aims to understand the financial and practical factors involved in surgical location decision-making, and the modifiable incentives to influence migration from operating room to procedure room.

Design
Economic analysis 

Methods
Oculoplastic surgeons were surveyed to determine the most important attributes when deciding to perform a surgery in an operating room (OR) or office procedure room (PR). Responses were collated and common themes extracted. Consensus themes were operationalized into major domains: reimbursement, comorbidities, sedation requirements, and logistics. Reimbursement consisted of five levels starting at $550, with each level increasing by 50%, until total reimbursement tripled at $1650. Comorbidities, sedation requirements, and logistics each had two levels, with one being preferable.

A discrete choice analysis was used to evaluate the relative importance each factor had on decision-making by surveying oculoplastic surgeons. Participants were randomly assigned 14 out of 40 hypothetical ptosis procedure scenarios, asking physicians to choose between completing a procedure in the PR or OR. For all scenarios, OR reimbursement was $550. Key physician characteristics were collected: urban vs rural location, surgery center ownership, age, years of experience, and number of ptosis surgeries performed. Analysis was conducted using an econometric model that assumes physicians decide whether to use the PR by evaluating a random utility function.

Results
68 oculoplastic surgeons completed the survey, yielding 882 observations. Age and years of experience were highly correlated (.97) and only years of experience was used in the analysis.

Increasing PR reimbursement increased probability of choosing PR, with diminishing effect as reimbursement rose above $1100. Risk factors demonstrated expected directional effects: serious comorbidities, sedation requirements, and logistical issues each reduced probability of PR use for a given reimbursement. Rural offices dramatically increased probability of choosing PR. Number of surgeries performed slightly increased probability of PR choice for every 100 prior surgeries. Ownership and years of experience were not significant.

Conclusion
The model revealed reimbursement is the most important factor, especially at $1100 or more, followed by practice location, sedation, number of surgeries, logistical issues and comorbidities. The results suggest if all risk factors are low, doubling reimbursement increases the likelihood of using the PR by 35%. If all risk factors are high, the likelihood increases by 17%. This study shed light on the factors surgeons use to evaluate ptosis surgery location choice. The insight gained through this analysis will hopefully inform policy decisions and lead to a more efficient and thoughtful use of resources.

The Impacts of Reimbursement Rates on Ptosis Procedure Location Choice: A Discrete Choice Analysis

Background
The prevalence of diabetes and hypertension is disproportionately elevated in the Arab American population. Dearborn, the largest Arab American population in the United States, suffers specifically from these health inequities. The prevalence of diabetes in Dearborn is estimated to be greater than 18%, in a study conducted 20 years ago, with limited data suggesting more up-to-date figures. Hypertension, likewise, is also disproportionately elevated with over one-third of the population afflicted. These levels have called for urgent intervention by local and state health agencies, with reported glycemic goals being achieved in less than one-third of the population. These chronic, systemic diseases have many micro and macrovascular health complications; many of which manifest in the eye with resulting in irreversible vision loss. Hypertensive and diabetic retinopathy are among the most common ophthalmologic diseases and commonly result in painful vision loss, which alters the patient’s independence and self-confidence. These complications are financially burdensome with these patients having much needing consistent injections and intraocular surgery. By decreasing the health disparities found in this population, we can grant patients a better future in which we help save their vision.

These health disparities can be attributed to many things: language barriers, decreased access to medication, and decreased health literacy among other causes. One way to combat such inequity is with the Dearborn Sees project. This is a project in collaboration with the Dearborn Health Department (DHD), as well as pending cooperation with the American Association of Ophthalmologists (AAO). The goal was to design a website that is coded and written in Arabic from the ground up, with the most common ophthalmologic diseases explained in simple Arabic text and video that the common Arab American could understand. The website will also feature the ability to search for your nearest ophthalmologist and use artificial intelligence to triage symptoms from a questionnaire to suggest the degree of urgency of disease. 

Methods
Coding and building a website in Arabic with a database of Dearborn-based ophthalmologists and using artificial intelligence to triage potential ophthalmologic emergencies.

Results
This website is still being built, with the confirmed cooperation of the DHD, and pending cooperation of the AAO. 

