Research Compensation and Enhanced Contacts in Studies With Persons Who Use Drugs: Lessons From the COVID-19 Pandemic Demand a Reset.

Policy changes resulting from the coronavirus 2019 (COVID-19) pandemic have had a substantial and positive impact on the clinical care of persons with opioid use disorder. These innovative paradigm shifts created a ripe environment for re-evaluating traditional approaches to recruiting and retaining persons who use drugs into research studies. For example, changes to methadone prescribing requirements and authorization of buprenorphine prescriptions via telehealth have both increased access to medications. In this commentary, we contribute to ongoing conversations about the ethics of compensation for participants in addiction-related clinical research and share methods of payment that proved successful in research performed during the pandemic. We also discuss approaches to enrollment and follow-up that were implemented during the height of COVID restrictions. These approaches may mutually benefit both participants and researchers in a post-pandemic era.

At the intersection of trust and mistrust: A qualitative analysis of motivators and barriers to research participation at a safety-net hospital.

INTRODUCTION: The underrepresentation of Black, Indigenous, and People of Color (BIPOC) individuals in healthcare research limits generalizability and contributes to healthcare inequities. Existing barriers and attitudes toward research participation must be addressed to increase the representation of safety net and other underserved populations. METHODS: We conducted semi-structured qualitative interviews with patients at an urban safety net hospital, focusing on facilitators, barriers, motivators, and preferences for research participation. We conducted direct content analysis guided by an implementation framework and used rapid analysis methods to generate final themes. RESULTS: We completed 38 interviews and identified six major themes related to preferences for engagement in research participation: (1) wide variation in research recruitment preferences; (2) logistical complexity negatively impacts willingness to participate; (3) risk contributes to hesitation toward research participation; (4) personal/community benefit, interest in study topic, and compensation serve as motivators for research participation; (5) continued participation despite reported shortcomings of informed consent process; and (6) mistrust could be overcome by relationship or credibility of information sources. CONCLUSION: Despite barriers to participation in research studies among safety-net populations, there are also facilitators that can be implemented to increase knowledge and comprehension, ease of participation, and willingness to join research studies. Study teams should vary recruitment and participation methods to ensure equal access to research opportunities. PATIENT/PUBLIC CONTRIBUTION: Our analysis methods and study progress were presented to individuals within the Boston Medical Center healthcare system. Through this process community engagement specialists, clinical experts, research directors, and others with significant experience working with safety-net populations supported data interpretation and provided recommendations for action following the dissemination of data.

"Community members have more impact on their neighbors than celebrities": leveraging community partnerships to build COVID-19 vaccine confidence.

BACKGROUND: Vaccines are a strong public health tool to protect against severe disease, hospitalization, and death from COVID-19. Still, inequities in COVID-19 vaccination rates and health outcomes continue to exist among Black and Latino populations. Boston Medical Center (BMC) has played a significant role in vaccinating medically underserved populations, and organized a series of community-engaged conversations to better understand community concerns regarding the COVID-19 vaccine. This paper describes the themes which resulted from these community-engaged conversations and proposes next steps for healthcare leaders. METHODS: We accessed nine publicly available recordings of the community-engaged conversations which were held between March 2021 and September 2021 and ranged from 8 to 122 attendees. Six conversations prioritized specific groups: the Haitian-Creole community, the Cape Verdean community, the Latino community, the Black Christian Faith community, guardians who care for children living with disabilities, and individuals affected by systemic lupus erythematosus. Remaining conversations targeted the general public of the Greater Boston Area. We employed a Consolidated Framework for Implementation Research-driven codebook to code our data. Our analysis utilized a modified version of qualitative rapid analysis methods. RESULTS: Five main themes emerged from these community-engaged conversations: (1) Structural factors are important barriers to COVID-19 vaccination; (2) Mistrust exists due to the negative impact of systemic oppression and perceived motivation of the government; (3) There is a desire to learn more about biological and clinical characteristics of the COVID-19 vaccine as well as the practical implications of being vaccinated; (4) Community leaders emphasize community engagement for delivering COVID-19 information and education and; (5) Community leaders believe that the COVID-19 vaccine is a solution to address the pandemic. CONCLUSION: This study illustrates a need for community-engaged COVID-19 vaccine messaging which reflects the nuances of the COVID-19 vaccine and pandemic without oversimplifying information. In highlighting common concerns of the Greater Boston Area which contribute to a lack of confidence in the COVID-19 vaccine, we underscore important considerations for public health and healthcare leadership in the development of initiatives which work to advance health equity.

