Utility of Skin Tone on Pulse Oximetry in Critically Ill Patients: A Prospective Cohort Study.

OBJECTIVE: Pulse oximetry, a ubiquitous vital sign in modern medicine, has inequitable accuracy that disproportionately affects minority Black and Hispanic patients, with associated increases in mortality, organ dysfunction, and oxygen therapy. Previous retrospective studies used self-reported race or ethnicity as a surrogate for skin tone which is believed to be the root cause of the disparity. Our objective was to determine the utility of skin tone in explaining pulse oximetry discrepancies. DESIGN: Prospective cohort study. SETTING: Patients were eligible if they had pulse oximetry recorded up to 5 minutes before arterial blood gas (ABG) measurements. Skin tone was measured using administered visual scales, reflectance colorimetry, and reflectance spectrophotometry. PARTICIPANTS: Admitted hospital patients at Duke University Hospital. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Sao2-Spo2 bias, variation of bias, and accuracy root mean square, comparing pulse oximetry, and ABG measurements. Linear mixed-effects models were fitted to estimate Sao2-Spo2 bias while accounting for clinical confounders.One hundred twenty-eight patients (57 Black, 56 White) with 521 ABG-pulse oximetry pairs were recruited. Skin tone data were prospectively collected using six measurement methods, generating eight measurements. The collected skin tone measurements were shown to yield differences among each other and overlap with self-reported racial groups, suggesting that skin tone could potentially provide information beyond self-reported race. Among the eight skin tone measurements in this study, and compared with self-reported race, the Monk Scale had the best relationship with differences in pulse oximetry bias (point estimate: -2.40%; 95% CI, -4.32% to -0.48%; p = 0.01) when comparing patients with lighter and dark skin tones. CONCLUSIONS: We found clinical performance differences in pulse oximetry, especially in darker skin tones. Additional studies are needed to determine the relative contributions of skin tone measures and other potential factors on pulse oximetry discrepancies.

ENCoDE - a skin tone and clinical dataset from a prospective trial on acute care patients.

Background: Although hypothesized to be the root cause of the pulse oximetry disparities, skin tone and its use for improving medical therapies have yet to be extensively studied. Studies previously used self-reported race as a proxy variable for skin tone. However, this approach cannot account for skin tone variability within race groups and also risks the potential to be confounded by other non-biological factors when modeling data. Therefore, to better evaluate health disparities associated with pulse oximetry, this study aimed to create a unique baseline dataset that included skin tone and electronic health record (EHR) data. Methods: Patients admitted to Duke University Hospital were eligible if they had at least one pulse oximetry value recorded within 5 minutes before an arterial blood gas (ABG) value. We collected skin tone data at 16 different body locations using multiple devices, including administered visual scales, colorimetric, spectrophotometric, and photography via mobile phone cameras. All patients' data were linked in Duke's Protected Analytics Computational Environment (PACE), converted into a common data model, and then de-identified before publication in PhysioNet. Results: Skin tone data were collected from 128 patients. We assessed 167 features per skin location on each patient. We also collected over 2000 images from mobile phones measured in the same controlled environment. Skin tone data are linked with patients' EHR data, such as laboratory data, vital sign recordings, and demographic information. Conclusions: Measuring different aspects of skin tone for each of the sixteen body locations and linking them with patients' EHR data could assist in the development of a more equitable AI model to combat disparities in healthcare associated with skin tone. A common data model format enables easy data federation with similar data from other sources, facilitating multicenter research on skin tone in healthcare. Description: A prospectively collected EHR-linked skin tone measurements database in a common data model with emphasis on pulse oximetry disparities.

Utility of skin tone on pulse oximetry in critically ill patients: a prospective cohort study.