Conclusion
The prevalence of diabetes and hypertension is disproportionally elevated in the Dearborn community. The implementation of technology that allows for easier comprehension for non-native speakers allows for far-reaching implications for many ethnically diverse communities throughout the United States.

The Dearborn Sees Project: Using Technology to Decrease Language Barriers and Improve Access to Care

Introduction: Readmission within the first 90 days following total joint arthroplasty (TJA) is both a predictor of postoperative complications as well as a cause of increased financial burden. Patients living in socioeconomically disadvantaged areas are known to be at increased risk for worse healthcare outcomes. This study hypothesized that 90- day readmission rates following aseptic TJA were associated with Area Deprivation Index (ADI), a surrogate marker for patients living in economically disadvantaged neighborhoods. 

Methods: All primary and aseptic revision TJAs performed in 2019 at one academic center were reviewed. A total of 1,084 patients were included with home addresses in 11 different states. The Neighborhood Atlas was used to calculate both the national (0-100 scale) and state (0-10 scale) ADIs for all patients, using metrics that include income, education, employment and housing quality. Chi-square tests were used for statistical analysis to calculate logistic regression models and odds ratios (OR) for examining the relationship between state and national ADIs and hospital readmission within the first 90 days following TJA. 

Results: There were a total of 82 readmissions found in the patient cohort. Of these readmissions, 27 were due to infection. The average state ADI was 4.75 and the average national ADI was 65.30. Logistic regression models showed no significant trends in 90-day readmissions based on state ADI (P=0.29). There was a statistically significant positive correlation between national ADI and 90-day readmission rates (Unit OR 1.01, P< 0.05). 

Conclusions: This study demonstrated that as a patient’s national ADI increased, there was a positive association with a patient’s odds of readmission within 90 days of an aseptic TJA. State ADIs did not have a significant association with 90- day readmission rates. Further investigations are required to understand the impact of patients’ socioeconomic status on post-operative complications and causes for readmission.

Area Deprivation Index as a Predictor of 90-day Readmission Rates in Total Joint Arthroplasty


Background
Tobacco use is a risk factor for head and neck squamous cell carcinomas (HNSCC) and is associated with poorer treatment outcomes. Patients who continue smoking after a cancer diagnosis are more likely to have tumor recurrence. Rural populations have higher tobacco use rates and higher observed incidence rates of tobacco-associated cancers. The goal is to identify smoking cessation barriers to improve treatment outcomes and overall survival for rural patients. 

Methods
Patients with a head and neck cancer diagnosis who were receiving care within the University of Rochester Medical system were consented. They completed a quantitative RedCap survey and/or a qualitative semi-structured interview. Head and neck cancer providers were also interviewed, and together, the responses were coded for themes related to cessation barriers and possible interventions. 

Results
The qualitative analysis identified a patient theme of self-determinism and support for smoking cessation. This includes both emotional support and information on external cessation resources. Patients made comments such as “There are people that can decide to quit and that's it. And there are people that need encouragement, right? There are people that need strength outside of themselves.” 

Providers identified a theme of developing standardized smoking cessation care. They spoke at length of the benefits of team members such as nurse navigators and dedicated smoking cessation staff. 

Quantitatively, rural patients were more likely to be smokers when compared to urban patients. Only 10% of interviewed rural patients (n=19) were likely to join a smoking cessation program if convinced by their PCP, whereas 38% of urban patients (n=29) could be convinced by their PCP (p<0.04). 

Discussion
Rural patients are less likely to respond favorably when counselled by their PCP. However, they value support from medical professionals. Cancer providers value a dedicated team member to deploy a standardized workflow for cessation counseling. Together, the qualitative and quantitative data both favor additional non-PCP team members when convincing rural patients to quit smoking. One novel solution, the “Rochester Model,” utilizes medical students to provide bedside smoking cessation to smoking patients. Preliminary results suggest that students are as effective as nurses in providing counseling when assessing smoking outcomes 1-, 3-, and 6-months post treatment. 

Conclusion
Non-PCP care members are essential to engaging rural smokers in cessation programs. Medical students are a possible new demographic of counselors. Further investigation is needed to assess their efficacy when counseling rural HNC patients.

