United States

Background: Medicare reimbursements are federally determined, while Medicaid reimbursements are determined by each state. More variable Medicaid reimbursements can create financial and administrative burdens that may prevent patients from receiving care.
Objective: To evaluate and characterize state variation in Medicaid and Medicare published reimbursement rates for the 20 most commonly ordered computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) and radiograph (XR) studies. 
Methods: The 20 most commonly performed CT, MRI, US, and XR studies (80 studies) based on Medicare’s 2019 National Summary Data File were evaluated. The technical and professional components of reimbursements were analyzed. Paired t-tests were used to compare the average provider reimbursement rates, the CV of reimbursement rates, and the proportion of each total reimbursement rate accounted for by the professional component between Medicare and Medicaid.
Results: Medicare reimbursement variation (CV range: 0.07-0.08) was significantly lower than Medicaid reimbursement variation (CV range: 0.217-0.548) (P &lt; 0.05 for all studies). For Medicaid, US had the lowest variation (CV= 0.280), then CT (CV= 0.328), XR (CV= 0.345) and MRI (CV= 0.398). Medicare dedicated a higher percentage to professional components than Medicaid for CT and MRI (P &lt; 0.001); Medicaid proportionally paid greater professional component fees for XR (P = 0.002). Most reimbursement volatility was due to fluctuations in the technical rather than professional components. 
Discussion: Medicaid reimbursements for the most commonly ordered imaging studies were significantly more variable than Medicare reimbursements. This reimbursement variation may limit access to imaging care for certain populations.

AMA Research Challenge 2022

State Variation of Medicaid Reimbursement Rates in the 20 most commonly ordered CT, MRI, Ultrasound and Radiograph Studies May Contribute to Geographic Healthcare Disparities

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Charles Lopresto, DO

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Welcome to the largest national, multi-specialty research event featuring research from 750 medical students, residents and fellows, and international medical graduates.


Background: Medicare reimbursements are federally determined, while Medicaid reimbursements are determined by each state. More variable Medicaid reimbursements can create financial and administrative burdens that may prevent patients from receiving care.
Objective: To evaluate and characterize state variation in Medicaid and Medicare published reimbursement rates for the 20 most commonly ordered computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) and radiograph (XR) studies. 
Methods: The 20 most commonly performed CT, MRI, US, and XR studies (80 studies) based on Medicare’s 2019 National Summary Data File were evaluated. The technical and professional components of reimbursements were analyzed. Paired t-tests were used to compare the average provider reimbursement rates, the CV of reimbursement rates, and the proportion of each total reimbursement rate accounted for by the professional component between Medicare and Medicaid.
Results: Medicare reimbursement variation (CV range: 0.07-0.08) was significantly lower than Medicaid reimbursement variation (CV range: 0.217-0.548) (P < 0.05 for all studies). For Medicaid, US had the lowest variation (CV= 0.280), then CT (CV= 0.328), XR (CV= 0.345) and MRI (CV= 0.398). Medicare dedicated a higher percentage to professional components than Medicaid for CT and MRI (P < 0.001); Medicaid proportionally paid greater professional component fees for XR (P = 0.002). Most reimbursement volatility was due to fluctuations in the technical rather than professional components. 
Discussion: Medicaid reimbursements for the most commonly ordered imaging studies were significantly more variable than Medicare reimbursements. This reimbursement variation may limit access to imaging care for certain populations.

poster

Background
The 2013 United States Preventive Services Task Force (USPSTF) lung cancer screening (LCS) guidelines were derived from clinical trials of predominantly White men, and lower rates of LCS eligibility have subsequently been found for Black and Hispanic adults. We evaluated whether the revised 2021 USPSTF criteria reduced inequities in LCS eligibility among a racially diverse sample of lung cancer patients. 

Methods
We conducted a retrospective chart review of patients at an urban safety net hospital diagnosed with a primary lung malignancy between 2015-2020. LCS eligibility was determined based on age, pack-years, and smoking status. For all patients and exclusively ever-smokers, χ2 tests were used to evaluate differences in LCS eligibility among demographic variables (race, sex, ethnicity, education level, insurance type) for both the 2013 and 2021 USPSTF criteria. Patients who were ineligible for LCS were categorized by respective reasons.

