Partisan Differences in Legislators' Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis.

BACKGROUND: The COVID-19 era has been characterized by the politicization of health-related topics. This is especially concerning given evidence that politicized discussion of vaccination may contribute to vaccine hesitancy. No research, however, has examined the content and politicization of legislator communication with the public about vaccination during the COVID-19 era. OBJECTIVE: The aim of this study was to examine vaccine-related tweets produced by state and federal legislators during the COVID-19 era to (1) describe the content of vaccine-related tweets; (2) examine the differences in vaccine-related tweet content between Democrats and Republicans; and (3) quantify (and describe trends over time in) partisan differences in vaccine-related communication. METHODS: We abstracted all vaccine-related tweets produced by state and federal legislators between February 01, 2020, and December 11, 2020. We used latent Dirichlet allocation to define the tweet topics and used descriptive statistics to describe differences by party in the use of topics and changes in political polarization over time. RESULTS: We included 14,519 tweets generated by 1463 state legislators and 521 federal legislators. Republicans were more likely to use words (eg, "record time," "launched," and "innovation") and topics (eg, Operation Warp Speed success) that were focused on the successful development of a SARS-CoV-2 vaccine. Democrats used a broader range of words (eg, "anti-vaxxers," "flu," and "free") and topics (eg, vaccine prioritization, influenza, and antivaxxers) that were more aligned with public health messaging related to the vaccine. Polarization increased over most of the study period. CONCLUSIONS: Republican and Democratic legislators used different language in their Twitter conversations about vaccination during the COVID-19 era, leading to increased political polarization of vaccine-related tweets. These communication patterns have the potential to contribute to vaccine hesitancy.

Increasing Short- and Long-Term Buprenorphine Treatment Capacity: Providing Waiver Training for Medical Students.

In the face of an ongoing opioid crisis in the United States, persistent treatment gaps exist for vulnerable populations. Among the 3 Food and Drug Administration-approved medications used to treat opioid use disorder, many patients prefer buprenorphine. But physicians are currently required to register with the Drug Enforcement Administration and complete 8 hours of qualifying training before they can receive a waiver to prescribe buprenorphine to their patients. In this article, the authors summarize the evolution of buprenorphine waiver training in undergraduate medical education and outline 2 potential paths to increase buprenorphine treatment capacity going forward: the curriculum change approach and the training module approach. As part of the 2018 Substance Use-Disorder Prevention that Promotes Opioid Recovery and Treatment for Patients and Communities Act, the Substance Abuse and Mental Health Services Administration has provided funding for medical schools to adapt their curricula to meet waiver training requirements. To date, however, only one school has had its curriculum approved for this purpose. Additionally, recent political efforts have been directed at eliminating aspects of the waiver training requirement and creating a more direct path to integrating waiver qualification into undergraduate medical education (UME). Other medical schools have adopted a more pragmatic approach involving the integration of existing online, in-person, and hybrid waiver-qualifying training modules into the curricula, generally for fourth-year students. This training module approach can be more rapidly, broadly, and cost-effectively implemented than the curriculum change approach. It can also be easily integrated into the online medical curricula that schools developed in response to the COVID-19 pandemic. Ultimately both curricular changes and support for student completion of existing training modules should be pursued in concert, but focus should not be single-mindedly on the former at the expense of the latter.

Association Between Crowdsourced Health Care Facility Ratings and Mortality in US Counties.