Comparing COVID-19-related Morbidity and Mortality Between Patients With and Without Substance Use Disorders: A Retrospective Cohort Study.

Objectives: People with substance use disorders (SUD) are suggested to have higher risk of hospitalization, intubation, or death from coronavirus disease 2019 (COVID-19), although data are mixed. Little is known about other COVID-19-related complications in this group. We compared morbidity and mortality among individuals with and without SUD who were admitted to an urban safety net hospital with COVID-19 early in the pandemic, contemporaneous to other published studies on this subject. Methods: We performed a retrospective study of patients ⩾18 years old admitted with COVID-19 from March 16th to April 8th, 2020. SUD included alcohol, opioid, cocaine, amphetamine, and benzodiazepine use disorders and was identified using diagnostic codes, free text clinical documentation, and urine drug screens. The primary outcome was inpatient mortality. Secondary outcomes included clinical complications (eg, secondary infections, venous thromboembolism) and resource utilization (eg, mechanical ventilation, length of stay). We used multivariable regression to assess the relationship between SUD and mortality. Results: Of 409 patients, the mean age was 56 years and 13.7% had SUD. Those with SUD were more likely to be male, have experienced homelessness, have pulmonary disease or hepatitis C, or use tobacco or cannabis. After multivariable analysis, SUD was not associated with mortality (aOR 1.03; 95% CI, 0.31-3.10). Secondary outcomes were also similar between groups. Conclusions: Our findings suggest that persons with and without SUD have similar COVID-19-related outcomes. Previously reported increased COVID-19 complications may be from medical comorbidities.

Inequities in COVID-19 vaccine and booster coverage across Massachusetts ZIP codes after the emergence of Omicron: A population-based cross-sectional study.

BACKGROUND: Inequities in Coronavirus Disease 2019 (COVID-19) vaccine and booster coverage may contribute to future disparities in morbidity and mortality within and between Massachusetts (MA) communities. METHODS AND FINDINGS: We conducted a population-based cross-sectional study of primary series vaccination and booster coverage 18 months into the general population vaccine rollout. We obtained public-use data on residents vaccinated and boosted by ZIP code (and by age group: 5 to 19, 20 to 39, 40 to 64, 65+) from MA Department of Public Health, as of October 10, 2022. We constructed population denominators for postal ZIP codes by aggregating census tract population estimates from the 2015-2019 American Community Survey. We excluded nonresidential ZIP codes and the smallest ZIP codes containing 1% of the state's population. We mapped variation in ZIP code-level primary series vaccine and booster coverage and used regression models to evaluate the association of these measures with ZIP code-level socioeconomic and demographic characteristics. Because age is strongly associated with COVID-19 severity and vaccine access/uptake, we assessed whether observed socioeconomic and racial/ethnic inequities persisted after adjusting for age composition and plotted age-specific vaccine and booster coverage by deciles of ZIP code characteristics. We analyzed data on 418 ZIP codes. We observed wide geographic variation in primary series vaccination and booster rates, with marked inequities by ZIP code-level education, median household income, essential worker share, and racial/ethnic composition. In age-stratified analyses, primary series vaccine coverage was very high among the elderly. However, we found large inequities in vaccination rates among younger adults and children, and very large inequities in booster rates for all age groups. In multivariable regression models, each 10 percentage point increase in "percent college educated" was associated with a 5.1 (95% confidence interval (CI) 3.9 to 6.3, p < 0.001) percentage point increase in primary series vaccine coverage and a 5.4 (95% CI 4.5 to 6.4, p < 0.001) percentage point increase in booster coverage. Although ZIP codes with higher "percent Black/Latino/Indigenous" and higher "percent essential workers" had lower vaccine coverage (-0.8, 95% CI -1.3 to -0.3, p < 0.01; -5.5, 95% CI -7.3 to -3.8, p < 0.001), these associations became strongly positive after adjusting for age and education (1.9, 95% CI 1.0 to 2.8, p < 0.001; 4.8, 95% CI 2.6 to 7.1, p < 0.001), consistent with high demand for vaccines among Black/Latino/Indigenous and essential worker populations within age and education groups. Strong positive associations between "median household income" and vaccination were attenuated after adjusting for age. Limitations of the study include imprecision of the estimated population denominators, lack of individual-level sociodemographic data, and potential for residential ZIP code misreporting in vaccination data. CONCLUSIONS: Eighteen months into MA's general population vaccine rollout, there remained large inequities in COVID-19 primary series vaccine and booster coverage across MA ZIP codes, particularly among younger age groups. Disparities in vaccination coverage by racial/ethnic composition were statistically explained by differences in age and education levels, which may mediate the effects of structural racism on vaccine uptake. Efforts to increase booster coverage are needed to limit future socioeconomic and racial/ethnic disparities in COVID-19 morbidity and mortality.

