Do digital technologies reduce racially biased reporting? Evidence from NYPD administrative data.

Recent work has emphasized the disproportionate bias faced by minorities when interacting with law enforcement. However, research on the topic has been hampered by biased sampling in administrative data, namely that records of police interactions with citizens only reflect information on the civilians that police elect to investigate, and not civilians that police observe but do not investigate. In this work, we address a related bias in administrative police data which has received less empirical attention, namely reporting biases around investigations that have taken place. Further, we investigate whether digital monitoring tools help mitigate this reporting bias. To do so, we examine changes in reports of interactions between law enforcement and citizens in the wake of the New York City Police Department's replacement of analog memo books with mobile smartphones. Results from a staggered difference in differences estimation indicate a significant increase in reports of citizen stops once the new smartphones are deployed. Importantly, we observe that the rise is driven by increased reports of "unproductive" stops, stops involving non-White citizens, and stops occurring in areas characterized by a greater concentration of crime and non-White residents. These results reinforce the recent observation that prior work has likely underestimated the extent of racial bias in policing. Further, they highlight that the implementation of digital monitoring tools can mitigate the issue to some extent.

Patient access to chronic medications during the Covid-19 pandemic: Evidence from a comprehensive dataset of US insurance claims.

Patient access and adherence to chronic medications is critical. In this work, we evaluate whether disruptions related to Covid-19 have affected new and existing patients' access to pharmacological therapies without interruption. We do so by performing a retrospective analysis on a dataset of 9.4 billion US prescription drug claims from 252 million patients from May, 2019 through August, 2020 (about 93% of prescriptions dispensed within those months). Using fixed effect (conditional likelihood) linear models, we evaluate continuity of care, how many days of supply patients received, and the likelihood of discontinuing therapy for drugs from classes with significant population health impacts. Findings indicate that more prescriptions were filled in March 2020 than in any prior month, followed by a significant drop in monthly dispensing. Compared to the pre-Covid era, a patient's likelihood of discontinuing some medications increased after the spread of Covid: norgestrel-ethinyl estradiol (hormonal contraceptive) discontinuation increased 0.62% (95% CI: 0.59% to 0.65%, p<0.001); dexmethylphenidate HCL (ADHD stimulant treatment) discontinuation increased 2.84% (95% CI: 2.79% to 2.89%, p<0.001); escitalopram oxalate (SSRI antidepressant) discontinuation increased 0.57% (95% CI: 0.561% to 0.578%, p<0.001); and haloperidol (antipsychotic) discontinuation increased 1.49% (95% CI: 1.41% to 1.57%, p<0.001). In contrast, the likelihood of discontinuing tacrolimus (immunosuppressant) decreased 0.15% (95% CI: 0.12% to 0.19%, p<0.001). The likelihood of discontinuing buprenorphine/naloxone (opioid addiction therapy) decreased 0.59% (95% CI: 0.55% to 0.62% decrease, p<0.001). We also observe a notable decline in new patients accessing these latter two therapies. Most US patients were able to access chronic medications during the early months of Covid-19, but still were more likely to discontinue their therapies than in previous months. Further, fewer than normal new patients started taking medications that may be vital to their care. Providers would do well to inquire about adherence and provide prompt, nonjudgmental, re-initiation of medications. From a policy perspective, opioid management programs seem to demonstrate a robust ability to manage existing patients in spite of disruption.

Ride-Hailing Services and Alcohol Consumption: Longitudinal Analysis.

