The COVID-19 pandemic has taken a significant toll on nursing homes in the US, with upwards of a third of deaths occurring in nursing homes, and more in long-term care facilities. By combining data on facility-level COVID-19 deaths with facility-level data on the neighborhoods where nursing home staff reside for a sample of eighteen states, this paper finds that staff neighborhood characteristics are a large and significant predictor of COVID-19 outbreaks. One standard deviation increases in average staff tract population density, public transportation use, and non-white share were associated with 1.3 (SE .33), 1.4 (SE .35), and 0.9 (SE .24) additional deaths per 100 beds, respectively. These effects are larger than all facility management or quality variables, and larger than the effect of the nursing home's own neighborhood characteristics. These results suggest that staff communities are likely to be an important source of infection, and that disparities in nursing home outbreaks may be related to differences in the types of neighborhoods nursing home staff live in.
There is abundant literature on efforts to reduce opioid prescriptions and misuse, but comparatively little on the treatment provided to people with opioid use disorder (OUD). Using claims data representing 12–15 million nonelderly adults covered through commercial group insurance during the period 2008–17, we explored rates of OUD diagnoses, treatment patterns, and spending. We found three key patterns: The rate of diagnosed OUD nearly doubled during 2008–17, and the distribution has shifted toward older age groups; the likelihood that diagnosed patients will receive any treatment has declined, particularly among those ages forty-five and older, because of a reduction in the use of medication-assisted treatment (MAT) and despite clinical evidence demonstrating its efficacy; and treatment spending is lower for patients who choose MAT. These patterns suggest that policies supporting the use of MAT are critical to addressing the undertreatment of OUD among the commercially insured and that further research to assess the cost-effectiveness of treatment with versus without medication is needed.
We study the link between the student credit expansion of the past 15 years and the contemporaneous rise in college tuition. To disentangle simultaneity issues, we analyze the effects of increases in federal student loan caps using detailed student-level financial data. We find a pass-through effect on tuition of changes in subsidized loan maximums of about 60 cents on the dollar and of about 20 cents on the dollar for unsubsidized federal loans. The effect is most pronounced for more expensive degrees and degrees offered by for-profit and 2-year institutions.