Laboratory test trends within 72 hours of hospital admission associated with death among COVID-19 patients.

Early identification of patients at risk for severe coronavirus disease 2019 (COVID-19) is crucial for appropriate triage and determination of need for closer monitoring. Few studies have examined laboratory trends in COVID-19 infection and sought to quantify the degree to which laboratory values affect mortality. We conducted a retrospective cohort (n = 407) study of hospitalized patients with COVID-19 early in the course of the pandemic, from March 16th to April 8th, 2020 and compared baseline to repeat laboratory testing 72 hours into admission. The primary outcome was death. We found that rises of 25 mg/L C-reactive protein, 50 units/L lactate dehydrogenase, and 100 ng/mL ferritin were associated with 23%, 28%, and 1% increased odds of death, respectively. In contrast, changes in fibrinogen, D-dimer, white blood cell count, and creatinine in the first few days of hospital admission were not associated with mortality. These quantitative findings may assist clinicians in determining the risk of potential clinical decline in patients with COVID-19 and influence early management.

Addressing Inequities in SARS-CoV-2 Vaccine Uptake: The Boston Medical Center Health System Experience.

Academic medical centers could play an important role in increasing access to and uptake of SARS-CoV-2 vaccines, especially in Black and Latino communities that have been disproportionately affected by the pandemic. This article describes the vaccination program developed by the Boston Medical Center (BMC) health system (New England's largest safety-net health system), its affiliated community health centers (CHCs), and community partners. The program was based on a conceptual framework for community interventions and aimed to increase equitable access to vaccination in the hardest-hit communities through community-based sites in churches and community centers, mobile vaccination events, and vaccination on the BMC campus. Key strategies included a communication campaign featuring trusted messengers, a focus on health equity, established partnerships with community leaders and CHCs, and strong collaboration with local health departments and the Commonwealth of Massachusetts to ensure equitable allocation of the vaccine supply. Process factors involved the use of robust analytics relying on the Centers for Disease Control and Prevention's Social Vulnerability Index (SVI). The vaccination program administered 109 938 first doses, with 94 703 (86%) given at community sites and 2466 (2%) given at mobile sites. Mobile vaccination events were key in reaching younger people living in locations with the highest SVIs. Challenges included the need for a robust operational infrastructure and mistrust of the health system given the long history of economic disinvestment in the surrounding community. The BMC model could serve as a blueprint for other medical centers interested in implementing programs aimed at increasing vaccine uptake during a pandemic and in developing an infrastructure to address other health-related disparities.

Factors associated with inpatient complications among patients with obesity and COVID-19 at an urban safety-net hospital: A retrospective cohort study.

Objective: Obesity increases morbidity and mortality from Coronavirus disease 2019 (COVID-19). This study characterized inpatient complications among patients with obesity and COVID-19-including myocardial infarction, renal failure requiring dialysis, stroke, secondary bacterial infection, and venous thromboembolism-and identified factors associated with developing at least one inpatient complication at a safety-net hospital with a diverse cohort. Methods: A retrospective review was performed of all patients admitted for ≥3 days with COVID-19 between 16 March 2020, and 8 April 2020. Logistic regression identified factors associated with developing at least one COVID-19-related complication among patients with obesity (body mass index ≥30 kg/m2). Results: 374 patients were included; 53.7% were classified as having obesity, 43.9% identified as Black, and 38.5% identified as Latino or Hispanic. Obesity was not associated with having at least one inpatient complication on multivariable analysis, but increased age (aOR 1.02, [95% CI 1.01-1.04], p = 0.010) and obstructive sleep apnea (aOR 2.25, [1.08-4.85], p = 0.034) were associated with this outcome. Conclusions: Obesity was not associated with specified inpatient complications among patients with COVID-19 admitted to a health system caring for diverse patients. Future studies should incorporate larger cohorts and reflect newer treatment protocols.

Development and validation of predictive models for COVID-19 outcomes in a safety-net hospital population.