BACKGROUND: Alcohol consumption is associated with a wide range of adverse health consequences and a leading cause of preventable deaths. Ride-hailing services such as Uber have been found to prevent alcohol-related motor vehicle fatalities. These services may, however, facilitate alcohol consumption generally and binge drinking in particular. OBJECTIVE: The goal of the research is to measure the impact of ride-hailing services on the extent and intensity of alcohol consumption. We allow these associations to depend on population density as the use of ride-hailing services varies across markets. METHODS: We exploit the phased rollout of the ride-hailing platform Uber using a difference-in-differences approach. We use this variation to measure changes in alcohol consumption among a local population following Uber's entry. Data are drawn from Uber press releases to capture platform entry and the Behavioral Risk Factor Surveillance Systems (BRFSS) Annual Survey to measure alcohol consumption in 113 metropolitan areas. Models are estimated using fixed-effects Poisson regression. Pre- and postentry trends are used to validate this approach. RESULTS: Ride-hailing has no association with the extent of alcohol consumption in high (0.61 [95% CI -0.05% to 1.28%]) or low (0.61 [95% CI -0.05% to 1.28%]) density markets, but is associated with increases in the binge drinking rate in high-density markets (0.71 [95% CI 0.13% to 1.29%]). This corresponds to a 4% increase in binge drinking within a Metropolitan Statistical Area. CONCLUSIONS: Ride-hailing services are associated with an increase in binge drinking, which has been associated with a wide array of adverse health outcomes. Drunk driving rates have fallen for more than a decade, while binge drinking continues to climb. Both trends may be accelerated by ride-hailing services. This suggests that health information messaging should increase emphasis on the direct dangers of alcohol consumption and binge drinking.

Physician-patient racial concordance and disparities in birthing mortality for newborns.

Recent work has emphasized the benefits of patient-physician concordance on clinical care outcomes for underrepresented minorities, arguing it can ameliorate outgroup biases, boost communication, and increase trust. We explore concordance in a setting where racial disparities are particularly severe: childbirth. In the United States, Black newborns die at three times the rate of White newborns. Results examining 1.8 million hospital births in the state of Florida between 1992 and 2015 suggest that newborn-physician racial concordance is associated with a significant improvement in mortality for Black infants. Results further suggest that these benefits manifest during more challenging births and in hospitals that deliver more Black babies. We find no significant improvement in maternal mortality when birthing mothers share race with their physician.

The Digitization of Patient Care: A Review of the Effects of Electronic Health Records on Health Care Quality and Utilization.

Electronic health records (EHRs) adoption has become nearly universal during the past decade. Academic research into the effects of EHRs has examined factors influencing adoption, clinical care benefits, financial and cost implications, and more. We provide an interdisciplinary overview and synthesis of this literature, drawing on work in public and population health, informatics, medicine, management information systems, and economics. We then chart paths forward for policy, practice, and research.

Patient-physician gender concordance and increased mortality among female heart attack patients.

We examine patient gender disparities in survival rates following acute myocardial infarctions (i.e., heart attacks) based on the gender of the treating physician. Using a census of heart attack patients admitted to Florida hospitals between 1991 and 2010, we find higher mortality among female patients who are treated by male physicians. Male patients and female patients experience similar outcomes when treated by female physicians, suggesting that unique challenges arise when male physicians treat female patients. We further find that male physicians with more exposure to female patients and female physicians have more success treating female patients.

Traders, guns, and money: The effects of mass shootings on stock prices of firearm manufacturers in the U.S.

We investigate how mass shootings influence the stock price of firearms manufacturers. While it is well known that mass shootings lead to increased firearms sales, the response from financial markets is unclear. On one hand, given the observed short-term increase in demand, firearm stock prices may rise due to the unexpected financial windfall for the firm. On the other, mass shootings may result in calls for regulation of the industry, leading to divestment of firearms stocks in spite of short-term demand. We examine this tension using a market movement event study in the wake of 93 mass shootings in the U.S. between 2009 and 2013. Findings show that stock prices of firearm manufacturers decline after shootings; each event reducing prices between 22.4 and 49.5 basis points, per day. These losses are exacerbated by the presence of a handgun and the number of victims killed, but not affected by the presence of children or location of the event. Finally, we find that these effects are most prevalent in the period 2009-2010 but disappear in later events, indicating that markets appear to have accepted mass shootings as the "new normal."