Importance: Pulse oximetry, a ubiquitous vital sign in modern medicine, has inequitable accuracy that disproportionately affects Black and Hispanic patients, with associated increases in mortality, organ dysfunction, and oxygen therapy. Although the root cause of these clinical performance discrepancies is believed to be skin tone, previous retrospective studies used self-reported race or ethnicity as a surrogate for skin tone. Objective: To determine the utility of objectively measured skin tone in explaining pulse oximetry discrepancies. Design Setting and Participants: Admitted hospital patients at Duke University Hospital were eligible for this prospective cohort study if they had pulse oximetry recorded up to 5 minutes prior to arterial blood gas (ABG) measurements. Skin tone was measured across sixteen body locations using administered visual scales (Fitzpatrick Skin Type, Monk Skin Tone, and Von Luschan), reflectance colorimetry (Delfin SkinColorCatch [L*, individual typology angle {ITA}, Melanin Index {MI}]), and reflectance spectrophotometry (Konica Minolta CM-700D [L*], Variable Spectro 1 [L*]). Main Outcomes and Measures: Mean directional bias, variability of bias, and accuracy root mean square (ARMS), comparing pulse oximetry and ABG measurements. Linear mixed-effects models were fitted to estimate mean directional bias while accounting for clinical confounders. Results: 128 patients (57 Black, 56 White) with 521 ABG-pulse oximetry pairs were recruited, none with hidden hypoxemia. Skin tone data was prospectively collected using 6 measurement methods, generating 8 measurements. The collected skin tone measurements were shown to yield differences among each other and overlap with self-reported racial groups, suggesting that skin tone could potentially provide information beyond self-reported race. Among the eight skin tone measurements in this study, and compared to self-reported race, the Monk Scale had the best relationship with differences in pulse oximetry bias (point estimate: -2.40%; 95% CI: -4.32%, -0.48%; p=0.01) when comparing patients with lighter and dark skin tones. Conclusions and relevance: We found clinical performance differences in pulse oximetry, especially in darker skin tones. Additional studies are needed to determine the relative contributions of skin tone measures and other potential factors on pulse oximetry discrepancies.

Cancer Informatics for Cancer Centers: Sharing Ideas on How to Build an Artificial Intelligence-Ready Informatics Ecosystem for Radiation Oncology.

In August 2022, the Cancer Informatics for Cancer Centers brought together cancer informatics leaders for its biannual symposium, Precision Medicine Applications in Radiation Oncology, co-chaired by Quynh-Thu Le, MD (Stanford University), and Walter J. Curran, MD (GenesisCare). Over the course of 3 days, presenters discussed a range of topics relevant to radiation oncology and the cancer informatics community more broadly, including biomarker development, decision support algorithms, novel imaging tools, theranostics, and artificial intelligence (AI) for the radiotherapy workflow. Since the symposium, there has been an impressive shift in the promise and potential for integration of AI in clinical care, accelerated in large part by major advances in generative AI. AI is now poised more than ever to revolutionize cancer care. Radiation oncology is a field that uses and generates a large amount of digital data and is therefore likely to be one of the first fields to be transformed by AI. As experts in the collection, management, and analysis of these data, the informatics community will take a leading role in ensuring that radiation oncology is prepared to take full advantage of these technological advances. In this report, we provide highlights from the symposium, which took place in Santa Barbara, California, from August 29 to 31, 2022. We discuss lessons learned from the symposium for data acquisition, management, representation, and sharing, and put these themes into context to prepare radiation oncology for the successful and safe integration of AI and informatics technologies.

Exploring barriers and facilitators of implementing an at-home SARS-CoV-2 antigen self-testing intervention: The Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) initiatives.

BACKGROUND: Evaluating community-based programs provides value to researchers, funding entities, and community stakeholders involved in program implementation, and can increase program impact and sustainability. To understand factors related to program implementation, we aimed to capture the perspective of community partners engaged in organizing and executing community-engaged programs to distribute COVID-19 at-home tests in underserved communities. METHODS: We conducted semi-structured interviews and focus groups with community-based stakeholders informed by the Outcomes for Implementation Research framework. RESULTS: Findings describe how community-engaged communication and dissemination strategies drove program adoption among grassroots stakeholders. Establishing and sustaining trusted relationships was vital to engaging partners with aligned values and capacity. Respondents characterized the programs as generally feasible and appropriate, and community partners felt capable of delivering the program successfully. However, they also described an increased burden on their workforce and desired more significant support. Respondents recognized the programs' community engagement practices as a critical facilitator of acceptability and impact. DISCUSSION: Implementation evaluation aims to inform current and future community outreach and engagement efforts with best practices. As we continue to inform and advance community-engaged disaster response practice, a parallel reimagining of public health funding mechanisms and timelines could provide a foundation for trust, collaboration, and community resiliency that endures beyond a given crisis.