Results
Among 678 lung cancer patients (46% female, mean age 66 ± 10 years), 51% were White and 39% were Black. Using the 2013 guidelines, White patients (183 [57%]) would have been more likely to be eligible than Black (89 [37%]) and other-race patients (23 [35%]) (p<0.0001). Using the 2021 guidelines, White patients (220 [68%]) remained more likely to be eligible for LCS than Black (130 [54%]) and other-race patients (31 [48%]) (p=0.0002). The most common reason for ineligibility using the 2013 (183 [50%]) and 2021 (90 [33%]) guidelines was not meeting the pack-years threshold. We identified 88 never-smokers [White (23%), Black (47%)]. Among exclusively ever-smokers, there was no significant difference in eligibility by race under the 2021 criteria [White (73%), Black (65%), other-race (65%); (p=0.48)]. For both the 2013 and 2021 guidelines, sex, ethnicity, education level, and insurance type were not associated with differential screening eligibility among the entire study sample nor exclusively ever-smokers.

Conclusion
The 2021 USPSTF LCS guidelines may not be sufficient to eliminate racial inequities in LCS eligibility among patients who go on to be diagnosed with lung cancer. Differential rates of lung cancer among never-smokers may contribute to this inequity. Further research is needed to refine LCS guidelines, with particular consideration of non-smoking risk factors.

Black Race Remains Associated with Lower Eligiblity for Screening Using 2021 US Preventive Services Task Force Recommendations among Lung Cancer Patients at an Urban Safety Net Hospital

Previous studies have evaluated comorbidities and sociodemographic factors individually or by type but not comprehensively. This study aims to analyze the influence of a wide variety of factors in a single study to better understand the big picture of their effects on case-fatalities. This cross-sectional study used county-level comorbidities, social determinants of health such as income and race, measures of preventive healthcare, age, education level, average household size, population density, and political voting patterns were all evaluated on a national and regional basis. Analysis was performed through Generalized Additive Models and adjusted by the COVID-19 Community Vulnerability Index (CCVI). Effect estimates of COVID-19 fatality rates for risk factors such as comorbidities, sociodemographic factors and determinant of health. Factors associated with reducing COVID-19 fatality rates were mostly sociodemographic factors such as age, education and income, and preventive health measures. Obesity, minimal leisurely activity, binge drinking, and higher rates of individuals taking high blood pressure medication were associated with increased case fatality rate in a county. Political leaning influenced case case-fatality rates. Regional trends showed contrasting effects where larger household size was protective in the Midwest, yet harmful in Northeast. Notably, higher rates of respiratory comorbidities such as asthma and chronic obstructive pulmonary disease (COPD) diagnosis were associated with reduced case-fatality rates in the Northeast. Increased rates of chronic kidney disease (CKD) within counties were often the strongest predictor of increased case-fatality rates for several regions. Our findings highlight the importance of considering the full context when evaluating
contributing factors to case-fatality rates. The spectrum of factors identified in this study must be analyzed in the context of one another and not in isolation.


Comorbidities and Sociodemographic Factors Effect on COVID-19 Fatalities: A Comprehensive Analysis

Background: The United States endured one of the hardest hits of the COVID-19 pandemic. The ethnic minority groups were affected the most due to skepticism about the vaccines. Concerning vaccine hesitancy in the US, fewer studies were performed for the South Asian American population compared to other groups. This review summarizes the essential factors that contributed to vaccine hesitancy in South Asian Americans and other minority groups and outlines the strategies to circumvent these factors to increase vaccination rates in these populations.

Methods: We conducted a comprehensive search for peer-reviewed articles in electronic databases, PubMed and Google scholar. The key search terms were "COVID-19 vaccine hesitancy", "South Asian Americans and COVID-19 vaccine hesitancy," and "minority population in US and COVID-19 vaccine hesitancy". Studies that aimed to investigate the detailed and comprehensive analysis of attitudes and perceptions of people towards the COVID-19 vaccine were included in our review. We included cross-sectional studies, surveys, and narrative and systematic reviews published during the pandemic (up to December 2021). Studies published in a language other than English and preprint articles with no evidence of a peer review process were excluded from our review.