Barriers to Smoking Cessation for Rural Head and Neck Cancer Patients

Background
Screen time is defined as time spent watching television, playing video games, or using electronic devices with a screen. Levels of screen time have increased in the pediatric population with some individuals consuming over 7 hours per day. In the literature, screen time has been shown to have effects on neuropsychiatric health and development, but there are limited comprehensive studies. The aim of this study was to determine the effects of screen time on mental health and neurodevelopment in the child and adolescent population in North America.

Methods
We conducted an umbrella review to assess the psychological effects of screen time on health outcomes in children and adolescents. We searched PubMed and Google Scholar for systematic reviews or meta-analyses published within the last 10 years. Studies were included in our initial search if they had the words “screen-time” with “meta-analysis” or “systematic review”. A total of 15 systematic reviews were found. These were narrowed down to 4 total systematic reviews that specifically addressed the child and adolescent population as well as outcomes regarding depression, anxiety, sleep disruption, language development, and academic development. Effect sizes were collected.

Results
Screen time in children and adolescents was found to have significant associations with several neuropsychiatric variables, including risk of depression (odds ratio 1.12, 95% confidence interval 1.03-1.22) and decreased sleep duration (2.283 [2.132-2.445]). Additionally, the meta-analyses studied show a negative association between screen time and language skills (n = 38, r = -0.14 [−0.18 to −0.10], OR 0.599 [0.515-0.694]), and no association with academic performance (d = -0.29 [−0.65 to 0.08], OR 0.591 [0.308-1.156]). 

Conclusion
There is an association between increased screen time and some adverse neuropsychiatric outcomes, including risk of depression, decreased sleep duration, anxiety, and lower language skills. Furthermore, the literature has even demonstrated a dose-response relationship for some outcomes. For example, participants with high screen time were more likely to have depression than their low screen time counterparts. These findings are increasingly important as technology becomes more prevalent and suggest that recommendations to limit screen time may mitigate adverse neuropsychiatric outcomes. Limitations of this umbrella review include the cross-sectional design of the meta-analyses and the accuracy of screen time reporting.


The Association of Screentime With Neuropsychiatric Health in the Pediatric Population: An Umbrella Review

Introduction. There are racial differences in how adverse childhood experiences (ACEs) affect depression which is experienced by 25% of cancer survivors. While previous studies have examined association between ACEs and depression in general population, studies focusing on cancer survivors are lacking. This study assessed the association between ACEs and history of depression among cancer survivors in different race groups.

Methods. This study was a cross-sectional analysis of the 2020 Behavioral Risk Factor Surveillance System among 19,241 cancer survivors. The ACE category (zero, one, two-three, ≥four) included questions assessing exposure to eight types of adverse childhood experiences before age 18 years. The outcome is self-reported history of depression. Three weighted multivariable logistic regression models were used to examine the association between ACE and depression for each race group: Non-Hispanic White (NHW), Non-Hispanic Black (NHB) and Hispanics, adjusting for age, sex, smoking status, income, education, marital status, body mass index, health status.

Results. In this sample, 41%, 22%, 21% and 16% reported having experienced zero, one, two-three, and >=4 ACEs respectively. Majority of survivors were NHW (82.5%) while 6.2%, 6.4% and 4.9% were NHB, Hispanics, and Others respectively. Personal history of depression was reported by 21% of survey respondents. Among survivors experiencing >=4 ACEs, depression was reported by 46.9 % of NHW, 55.2% of NHB and 50.6% of Hispanics. In the adjusted models, among NHW survivors with 1 ACE (aOR: 1.7, 95% CI. 1.3– 2.2), 2-3 ACEs (aOR: 1.9, 95% CI. 1.5– 2.4), or >=4 ACES (aOR: 4.2, 95% CI. 3.3– 5.5) had higher odds of depression compared with those with zero ACEs. Among NHB, survivors with >=4 ACEs had higher odds of depression (aOR: 2.5, 95% CI. 1.2– 5.0) compared with those with zero ACEs; no significant difference was observed for survivors with 1 or 2-3 ACEs. Similarly, among Hispanics, survivors with >=4 ACEs had higher odds of depression (aOR: 11.3, 95% CI. 5.4– 23.8) compared with those with zero ACEs whiles no significant difference was observed for survivors with 1 or 2-3 ACEs.

