Author Archives: afscme

Daily Nursing Home Staffing Levels Highly Variable, Often Below CMS Expectations

Source: Fangli Geng, David G. Stevenson, and David C. Grabowski, Health Affairs, Vol. 38 No. 7, July 2019
(subscription required)

From the abstract:
Staffing is an important quality measure that is included on the federal Nursing Home Compare website. New payroll-based data reveal large daily staffing fluctuations, low weekend staffing, and daily staffing levels often below the expectations of the Centers for Medicare and Medicaid Services (CMS). These data provide a more accurate and complete staffing picture for CMS and consumers.

In Hospitals With More Nurses Who Have Baccalaureate Degrees, Better Outcomes For Patients After Cardiac Arrest

Source: Jordan M. Harrison, Linda H. Aiken, Douglas M. Sloane, J. Margo Brooks Carthon, Raina M. Merchant, Robert A. Berg, Matthew D. McHugh, Health Affairs, Vol. 38 No. 7, July 2019
(subscription required)

From the abstract:
In 2010, prompted by compelling evidence that demonstrated better patient outcomes in hospitals with higher percentages of nurses with a bachelor of science in nursing (BSN), the Institute of Medicine recommended that 80 percent of the nurse workforce be qualified at that level or higher by 2020. Using data from the American Heart Association’s Get With the Guidelines–Resuscitation registry (for 2013–18), RN4CAST-US hospital nurse surveys (2015–16), and the American Hospital Association (2015), we found that each 10-percentage-point increase in the hospital share of nurses with a BSN was associated with 24 percent greater odds of surviving to discharge with good cerebral performance among patients who experienced in-hospital cardiac arrest. Lower patient-to-nurse ratios on general medical and surgical units were also associated with significantly greater odds of surviving with good cerebral performance. These findings contribute to the growing body of evidence that supports policies to increase access to baccalaureate-level education and improve hospital nurse staffing.

Growth Of Public Coverage Among Working Families In The Private Sector

Source: Douglas Strane, Genevieve P. Kanter, Meredith Matone, Ahaviah Glaser, and David M. Rubin, Health Affairs, Vol. 38 No. 7, July 2019
(subscription required)

From the abstract:
Working families have increasingly enrolled their children in Medicaid or the Children’s Health Insurance Program in recent years. Parents’ place of employment affects the availability and cost of family health insurance, making it a determinant of pediatric public insurance enrollment. We examined that enrollment in the period 2008–16 in families working full time and earning more than 100 percent of the federal poverty level at three types of employers. Among low-income families (100–199 percent of poverty), children’s public health insurance coverage was highest for those with parents employed at small private firms, increasing from 53 percent to 79 percent, while the public insurance coverage rate also increased among children with parents working for large private firms (from 45 percent to 69 percent). Among moderate-income families (200–299 percent of poverty) working at small private firms, public coverage increased from 21 percent to 64 percent. Increases in the number of working families with pediatric public insurance were driven by employees of large private firms. Maintaining high pediatric insurance coverage rates will require policies that recognize the changing role of public insurance for working families as the cost of employer-based coverage grows.

Blue-Collar Workers Had Greatest Insurance Gains After ACA Implementation

Source: Sumit D. Agarwal, Anna L. Goldman, and Benjamin D. Sommers, Health Affairs, Vol. 38 No. 7, July 2019
(subscription required)

From the abstract:
Analyzing national survey data, we found that workers in traditionally blue-collar industries (service jobs, farming, construction, and transportation) experienced the largest gains in health insurance after implementation of the Affordable Care Act (ACA) in 2014. Compared to other occupations, these had lower employer-based coverage rates before the ACA. Most of the post-ACA coverage gains came from Medicaid and directly purchased nongroup insurance.