Access to COVID-19 testing by individuals with housing insecurity during the early days of the COVID-19 pandemic in the United States: a scoping review.

Introduction: The COVID-19 pandemic focused attention on healthcare disparities and inequities faced by individuals within marginalized and structurally disadvantaged groups in the United States. These individuals bore the heaviest burden across this pandemic as they faced increased risk of infection and difficulty in accessing testing and medical care. Individuals experiencing housing insecurity are a particularly vulnerable population given the additional barriers they face. In this scoping review, we identify some of the barriers this high-risk group experienced during the early days of the pandemic and assess novel solutions to overcome these barriers. Methods: A scoping review was performed following PRISMA-Sc guidelines looking for studies focusing on COVID-19 testing among individuals experiencing housing insecurity. Barriers as well as solutions to barriers were identified as applicable and summarized using qualitative methods, highlighting particular ways that proved effective in facilitating access to testing access and delivery. Results: Ultimately, 42 studies were included in the scoping review, with 143 barriers grouped into four categories: lack of cultural understanding, systemic racism, and stigma; medical care cost, insurance, and logistics; immigration policies, language, and fear of deportation; and other. Out of these 42 studies, 30 of these studies also suggested solutions to address them. Conclusion: A paucity of studies have analyzed COVID-19 testing barriers among those experiencing housing insecurity, and this is even more pronounced in terms of solutions to address those barriers. Expanding resources and supporting investigators within this space is necessary to ensure equitable healthcare delivery.

Association of neighborhood-level sociodemographic factors with Direct-to-Consumer (DTC) distribution of COVID-19 rapid antigen tests in 5 US communities.

BACKGROUND: Many interventions for widescale distribution of rapid antigen tests for COVID-19 have utilized online, direct-to-consumer (DTC) ordering systems; however, little is known about the sociodemographic characteristics of home-test users. We aimed to characterize the patterns of online orders for rapid antigen tests and determine geospatial and temporal associations with neighborhood characteristics and community incidence of COVID-19, respectively. METHODS: This observational study analyzed online, DTC orders for rapid antigen test kits from beneficiaries of the Say Yes! Covid Test program from March to November 2021 in five communities: Louisville, Kentucky; Indianapolis, Indiana; Fulton County, Georgia; O'ahu, Hawaii; and Ann Arbor/Ypsilanti, Michigan. Using spatial autoregressive models, we assessed the geospatial associations of test kit distribution with Census block-level education, income, age, population density, and racial distribution and Census tract-level Social Vulnerability Index. Lag association analyses were used to measure the association between online rapid antigen kit orders and community-level COVID-19 incidence. RESULTS: In total, 164,402 DTC test kits were ordered during the intervention. Distribution of tests at all sites were significantly geospatially clustered at the block-group level (Moran's I: p < 0.001); however, education, income, age, population density, race, and social vulnerability index were inconsistently associated with test orders across sites. In Michigan, Georgia, and Kentucky, there were strong associations between same-day COVID-19 incidence and test kit orders (Michigan: r = 0.89, Georgia: r = 0.85, Kentucky: r = 0.75). The incidence of COVID-19 during the current day and the previous 6-days increased current DTC orders by 9.0 (95% CI = 1.7, 16.3), 3.0 (95% CI = 1.3, 4.6), and 6.8 (95% CI = 3.4, 10.2) in Michigan, Georgia, and Kentucky, respectively. There was no same-day or 6-day lagged correlation between test kit orders and COVID-19 incidence in Indiana. CONCLUSIONS: Our findings suggest that online ordering is not associated with geospatial clustering based on sociodemographic characteristics. Observed temporal preferences for DTC ordering can guide public health messaging around DTC testing programs.

RADx-UP Testing Core: Access to COVID-19 Diagnostics in Community-Engaged Research with Underserved Populations.