Conclusion. Cancer survivors with ACEs may represent an important targeted prevention group to reduce risk of depression. While there is a relationship between all categories of ACE and depression among NHW cancer survivors, only those with >=4 ACEs had association with depression among NHB and Hispanics. Variation by race warrants additional studies regarding potential for selective prevention and identification of resilient, cultural, and healthcare access factors.

Keywords. adverse childhood experiences, depression, cancer survivors, racial disparities


Racial disparities in the association between adverse childhood experiences and history of self-reported depression among cancer survivors

Background The US has a severe shortage of psychiatry workforce. In 2021, one in three Americans lived in Mental Health Professional Shortage Area (MHPSAs). Telehealth has long been advocated as a promising delivery model to mitigate the psychiatry workforce shortage but is limited by broadband access. This study identified counties without either psychiatrists or broadband coverage, described their characteristics, and examined their mental health outcomes.


Methods This cross-sectional analysis of all US counties employed public data in 2020. We used psychiatrist data from the Health Resources and Services Administration’s Area Health Resources Files, county socio-demographic characteristics from the American Community Survey, county-level measurements of broadband coverage from the Department of Commerce, and mental health outcomes from the County Health Rankings. We first identified counties without psychiatrists or broadband coverage in 2020 before performing a multivariate logistic regression to assess characteristics of those counties. The regression included state fixed effects, controlling for county level covariates: health insurance, unemployment, educational attainment, racial/ethnicity composition, household income, rurality (defined as the 2013 USDA rural-urban continuum codes of 8 or 9), and MHPSA designation. We used chi-squared tests to compare percent of adults with a history of depression, frequent mental distress, and drug overdose deaths and completed suicides per 100,000 population between counties without psychiatrists or broadband and other counties.


Results
We found that 596 (19%) counties were without psychiatrists or broadband, representing 10.5 million residents. Our regression results indicated that these counties were more likely to be rural (adjusted odds ratio [AOR]=3.048, p<0.01), have higher unemployment rates (AOR=1.122, p<0.01) and uninsurance rates (AOR=1.031, p<0.01), and lower proportion of population with bachelor’s degrees (AOR=0.919, p<0.01), but were not associated with MHPSA designation. 

Counties without psychiatrists or broadband had higher percentages of adults with a history of depression (22.4% vs 18.9%, p<0.01), frequent mental distress (16.5% vs 13.8%, p<0.01), drug overdose mortality (40.9 vs 11.1 per 100,000, p<0.01), and completed suicides (88.1 vs 11.3 per 100,000, p<0.01) compared to other counties. 


Conclusion: Despite the recent expansion of telehealth services, continued gaps in both broadband coverage and the psychiatrist workforce exist and are associated worse mental health outcomes, highlighting the need for further policy interventions to improve digital equity and access to psychiatric care, especially by targeting predominately rural counties and counties with lower socio-economic status.

Lacking Both Psychiatry Workforce and Broadband Coverage and Association with Mental Health Outcomes

Background 
Research has demonstrated that regularly measuring and monitoring SUD patients during treatment enhances outpatient mental health outcomes. (Lambert et al., 2003). Systematically monitoring patient progress in treatment for substance abuse can sustain individualized care. (Cacciola et al., 2013). However, consensus on which tool to adapt for SUD treatment outcomes and monitoring remains hindered by the diversity of 
outcome criteria proposed for SUD treatment (Alves et al., 2017). This study aims to identify, examine, and compare existing tools for measuring SUD treatment outcomes, considering their characteristics, benefits, limitations, utility, and cost-effectiveness. 

Methods 
Thirteen measurement tools used for SUD were identified through PubMed and Addictions Drug and Alcohol Institute Library searches. Tools analyzed include WHO- QOL, WHO-QOL-BREF, ARC, BARC-10, PHQ-9, TEA, OCVAS, BAM, COWS, ASI-5, ASI-Lite, CAGE-AID and AUDIT. Domains covered by these tools were categorized into Substance Use, Social, Physical Health, Mental Health and Economic. We performed a qualitative analysis of differences between these tools based on their coverage of the above domains, question length and format, administration time, scoring/analysis, and frequency of administration. 