Importance: Mortality across US counties varies considerably, from 252 to 1847 deaths per 100 000 people in 2018. Although patient satisfaction with health care is associated with patient- and facility-level health outcomes, the association between health care satisfaction and community-level health outcomes is not known. Objective: To examine the association between online ratings of health care facilities and mortality across US counties and to identify language specific to 1-star (lowest rating) and 5-star (highest rating) reviews in counties with high vs low mortality. Design, Setting, and Participants: This retrospective population-based cross-sectional study examined reviews and ratings of 95 120 essential health care facilities across 1301 US counties. Counties that had at least 1 essential health care facility with reviews available on Yelp, an online review platform, were included. Essential health care was defined according to the 10 essential health benefits covered by Affordable Care Act insurance plans. Main Outcomes and Measures: The mean rating of essential health care facilities was calculated by county from January 1, 2015, to December 31, 2019. Ratings were on a scale of 1 to 5 stars, with 1 being the worst rating and 5 the best. County-level composite measures of health behaviors, clinical care, social and economic factors, and physical environment were obtained from the University of Wisconsin School of Medicine and Public Health County Health Rankings database. The 2018 age-adjusted mortality by county was obtained from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiological Research database. Multiple linear regression analysis was used to estimate the association between mean facility rating and mortality, adjusting for county health ranking variables. Words with frequencies of use that were significantly different across 1-star and 5-star reviews in counties with high vs low mortality were identified. Results: The 95 120 facilities meeting inclusion criteria were distributed across 1301 of 3142 US counties (41.4%). At the county level, a 1-point increase in mean rating was associated with a mean (SE) age-adjusted decrease of 18.05 (3.68) deaths per 100 000 people (P < .001). Words specific to 1-star reviews in high-mortality counties included told, rude, and wait, and words specific to 5-star reviews in low-mortality counties included Dr, pain, and professional. Conclusions and Relevance: This study found that, at the county level, higher online ratings of essential health care facilities were associated with lower mortality. Equivalent online ratings did not necessarily reflect equivalent experiences of care across counties with different mortality levels, as evidenced by variations in the frequency of use of key words in reviews. These findings suggest that online ratings and reviews may provide insight into unequal experiences of essential health care.

Online Reviews of Mental Health Treatment Facilities: Narrative Themes Associated With Positive and Negative Ratings.

OBJECTIVE: Previous studies indicate that patients' satisfaction with mental health care is correlated with both treatment outcomes and quality of life. The aims of this study were to describe online reviews of mental health treatment facilities, including key themes in review content, and to evaluate the correlation between narrative review themes, facility characteristics, and review ratings. METHODS: United States National Mental Health Services Survey (N-MHSS) facilities were linked to corresponding Yelp pages, created between March 2007 and September 2019. Correlations between review ratings and both machine learning-generated latent Dirichlet allocation topics and N-MHSS-reported facility characteristics were measured by using Spearman's rank-order correlation coefficient. Significance was defined by a Bonferroni-adjusted p<0.001. RESULTS: Of 10,191 unique mental health treatment facilities, 1,383 (13.6%) had relevant Yelp pages with 8,133 corresponding reviews. The number of newly reviewed facilities and the number of new reviews increased throughout the study period. Narrative topics positively correlated with review ratings included caring staff (Spearman's ρ=0.39) and nonpharmacologic treatment (ρ=0.16). Topics negatively correlated with review ratings included rude staff (ρ=-0.14) and safety and abuse (ρ=-0.14). Of 126 N-MHSS survey items, 11 were positively correlated with review rating, including "outpatient mental health facility" (ρ=0.13), and 33 were negatively correlated with review rating, including accepting Medicare (ρ=-0.21). CONCLUSIONS: Narrative topics provide information beyond what is currently collected through the N-MHSS. Topics associated with positive and negative reviews, such as staff attitude toward patients, can guide improvement in patients' satisfaction and engagement with mental health care.

Who is Biking for? Urban Bikeshare Networks' Responses to the COVID-19 Pandemic, Disparities in Bikeshare Access, and a Way Forward.

Black, Latinx, and Indigenous people have contracted the SARS-CoV-2 virus and died of COVID-19 at higher rates than White people. Individuals rated public transit, taxis, and ride-hailing as the modes of transportation putting them at greatest risk of COVID-19 infection. Cycling may thus be an attractive alternative for commuting. Amid the increase in bikeshare usage during the early months of the pandemic, bikeshare companies made changes to membership requirements to increase accessibility, targeting especially essential workers. Essential workers in the United States are disproportionately Black and Latinx, underpaid, and reliant on public transit to commute to work. We document changes made by bikeshare companies, including benefits to various groups of essential workers, and we discuss such changes in the context of longstanding racial disparities in bikeshare access. While well intended, the arbitrary delineation in eligibility for such benefits by class of essential workers unwittingly curtailed access for many who may have benefited most. Given that equity in bikeshare is an important tool to improve access to safe transportation, critical changes in the distribution, accessibility, and usability of bikeshare networks is essential. Bikeshare companies, city planners, and policy makers should collaborate with community-based bike advocates to implement changes, as vocalized by those most in need of alternative forms of transportation.

State Legislators' Divergent Social Media Response to the Opioid Epidemic from 2014 to 2019: Longitudinal Topic Modeling Analysis.