Research on the COVID-19 pandemic revealed a disproportionate burden of COVID-19 infection and death among underserved populations and exposed low rates of SARS-CoV-2 testing in these communities. A landmark National Institutes of Health (NIH) funding initiative, the Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) program, was developed to address the research gap in understanding the adoption of COVID-19 testing in underserved populations. This program is the single largest investment in health disparities and community-engaged research in the history of the NIH. The RADx-UP Testing Core (TC) provides community-based investigators with essential scientific expertise and guidance on COVID-19 diagnostics. This commentary describes the first 2 years of the TC's experience, highlighting the challenges faced and insights gained to safely and effectively deploy large-scale diagnostics for community-initiated research in underserved populations during a pandemic. The success of RADx-UP shows that community-based research to increase access and uptake of testing among underserved populations can be accomplished during a pandemic with tools, resources, and multidisciplinary expertise provided by a centralized testing-specific coordinating center. We developed adaptive tools to support individual testing strategies and frameworks for these diverse studies and ensured continuous monitoring of testing strategies and use of study data. In a rapidly evolving setting of tremendous uncertainty, the TC provided essential and real-time technical expertise to support safe, effective, and adaptive testing. The lessons learned go beyond this pandemic and can serve as a framework for rapid deployment of testing in response to future crises, especially when populations are affected inequitably.

Informatics tools to implement late cardiovascular risk prediction modeling for population management of high-risk childhood cancer survivors.

BACKGROUND: Clinical informatics tools to integrate data from multiple sources have the potential to catalyze population health management of childhood cancer survivors at high risk for late heart failure through the implementation of previously validated risk calculators. METHODS: The Oklahoma cohort (n = 365) harnessed data elements from Passport for Care (PFC), and the Duke cohort (n = 274) employed informatics methods to automatically extract chemotherapy exposures from electronic health record (EHR) data for survivors 18 years old and younger at diagnosis. The Childhood Cancer Survivor Study (CCSS) late cardiovascular risk calculator was implemented, and risk groups for heart failure were compared to the Children's Oncology Group (COG) and the International Guidelines Harmonization Group (IGHG) recommendations. Analysis within the Oklahoma cohort assessed disparities in guideline-adherent care. RESULTS: The Oklahoma and Duke cohorts both observed good overall concordance between the CCSS and COG risk groups for late heart failure, with weighted kappa statistics of .70 and .75, respectively. Low-risk groups showed excellent concordance (kappa > .9). Moderate and high-risk groups showed moderate concordance (kappa .44-.60). In the Oklahoma cohort, adolescents at diagnosis were significantly less likely to receive guideline-adherent echocardiogram surveillance compared with survivors younger than 13 years old at diagnosis (odds ratio [OD] 0.22; 95% confidence interval [CI]: 0.10-0.49). CONCLUSIONS: Clinical informatics tools represent a feasible approach to leverage discrete treatment-related data elements from PFC or the EHR to successfully implement previously validated late cardiovascular risk prediction models on a population health level. Concordance of CCSS, COG, and IGHG risk groups using real-world data informs current guidelines and identifies inequities in guideline-adherent care.

The Childhood Cancer Data Initiative: Using the Power of Data to Learn From and Improve Outcomes for Every Child and Young Adult With Pediatric Cancer.

Data-driven basic, translational, and clinical research has resulted in improved outcomes for children, adolescents, and young adults (AYAs) with pediatric cancers. However, challenges in sharing data between institutions, particularly in research, prevent addressing substantial unmet needs in children and AYA patients diagnosed with certain pediatric cancers. Systematically collecting and sharing data from every child and AYA can enable greater understanding of pediatric cancers, improve survivorship, and accelerate development of new and more effective therapies. To accomplish this goal, the Childhood Cancer Data Initiative (CCDI) was launched in 2019 at the National Cancer Institute. CCDI is a collaborative community endeavor supported by a 10-year, $50-million (in US dollars) annual federal investment. CCDI aims to learn from every patient diagnosed with a pediatric cancer by designing and building a data ecosystem that facilitates data collection, sharing, and analysis for researchers, clinicians, and patients across the cancer community. For example, CCDI's Molecular Characterization Initiative provides comprehensive clinical molecular characterization for children and AYAs with newly diagnosed cancers. Through these efforts, the CCDI strives to provide clinical benefit to patients and improvements in diagnosis and care through data-focused research support and to build expandable, sustainable data resources and workflows to advance research well past the planned 10 years of the initiative. Importantly, if CCDI demonstrates the success of this model for pediatric cancers, similar approaches can be applied to adults, transforming both clinical research and treatment to improve outcomes for all patients with cancer.