Results: A total of 70 articles were included in our review that met the inclusion criteria. The commonly encountered reasons for vaccine hesitancy were the expedited development of the COVID-19 vaccine, concerns regarding the vaccine safety, potential side effects and long-term consequences, doubt about the efficacy of the vaccine, and lack of trust in the health care system due to systemic racism and discrimination endured by minority population. Political biases and anti-vaccine propaganda through social media also contributed to vaccine hesitancy.

Conclusion: Concerns regarding the adverse effects and efficacy of the vaccine, lack of trust in the healthcare system, inadequate access to healthcare, and underrepresentation of minorities in clinical research contributed to vaccine hesitancy among the minority population, including South Asian Americans. Implementing health education programs with culturally & linguistically appropriate materials to create awareness regarding vaccination against COVID-19 and representing minority populations in health care research to gain trust will be beneficial.




COVID -19 Vaccine Hesitancy Among the Minorities in the US, including South Asian Americans: Facts and Reasons

Education Without Walls: Using a Street Medicine Program to Provide Real-World Interprofessional Learning

The development and implementation of artificial intelligence and machine learning (AI/ML) into healthcare offers exciting promises such as enhanced detection, prevention, and response to disease, automation of mundane tasks, promotion of healthy lifestyles, and disease self-management. While AI/ML can certainly be an asset, it is imperative to proactively confront potential problems throughout the development process. This presentation provides considerations across the health spectrum, including changes in medical training and knowledge, healthcare equity, the standard of care, and the patient-physician relationship. To maximize benefit from AI/ML, ethical and policy challenges that accompany the technology must be addressed so that AI/ML genuinely improves patients’ health and physician workplaces. This presentation provides an overview of such challenges and emphasizes how creating fair, beneficial AI/ML starts in its development process.

Ethical and Policy Challenges Associated with Machine Learning and Artificial Intelligence in Healthcare

Background: The Front Line Resilience (FLR) program was developed to provide mental resiliency tools to firefighters, health care professionals, and medical students serving Asheville, NC during the COVID-19 pandemic. Participants attended 15–30-minute weekly Zoom sessions to learn mindfulness topics. Interested participants were paired with a practice partner. The purpose of this study was to evaluate participants’ perceptions of the effectiveness of a virtual curriculum on their mindfulness practices and resiliency. 

Methods: FLR participants were invited to evaluate program effectiveness via online feedback surveys. Survey respondents were then invited to participate in an interview for more in-depth evaluation. Surveys were analyzed using descriptive statistics. Interviews were transcribed and independently assessed by two researchers via manifest content analysis. 

Results: Of all 46 participants who attended at least one FLR session, ten respondents completed the survey. Of those respondents, five (50%) participated in interviews. Respondents indicated that FLR had a moderate (70%) or significant (30%) effect on their mindfulness practice, and a moderate (60%) or significant (30%) effect on resilience. Thematic analysis of interviews revealed participants learned specific techniques to expand their resilience toolbox and valued connection and accountability with other frontline professionals; however, their experiences did not always meet expectations. 

Conclusion: FLR positively impacted mindfulness practices and resiliency of frontline workers during the COVID-19 pandemic. This model could be used to support mindfulness practices for other professions.

Front Line Resilience: A virtual curriculum with medical providers and firefighters during COVID-19

The aim of this study is to investigate the impact of the coronavirus pandemic on the rates of major lower extremity amputations related to the delayed treatment of patients with peripheral vascular disease and diabetes mellitus at Eastern Maine Medical Center (EMMC) in Bangor, Maine.