The Invisible Web of Work: The Intertwining of A-I, Electronic Surveillance, and Labor Law

Source: Richard A. Bales, Katherine V.W. Stone, UCLA School of Law, Public Law Research Paper No. 19-18, Last revised: June 30, 2019

From the abstract:
Employers and others who hire or engage workers to perform services use a dizzying array of electronic mechanisms to make personnel decisions about hiring, worker evaluation, compensation, discipline, and retention. These electronic mechanisms include electronic trackers, surveillance cameras, metabolism monitors, wearable biological measuring devices, and implantable technology. These tools enable employers to record their workers’ every movement, listen in on their conversations, measure minute aspects of performance, and detect oppositional organizing activities. The data collected is transformed by means of artificial intelligence (A-I) algorithms into a permanent electronic resume that can identify and predict an individual’s performance as well as their work ethic, personality, union proclivity, employer loyalty, and future health care costs. The electronic resume produced by A-I will accompany workers from job to job as they move around the boundaryless workplace. Thus A-I and electronic monitoring produce an invisible electronic web that threatens to invade worker privacy, deter unionization, enable subtle forms of employer blackballing, exacerbate employment discrimination, render unions ineffective, and obliterate the protections of the labor laws.

This article describes the many ways A-I is being used in the workplace and how its use is transforming the practices of hiring, evaluating, compensating, controlling, and dismissing workers. It then focuses on four areas of law in which A-I threatens to undermine worker protections: anti-discrimination law, privacy law, antitrust law, and labor law. Finally, this article maps out an agenda for future law reform and research.

Is Technology Widening the Gender Gap? Automation and the Future of Female Employment

Source: Mariya Brussevich, Era Dabla-Norris, Salma Khalid, IMF Working Paper No. 19/91, May 2019

From the abstract:
Using individual level data on task composition at work for 30 advanced and emerging economies, we find that women, on average, perform more routine tasks than men/tasks that are more prone to automation. To quantify the impact on jobs, we relate data on task composition at work to occupation level estimates of probability of automation, controlling for a rich set of individual characteristics (e.g., education, age, literacy and numeracy skills). Our results indicate that female workers are at a significantly higher risk for displacement by automation than male workers, with 11 percent of the female workforce at high risk of being automated given the current state of technology, albeit with significant cross-country heterogeneity. The probability of automation is lower for younger cohorts of women, and for those in managerial positions.

Financial Frictions and Stimulative Effects of Temporary Corporate Tax Cuts

Source: William Gbohoui, Rui Castro, IMF Working Paper No. 19/97, May 2019

From the abstract:
This paper uses an industry equilibrium model where some firms are financially constrained to quantify the effects of a transitory corporate tax cut funded by a future tax increase on the U.S. economy. It finds that by increasing current cash-flows tax cuts alleviate financing frictions, hereby stimulating current investment. Per dollar of tax stimulus, aggregate investment increases by 26 cents on impact, and aggregate output by 3.5 cents. The average effect masks heterogeneity: multipliers are close to 1 for constrained firms, especially new entrants, and negative for larger and unconstrained firms. The output effects extend well past the period the policy is reversed, leading to a cumulative multiplier of 7.2 cents. Multipliers are significantly larger when controlling for the investment crowding-out effect among unconstrained firms.

The ‘giant sucking sound’ of NAFTA: Ross Perot was ridiculed as alarmist in 1992 but his warning turned out to be prescient

Source: Harley Shaiken, The Conversation, July 12, 2019

…. As it turns out, Perot, who died on July 9, had a point. His projections were often fanciful, but his warning turned out to be prescient. ….

…. “You implement that NAFTA, the Mexican trade agreement, where they pay people a dollar an hour, have no health care, no retirement, no pollution controls,” Perot said during the second presidential debate in October 1992, “and you’re going to hear a giant sucking sound of jobs being pulled out of this country.”

The response to that remark was fierce and immediate. Economists argued he was dead wrong as they sang the praises of free trade. Perot’s warning, however, resonated with workers, unions, environmentalists and people in manufacturing towns across the country, helping him earn 20 million votes or about 19% of the total. ….

…..Scholars and policymakers often disagree about the impact that NAFTA has had on economic growth and job generation in the U.S. That impact, they say, is not always easy to disentangle from other economic, social and political factors that have influenced U.S. growth.

It is true that leaders of all three countries did tear down trade barriers and insert effective protections for corporations and investment. But critics like Perot were right – and Clinton was wrong – about the warning on jobs.

The Economic Policy Institute, a left-leaning think tank, concluded that the U.S. lost about 850,000 jobs from 1993 to 2013 as a result of NAFTA and that number has undoubtedly risen. And the “social progress as well as economic growth” in relation to the agreement never seemed to appear. Despite strong productivity growth in U.S. and Mexican manufacturing, real wages sank by 17% in Mexico from 1994 to 2011 and slid in the U.S. as well. ….