Background Twitter has been used to track trends and disseminate health information during viral epidemics. On January 21, 2020, the CDC activated its Emergency Operations Center and the WHO released its first situation report about Coronavirus Disease 2019 (COVID-19), sparking significant media attention. How Twitter content and sentiment evolved in the early stages of the COVID-19 pandemic has not been described. Methods We extracted tweets matching hashtags related to COVID-19 from January 14th to 28th, 2020 using Twitter’s application programming interface. We measured themes and frequency of keywords related to infection prevention practices.  We performed a sentiment analysis to identify the sentiment polarity and predominant emotions in tweets and conducted topic modeling to identify and explore discussion topics over time. We compared sentiment, emotion, and topics among the most popular tweets, defined by the number of retweets. Results We evaluated 126,049 tweets from 53,196 unique users. The hourly number of COVID-19 related tweets starkly increased from January 21, 2020 onward. Nearly half (49.5%) of all tweets expressed fear and nearly 30% expressed surprise. In the full cohort, the economic and political impact of COVID-19 was the most commonly discussed topic. When focusing on the most retweeted tweets, the incidence of fear decreased and topics focused on quarantine efforts, the outbreak and its transmission, as well as prevention. Conclusion Twitter is a rich medium that can be leveraged to understand public sentiment in real-time and potentially target individualized public health messages based on user interest and emotion.

Background: Twitter has been used to track trends and disseminate health information during viral epidemics. On January 21, 2020, the CDC activated its Emergency Operations Center and the WHO released its first situation report about Coronavirus disease 2019 (COVID-19), sparking significant media attention. How Twitter content and sentiment has evolved in the early stages of any outbreak, including the COVID-19 epidemic, has not been described. Objective: To quantify and understand early changes in Twitter activity, content, and sentiment about the COVID-19 epidemic. Design: Observational study. Setting: Twitter platform. Participants: All Twitter users who created or sent a message from January 14th to 28th, 2020. Measurements: We extracted tweets matching hashtags related to COVID-19 and measured frequency of keywords related to infection prevention practices, vaccination, and racial prejudice. We performed a sentiment analysis to identify emotional valence and predominant emotions. We conducted topic modeling to identify and explore discussion topics over time. Results: We evaluated 126,049 tweets from 53,196 unique users. The hourly number of COVID-19-related tweets starkly increased from January 21, 2020 onward. Nearly half (49.5%) of all tweets expressed fear and nearly 30% expressed surprise. The frequency of racially charged tweets closely paralleled the number of newly diagnosed cases of COVID-19. The economic and political impact of the COVID-19 was the most commonly discussed topic, while public health risk and prevention were among the least discussed. Conclusion: Tweets with negative sentiment and emotion parallel the incidence of cases for the COVID-19 outbreak. Twitter is a rich medium that can be leveraged to understand public sentiment in real-time and target public health messages based on user interest and emotion. : medRxiv preprint their potential theme labels. The topics are ordered by frequency. Colors for each topic correspond to those in Figure 6b. Topic labels were assigned by the authors.

Background : The Affordable Care Act expanded Medicaid eligibility allowing low-income individuals greater access to healthcare. However, the uptake of state Medicaid expansion has been variable. It remains unclear how the Medicaid expansion was associated with the temporal trends in use of evidence-based cardiovascular drugs. Methods : We used the publicly available Medicaid Drug Utilization and Current Population Survey to extract filled prescription rates per 1000 Medicaid beneficiaries of statins, antihypertensives, P2Y12 inhibitors, and direct oral anticoagulants (DOAC). We defined expander states as those who expanded Medicaid on January 1, 2014, and non-expander states as those who had not expanded by December 31, 2018. Difference-in-differences (DID) analyses were performed to compare the association of the Medicaid expansion with per-capita cardiovascular drug prescription rates in expander versus non-expander states. Results : Between 2011 and 2018, the total number of prescriptions among all Medicaid beneficiaries increased, with gains of 89.7% in statins (11.0 to 20.8 million), 76% in antihypertensives (35.3 to 62.2 million), and 37% in P2Y12 inhibitors (1.7 to 2.3 million). Medicaid expansion was associated with significantly greater increases in quarterly prescriptions (per 1000 Medicaid beneficiaries) of statins [DID estimate (95% CI): 22.5 (16.5 to 28.6), P<0.001], antihypertensives [DID estimate (95% CI): 63.2 (47.3 to 79.1), P<0.001], and P2Y12 inhibitors [DID estimate (95% CI): 1.7 (1.2 to 2.2), P<0.001]. Between 2013 and 2018, more than 75% of the expander states had increases in prescription rates of both statins and antihypertensives. In contrast, 44% of non-expander states saw declines in statins and antihypertensives. The Medicaid expansion was not associated with higher DOAC prescription rates [DID estimate (95% CI) 0.9 [-0.3 to 2.1], P=0.142). Conclusions : The 2014 Medicaid expansion was associated with a significant increase in per-capita utilization of cardiovascular prescription drugs among Medicaid beneficiaries. These gains in utilization may contribute to long-term cardiovascular benefits to lower-income and previously underinsured populations.

Despite the rapid growth of academic hospital medicine, scholarly productivity remains poorly characterized. In this cross-sectional study, distribution of academic rank and scholarly output of academic hospital medicine faculty are described. We extracted data for 1,554 hospitalists on faculty at the top 25 internal medicine residency programs. Only 11.7% of faculty had reached associate (9.0%) or full professor (2.7%). The median number of publications was 0.0 (interquartile range [IQR], 0.0-4.0), with 51.4% without a single publication. Faculty 6 to 10 years post residency had a median of 1.0 (IQR, 0.0-4.0) publication, with 46.8% of these faculty without a publication. Among men, 54.3% had published at least one manuscript, compared to 42.7% of women (P < .0001). Predictors of promotion included H-index, number of years post residency graduation, completion of chief residency, and graduation from a top 25 medical school. Promotion remains uncommon in academic hospital medicine, which may be partially due to low rates of scholarly productivity.