Impact of the COVID-19 Pandemic on the Rates of Peripheral Vascular Disease and Diabetes-Related Lower Extremity Amputations in a Level II Trauma Center in Northern Maine

Improving Health Professionals' and Learners' Attitudes Towards Homeless Individuals Through Street-Based Outreach

Background
Opioid-Use Disorder is characterized by the problematic use of opioids leading to significant impairment and distress. The disorder affects approximately 2.1 million people within the United States alone, and 16 million people worldwide as of 2016. Fortunately, there are several methods poised to aid in the prevention of OUD. One method is preemptive multimodal analgesia to reduce subjective post-operative pain outcomes as well as oral morphine equivalents. Another method utilizes a cheap, cost-effective at-home opioid disposal kit as a method to discard left-over opioid prescriptions after recovery.
Methods
The preemptive MMA study consisted of a retrospective chart analysis, which found 1416 eligible patients who underwent THA or TKA. The patients received acetaminophen, celecoxib, and gabapentin between 30-60 minutes pre-operatively. Post-operatively, oral morphine equivalents were monitored along with subjective pain scores. In reference to the at-home disposal kit study, a RCT compared patients receiving the usual standard of care, to the group obtaining an at-home opioid disposal kit post-op. A text messaging service was implemented to obtain self-reported data and disposal rates.
Results
The preemptive MMA led to a significant decrease in oral morphine equivalents at day zero and day two post-op, as well as a significant reduction in subjective pain scores at almost every time-period regardless of the operation.
In the at-home disposal kit study, 42.7% of patients in the control group self-reported disposal of their remaining opioids, while 60.0% of patients who received a kit disposed of their left-over medication. 
Conclusion
Preemptive MMA significantly reduced the patient’s subjective pain levels post-operatively at almost every time-period tested. It is important to emphasize that in this study the medications administered were non-opioids, as perioperative opioid prescriptions lead to an increased risk of developing OUD. Additionally, in a randomized clinical trial, mild opioids (Codeine/Acetaminophen) were found to be non-inferior to strong opioids in respect to pain after fractures requiring surgical intervention; therefore, a mild treatment plan is preferred and preventive in the development of OUD. Furthermore, at-home disposal kits could be used in conjunction with preemptive MMA to reduce the rate of OUD in the greater population by motivating patients with a proper disposal method.


Pre- and Post-Operative Practices to Reduce the Rate of Opioid-Use Disorder

Background: In the US, the majority of Class I medical device recalls—FDA’s most serious designation, indicating high probability of adverse health consequences or death—are attributed to devices cleared under the 510(k) pathway. The role of predicates, which are previously authorized devices used to clear new devices under 510(k), in Class I recalls has not been systematically studied. We sought to determine whether 510(k) devices subject to Class I recalls used predicates that had a previous history of recalls, and to assess whether recalled devices were used as predicates in future device authorizations.

Methods: In this cross-sectional study, all 510(k) devices subject to Class I recalls between January 2020 through December 2021 (“index devices”) were identified from the FDA’s annual recall listing. Information about predicate devices was extracted from index device decision memos in the Devices@FDA database. Devices authorized using index devices as predicates (“descendants”) were identified using a commercially available database. Devices were characterized by their regulatory history (medical specialty, product code, special designations, use of clinical evidence) and recall history (date of recall relative to index device recall or clearance, FDA classification of recall severity).

Results: Between 2020-21, 75 devices were subject to Class I recalls, with each recall affecting nearly ten thousand devices. Of these devices, 31 (41.3%) had prior recalls, including 13 (41.9%) with Class I recalls. These 75 devices had 109 unique predicates, of which 62 (56.9%) had prior recalls, including 43 (69.4%) with at least one Class I recall. Recalls for 36 predicates (30.3%) preceded the predicate’s use to support clearance of the index device, and recalls for 51 predicates (42.9%) preceded the index device’s Class I recall. Fifty-two (69.3%) index devices were predicates for subsequent device authorizations. Of the 94 unique descendants identified, 49 (52.1%) had recalls, including 39 (79.6%) with at least one Class I recall.

Conclusion: Many 510(k) devices subject to Class I recalls were authorized using predicates with a known history of safety concerns and were used to clear additional devices that were later recalled. Stronger safeguards for the 510(k) pathway are needed to prevent such problematic predicate selection.

Next from AMA Research Challenge 2022

Black Race Remains Associated with Lower Eligiblity for Screening Using 2021 US Preventive Services Task Force Recommendations among Lung Cancer Patients at an Urban Safety Net Hospital

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