Adapting the Evidence Academy model for virtual stakeholder engagement in a national setting during the COVID-19 pandemic.

The COVID-19 pandemic raised the importance of adaptive capacity and preparedness when engaging historically marginalized populations in research and practice. The Rapid Acceleration of Diagnostics in Underserved Populations' COVID-19 Equity Evidence Academy Series (RADx-UP EA) is a virtual, national, interactive conference model designed to support and engage community-academic partnerships in a collaborative effort to improve practices that overcome disparities in SARS-CoV-2 testing and testing technologies. The RADx-UP EA promotes information sharing, critical reflection and discussion, and creation of translatable strategies for health equity. Staff and faculty from the RADx-UP Coordination and Data Collection Center developed three EA events with diverse geographic, racial, and ethnic representation of attendees from RADx-UP community-academic project teams: February 2021 (n = 319); November 2021 (n = 242); and September 2022 (n = 254). Each EA event included a data profile; 2-day, virtual event; event summary report; community dissemination product; and an evaluation strategy. Operational and translational delivery processes were iteratively adapted for each EA across one or more of five adaptive capacity domains: assets, knowledge and learning, social organization, flexibility, and innovation. The RADx-UP EA model can be generalized beyond RADx-UP and tailored by community and academic input to respond to local or national health emergencies.

Increasing access and uptake of SARS-CoV-2 at-home tests using a community-engaged approach.

Inequalities around COVID-19 testing and vaccination persist in the U.S. health system. We investigated whether a community-engaged approach could be used to distribute free, at-home, rapid SARS-CoV-2 tests to underserved populations. Between November 18-December 31, 2021, 400,000 tests were successfully distributed via 67 community partners and a mobile unit to a majority Hispanic/Latino/Spanish population in Merced County, California. Testing before gathering (59 %) was the most common testing reason. Asians versus Whites were more likely to test for COVID-19 if they had close contact with someone who may have been positive (odds ratio [OR] = 3.4, 95 % confidence interval [CI] = 1.7-6.7). Minors versus adults were more likely to test if they had close contact with someone who was confirmed positive (OR = 1.7, 95 % CI = 1.0-3.0), whereas Asian (OR = 4.1, 95 % CI = 1.2-13.7) and Hispanic/Latino/Spanish (OR = 2.5, 95 % CI = 1.0-6.6) versus White individuals were more likely to test if they had a positive household member. Asians versus Whites were more likely to receive a positive test result. Minors were less likely than adults to have been vaccinated (OR = 0.2, 95 % CI = 0.1-0.3). Among unvaccinated individuals, those who completed the survey in English versus Spanish indicated they were more likely to get vaccinated in the future (OR = 8.2, 95 % CI = 1.5-44.4). Asians versus Whites were less likely to prefer accessing oral COVID medications from a pharmacy/drug store only compared with a doctor's office or community setting (OR = 0.3, 95 % CI = 0.2-0.6). Study findings reinforce the need for replicable and scalable community-engaged strategies for reducing COVID-19 disparities by increasing SARS-CoV-2 test and vaccine access and uptake.

Use of a Digital Assistant to Report COVID-19 Rapid Antigen Self-test Results to Health Departments in 6 US Communities.