OBJECTIVE: To develop predictive models of coronavirus disease 2019 (COVID-19) outcomes, elucidate the influence of socioeconomic factors, and assess algorithmic racial fairness using a racially diverse patient population with high social needs. MATERIALS AND METHODS: Data included 7,102 patients with positive (RT-PCR) severe acute respiratory syndrome coronavirus 2 test at a safety-net system in Massachusetts. Linear and nonlinear classification methods were applied. A score based on a recurrent neural network and a transformer architecture was developed to capture the dynamic evolution of vital signs. Combined with patient characteristics, clinical variables, and hospital occupancy measures, this dynamic vital score was used to train predictive models. RESULTS: Hospitalizations can be predicted with an area under the receiver-operating characteristic curve (AUC) of 92% using symptoms, hospital occupancy, and patient characteristics, including social determinants of health. Parsimonious models to predict intensive care, mechanical ventilation, and mortality that used the most recent labs and vitals exhibited AUCs of 92.7%, 91.2%, and 94%, respectively. Early predictive models, using labs and vital signs closer to admission had AUCs of 81.1%, 84.9%, and 92%, respectively. DISCUSSION: The most accurate models exhibit racial bias, being more likely to falsely predict that Black patients will be hospitalized. Models that are only based on the dynamic vital score exhibited accuracies close to the best parsimonious models, although the latter also used laboratories. CONCLUSIONS: This large study demonstrates that COVID-19 severity may accurately be predicted using a score that accounts for the dynamic evolution of vital signs. Further, race, social determinants of health, and hospital occupancy play an important role.

Long COVID and Health Inequities: The Role of Primary Care.

Policy Points An estimated 700,000 people in the United States have "long COVID," that is, symptoms of COVID-19 persisting beyond three weeks. COVID-19 and its long-term sequelae are strongly influenced by social determinants such as poverty and by structural inequalities such as racism and discrimination. Primary care providers are in a unique position to provide and coordinate care for vulnerable patients with long COVID. Policy measures should include strengthening primary care, optimizing data quality, and addressing the multiple nested domains of inequity.

The Effect of IL-6 Inhibitors on Mortality Among Hospitalized COVID-19 Patients: A Multicenter Study.

BACKGROUND: The effectiveness of interleukin-6 inhibitors (IL-6i) in ameliorating coronavirus disease 2019 (COVID-19) remains uncertain. METHODS: We analyzed data for patients aged ≥18 years admitted with a positive severe acute respiratory syndrome coronavirus 2 polymerase chain reaction test at 4 safety-net hospital systems with diverse populations and high rates of medical comorbidities in 3 US regions. We used inverse probability of treatment weighting via machine learning for confounding adjustment by demographics, comorbidities, and disease severity markers. We estimated the average treatment effect, the odds of IL-6i effect on in-hospital mortality from COVID-19, using a logistic marginal structural model. RESULTS: Of 516 patients, 104 (20.1%) received IL-6i. Estimate of the average treatment effect adjusted for confounders suggested a 37% reduction in odds of in-hospital mortality in those who received IL-6i compared with those who did not, although the confidence interval included the null value of 1 (odds ratio = 0.63; 95% confidence interval, .29-1.38). A sensitivity analysis suggested that potential unmeasured confounding would require a minimum odds ratio of 2.55 to nullify our estimated IL-6i effect size. CONCLUSIONS: Despite low precision, our findings suggested a relatively large effect size of IL-6i in reducing the odds of COVID-19-related in-hospital mortality.

Early administration of interleukin-6 inhibitors for patients with severe COVID-19 disease is associated with decreased intubation, reduced mortality, and increased discharge.

OBJECTIVE: The aim of this observational study was to determine the optimal timing of interleukin-6 receptor inhibitor (IL6ri) administration for coronavirus disease 2019 (COVID-19). METHODS: Patients with COVID-19 were given an IL6ri (sarilumab or tocilizumab) based on iteratively reviewed guidelines. IL6ri were initially reserved for critically ill patients, but after review, treatment was liberalized to patients with lower oxygen requirements. Patients were divided into two groups: those requiring ≤45% fraction of inspired oxygen (FiO2) (termed stage IIB) and those requiring >45% FiO2 (termed stage III) at the time of IL6ri administration. The main outcomes were all-cause mortality, discharge alive from hospital, and extubation. RESULTS: A total of 255 COVID-19 patients were treated with IL6ri (149 stage IIB and 106 stage III). Patients treated in stage IIB had lower mortality than those treated in stage III (adjusted hazard ratio (aHR) 0.24, 95% confidence interval (CI) 0.08-0.74). Overall, 218 (85.5%) patients were discharged alive. Patients treated in stage IIB were more likely to be discharged (aHR 1.43, 95% CI 1.06-1.93) and were less likely to be intubated (aHR 0.43, 95% CI 0.24-0.79). CONCLUSIONS: IL6ri administration prior to >45% FiO2 requirement was associated with improved COVID-19 outcomes. This can guide clinical management pending results from randomized controlled trials.