Results 
Our results demonstrated that many of the identified SUD outcome measurement tools covered varying domains. Of all the tools analyzed, 38% covered all 5 domains while 3 tools focused solely on the Substance Use domain. The most commonly covered domains were “Substance Use” and “Mental Health” each represented by 9 tools, followed by “Social”, “Physical Health” and “Economic” domains, each represented by 8 tools. Question structure varied, with Likert scaling being most common. The number of 
questions ranged from 1 to 200, and the time required for completion variedfrom under 1 minute to 75 minutes. Scoring methods included summation, averaging, formulaic scoring, and floor vs ceiling scoring. Frequency of administration varied across settings. 

Conclusion 
Lack of consensus and standardization in measurement tools for SUD poses significant challenges in assessing, monitoring and treating SUD. Absence of standardized tools hinders treatment outcome comparisons, evaluation of intervention effectiveness, and evidence-based decisions. It also impedes the development of uniform guidelines, which may result in suboptimal care. The burden caused by this lack of standardization and overall consensus emphasizes the urgent need for collaboration and agreement in the field of SUD measurement tools. Such consensus could provide great improvement to assessment, treatment and overall outcomes of those affected.

Examining Strengths and Limitations of Treatment Outcome Measurement Tools for Substance Use Disorders

Background: Lung transplants from donors with hepatitis C (HCV D+) have excellent outcomes, but these organ offers are often not even considered or, if considered, continue to be declined. We evaluated whether (1) being listed to consider and (2) accepting HCV D+ offers provided a survival benefit to lung transplant candidates.
Methods: Using the Scientific Registry of Transplant Recipients, we identified all adult (≥18 years) lung transplant candidates 2016-2021 and compared waitlist mortality between candidates listed as willing vs. not willing to consider HCV D+ offers using Fine Gray competing risk regression. Among those who were listed as willing to consider HCV D+ offers, we then identified all candidates offered an HCV D+ lung that was later accepted and followed them from offer decision until death or end-of-study. We estimated adjusted mortality risk of accepting vs. declining an HCV D+ lung offer using propensity-weighted Cox regression.
Results: From 2016-2021, we identified 21,007 lung transplant candidates, 33.8% of whom were willing to consider HCV D+ offers. Candidates willing to consider HCV D+ offers had a 17% lower risk of waitlist mortality (subhazard ratio 0.83, 95%CI 0.75-0.91, p<0.001) than candidates not willing to consider HCV D+ offers overall, and a 24% lower risk of mortality after adjusting for candidate characteristics (subhazard ratio 0.76, 95%CI 0.69-0.84, p<0.001). Over the same period, 665 HCV D+ lung offers were accepted after being declined a total of 2,562 times. HCV D+ offer acceptance vs. decline was associated with a 20% lower risk of mortality (adjusted hazard ratio 0.80, 95% CI 0.66-0.96, p=0.02). Among candidates who declined HCV D+ offers, 66.1% eventually received a lung transplant from a donor without HCV, 12.4% received a different HCV D+ lung transplant, 14.8% were removed from the waitlist, 5.0% died, and 1.8% remained on the waitlist at three years after initial HCV D+ offer decline. 
Conclusion: Considering vs. not consider HCV D+ lung offers was associated with a 24% lower risk of waitlist mortality, while accepting vs. declining an HCV D+ lung offer was associated with a 20% lower risk of mortality. Centers and candidates should consider accepting suitable HCV D+ lung offers to optimize outcomes, as it could mean the difference between excellent survival and waiting for a supposedly “better” offer that might never come.

To Decline or Not To Decline: Consequences of Decision-Making 
Regarding Lung Offers from Donors with Hepatitis C

**Scoring is only possible in the semifinals hall**

**Abstract:**



Next from AMA Research Challenge 2023

The Impacts of Reimbursement Rates on Ptosis Procedure Location Choice: A Discrete Choice Analysis

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