Importance: Widespread distribution of rapid antigen tests is integral to the US strategy to address COVID-19; however, it is estimated that few rapid antigen test results are reported to local departments of health. Objective: To characterize how often individuals in 6 communities throughout the United States used a digital assistant to log rapid antigen test results and report them to their local departments of health. Design, Setting, and Participants: This prospective cohort study is based on anonymously collected data from the beneficiaries of the Say Yes! Covid Test program, which distributed more than 3 000 000 rapid antigen tests at no cost to residents of 6 communities (Louisville, Kentucky; Indianapolis, Indiana; Fulton County, Georgia; O'ahu, Hawaii; Ann Arbor and Ypsilanti, Michigan; and Chattanooga, Tennessee) between April and October 2021. A descriptive evaluation of beneficiary use of a digital assistant for logging and reporting their rapid antigen test results was performed. Interventions: Widespread community distribution of rapid antigen tests. Main Outcomes and Measures: Number and proportion of tests logged and reported to the local department of health through the digital assistant. Results: A total of 313 000 test kits were distributed, including 178 785 test kits that were ordered using the digital assistant. Among all distributed kits, 14 398 households (4.6%) used the digital assistant, but beneficiaries reported three-quarters of their rapid antigen test results to their state public health departments (30 965 tests reported of 41 465 total test results [75.0%]). The reporting behavior varied by community and was significantly higher among communities that were incentivized for reporting test results vs those that were not incentivized or partially incentivized (90.5% [95% CI, 89.9%-91.2%] vs 70.5%; [95% CI, 70.0%-71.0%]). In all communities, positive tests were less frequently reported than negative tests (60.4% [95% CI, 58.1%-62.8%] vs 75.5% [95% CI, 75.1%-76.0%]). Conclusions and Relevance: These results suggest that application-based reporting with incentives may be associated with increased reporting of rapid tests for COVID-19. However, increasing the adoption of the digital assistant may be a critical first step.

Simulating Colorectal Cancer Trials Using Real-World Data.

PURPOSE: Using real-world data (RWD)-based trial simulation approach, we aim to simulate colorectal cancer (CRC) trials and examine both effectiveness and safety end points in different simulation scenarios. METHODS: We identified five phase III trials comparing new treatment regimens with an US Food and Drug Administration-approved first-line treatment in patients with metastatic CRC (ie, fluorouracil, leucovorin, and irinotecan) as the standard-of-care (SOC) control arm. Using Electronic Health Record-derived data from the OneFlorida network, we defined the study populations and outcome measures using the protocols from the original trials. Our design scenarios were (1) simulation of the SOC fluorouracil, leucovorin, and irinotecan arm and (2) comparative effectiveness research (CER) simulation of the control and experimental arms. For each scenario, we adjusted for random assignment, sampling, and dropout. We used overall survival (OS) and severe adverse events (SAEs) to measure effectiveness and safety. RESULTS: We conducted CER simulations for two trials, and SOC simulations for three trials. The effect sizes of our simulated trials were stable across all simulation runs. Compared with the original trials, we observed longer OS and higher mean number of SAEs in both CER and SOC simulation. In the two CER simulations, hazard ratios associated with death from simulations were similar to that reported in the original trials. Consistent with the original trials, we found higher risk ratios of SAEs in the experiment arm, suggesting potentially higher toxicities from the new treatment regimen. We also observed similar SAE rates across all simulations compared with the original trials. CONCLUSION: In this study, we simulated five CRC trials, and tested two simulation scenarios with several different configurations demonstrated that our simulations can robustly generate effectiveness and safety outcomes comparable with the original trials using real-world data.

Standardizing, harmonizing, and protecting data collection to broaden the impact of COVID-19 research: the rapid acceleration of diagnostics-underserved populations (RADx-UP) initiative.

OBJECTIVE: The Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) program is a consortium of community-engaged research projects with the goal of increasing access to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) tests in underserved populations. To accelerate clinical research, common data elements (CDEs) were selected and refined to standardize data collection and enhance cross-consortium analysis. MATERIALS AND METHODS: The RADx-UP consortium began with more than 700 CDEs from the National Institutes of Health (NIH) CDE Repository, Disaster Research Response (DR2) guidelines, and the PHENotypes and eXposures (PhenX) Toolkit. Following a review of initial CDEs, we made selections and further refinements through an iterative process that included live forums, consultations, and surveys completed by the first 69 RADx-UP projects. RESULTS: Following a multistep CDE development process, we decreased the number of CDEs, modified the question types, and changed the CDE wording. Most research projects were willing to collect and share demographic NIH Tier 1 CDEs, with the top exception reason being a lack of CDE applicability to the project. The NIH RADx-UP Tier 1 CDE with the lowest frequency of collection and sharing was sexual orientation. DISCUSSION: We engaged a wide range of projects and solicited bidirectional input to create CDEs. These RADx-UP CDEs could serve as the foundation for a patient-centered informatics architecture allowing the integration of disease-specific databases to support hypothesis-driven clinical research in underserved populations. CONCLUSION: A community-engaged approach using bidirectional feedback can lead to the better development and implementation of CDEs in underserved populations during public health emergencies.