BACKGROUND: The opioid epidemic is widely recognized as a legislative priority, but there is substantial variation in state adoption of evidence-based policy. State legislators' use of social media to disseminate information and to indicate support for specific initiatives continues to grow and may reflect legislators' openness to opioid-related policy change. OBJECTIVE: We sought to identify changes in the national dialogue regarding the opioid epidemic among Democratic and Republican state legislators and to estimate changing partisanship around understanding and addressing the epidemic over time. DESIGN: Longitudinal natural language processing analysis. PARTICIPANTS: A total of 4083 US state legislators in office between 2014 and 2019 with any opioid-related social media posts. MAIN MEASURES: Association between opioid-related post volume and state overdose mortality, as measured by Kendall's rank correlation coefficient. Latent Dirichlet allocation analysis of all social media posts to identify key opioid-related topics. Longitudinal analysis of differences in the prevalence of key topics among Democrats and Republicans over time. KEY RESULTS: In total, 43,558 social media posts met inclusion criteria, with the vast majority to Twitter (n=28,564; 65.6%) or Facebook (n=14,283; 32.8%). Posts were more likely to mention fentanyl and less likely to mention heroin over time. The volume of opioid-related content was positively associated with state-level unintentional overdose mortality among both Democrats (tau=0.42, P<.001) and Republicans (tau=0.39, P<.001). Democrats' social media content has increasingly spoken to holding pharmaceutical companies accountable, while Republicans' social media content has increasingly spoken to curbing illicit drug trade. Overall, partisanship across topics increased from 2016 to 2019. CONCLUSION: The volume of opioid-related social media posts by US state legislators between 2014 and 2019 is associated with state-level overdose mortality, but the content across parties is significantly different. Democrats' and Republicans' social media posts may reflect growing partisanship regarding how best to address the overdose epidemic.

Author Correction: Variability in Language used on Social Media Prior to Hospital Visits.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Variability in Language used on Social Media prior to Hospital Visits.

Forecasting healthcare utilization has the potential to anticipate care needs, either accelerating needed care or redirecting patients toward care most appropriate to their needs. While prior research has utilized clinical information to forecast readmissions, analyzing digital footprints from social media can inform our understanding of individuals' behaviors, thoughts, and motivations preceding a healthcare visit. We evaluate how language patterns on social media change prior to emergency department (ED) visits and inpatient hospital admissions in this case-crossover study of adult patients visiting a large urban academic hospital system who consented to share access to their history of Facebook statuses and electronic medical records. An ensemble machine learning model forecasted ED visits and inpatient admissions with out-of-sample cross-validated AUCs of 0.64 and 0.70 respectively. Prior to an ED visit, there was a significant increase in depressed language (Cohen's d = 0.238), and a decrease in informal language (d = 0.345). Facebook posts prior to an inpatient admission showed significant increase in expressions of somatic pain (d = 0.267) and decrease in extraverted/social language (d = 0.357). These results are a first step in developing methods to utilize user-generated content to characterize patient care-seeking context which could ultimately enable better allocation of resources and potentially early interventions to reduce unplanned visits.

Recognizing Racism in Medicine: A Student-Organized and Community-Engaged Health Professional Conference.

Purpose: This piece details the evaluation and implementation of a student-led educational intervention designed to train health professionals on the impact of racism in health care and provide tools to mitigate it. In addition, this conference, cosponsored by medical, nursing, and social work training programs, facilitates development of networks of providers with the knowledge and skills to recognize and address racism in health care. Methods: The conference included 2 keynote speakers, an interprofessional panel, and 15 workshops. Participants (n=220) were asked to complete a survey assessing perceptions of conference content and impact. We compared responses pre- and postconference using Wilcoxon signed-rank tests. Results: Of the survey respondents (n=44), 45.5% were medical students, 13.6% nursing students, and 9% social work students; 65.9% self-identified as a race/ethnicity other than non-Hispanic white; and 63.6% self-identified as female. We found that 47.7% respondents reported they were more comfortable discussing how racism affects health (p<0.001), 36.4% had better understanding of the impact of racism on an individual's health (p<0.001), and 54.5% felt more connected to other health professionals working to recognize and address racism in medicine (p<0.001). Conclusion: These findings suggest that a student-organized conference could potentially be an effective strategy in addressing a critical gap in racism training for health care professionals.