If you build it, will they use it? Use of a Digital Assistant for Self-Reporting of COVID-19 Rapid Antigen Test Results during Large Nationwide Community Testing Initiative.

Importance: Wide-spread distribution of rapid-antigen tests is integral to the United States' strategy to address COVID-19; however, it is estimated that few rapid-antigen test results are reported to local departments of health. Objective: To characterize how often individuals in six communities throughout the United States used a digital assistant to log rapid-antigen test results and report them to their local Department of Health. Design: This prospective cohort study is based on anonymously collected data from the beneficiaries of The Say Yes! Covid Test program, which distributed 3,000,000 rapid antigen tests at no cost to residents of six communities between April and October 2021. We provide a descriptive evaluation of beneficiaries' use of digital assistant for logging and reporting their rapid antigen test results. Main Outcome and Measures: Number and proportion of tests logged and reported to the Department of Health through the digital assistant. Results: A total of 178,785 test kits were ordered by the digital assistant, and 14,398 households used the digital assistant to log 41,465 test results. Overall, a small proportion of beneficiaries used the digital assistant (8%), but over 75% of those who used it reported their rapid antigen test results to their state public health department. The reporting behavior varied between communities and was significantly different for communities that were incentivized for reporting test results (p < 0.001). In all communities, positive tests were less reported than negative tests (60.4% vs 75.5%; p<0.001). Conclusions and Relevance: These results indicate that app-based reporting with incentives may be an effective way to increase reporting of rapid tests for COVID-19; however, increasing the adoption of the digital assistant is a critical first step.

Association of Mass Distribution of Rapid Antigen Tests and SARS-CoV-2 Prevalence: Results from NIH-CDC funded Say Yes! Covid Test program in Michigan.

Importance: Wide-spread distribution of diagnostics is an integral part of the United States’ COVID-19 strategy; however, few studies have assessed the effectiveness of this intervention at reducing transmission of community COVID-19. Objective: To assess the impact of the Say Yes! Covid Test (SYCT!) Michigan program, a population-based program that distributed 20,000 free rapid antigen tests within Ann Arbor and Ypsilanti, Michigan in June-August 2021, on community prevalence of SARS-CoV-2. Design: This ecological study analyzed cases of SARS-CoV-2 from March to October 2021 reported to the Washtenaw County Health Department. Setting: Washtenaw County, Michigan. Participants: All residents of Washtenaw County. Interventions: Community-wide distribution of 500,000 rapid antigen tests for SARS-CoV-2 to residents of Ann Arbor and Ypsilanti, Michigan. Each household was limited to one test kit containing 25 rapid antigen tests. Main Outcome and Measures: Community prevalence of SARS-CoV-2, as measured through 7-day average cases, in Ann Arbor and Ypsilanti was compared to the rest of Washtenaw County. A generalized additive model was fitted with non-parametric trends for control and relative differences of trends in the pre-intervention, intervention, and post-intervention periods to compare intervention municipalities of Ann Arbor and Ypsilanti to the rest of Washtenaw County. Model results were used to calculate average cases prevented in the post-intervention period. Results: In the post-intervention period, there were significantly lower standardized average cases in the intervention communities of Ann Arbor/Ypsilanti compared to the rest of Washtenaw County (p<0.001). The estimated standardized relative difference between Ann Arbor/Ypsilanti and the rest of Washtenaw County was -0.016 cases per day (95% CI: -0.020 to -0.013), implying that the intervention prevented 40 average cases per day two months into the post-intervention period if trends were consistent. Conclusions and Relevance: Mass distribution of rapid antigen tests may be a useful mitigation strategy to combat community transmission of SARS-CoV-2, especially given the recent relaxation of social distancing and masking requirements.