The Role of Retiree Health Insurance in the Employment Behavior of Older Men

We model the employment and medical care decisions of older men who face health risk. The budget constraint incorporates detailed characteristics of health insurance as well as Social Security and private pensions. A man whose health insurance is tied to continued employment with his current employer faces the risk of large medical expenditures in the event of an adverse health shock if he retires before becoming eligible for Medicare at age 65. A man whose employer provides retiree health insurance or who has access to other health insurance not tied to his employment decision (e.g., from his wife) can retire before age 65 without consequences for his health insurance coverage. We use data from the Health and Retirement Survey to estimate the parameters of the model using structural methods. Simulations based on the estimates imply that changes in health insurance, including access and restrictions to retiree health insurance and Medicare have a modest impact on employment behavior among older males.

Retiree Health Insurance and the Labor Force Behavior of Older Men in the 1990s

We estimate the impact of employer-provided retiree health insurance on the rate at which men aged 51-62 enter and exit the labor force and switch jobs. The models estimated are an approximation of the employment decision rules implied by a dynamic stochastic model of employment behavior of older individuals. We use data from the Health and Retirement Survey (HRS), which contains more detailed and accurate measures of retiree health insurance than those used in most previous studies. The results show that availability of employer-provided retiree health insurance (EPRHI) increases the rate of exit from employment by two percentage points per year on average if the individual shares the cost of the insurance coverage with the firm, and by six percentage points if the firm pays the entire cost. The impact of EPRHI on the annual rate of labor force exit increases with age, reaching nine percentage points by age 61. These are larger than the effects estimated in previous studies. The accurate and detailed health insurance measures available in the HRS help account for the larger effects found here. Controlling for unobserved heterogeneity, a possibility not accounted for in previous studies, also has a substantial impact on the estimates.

Nurse scientists overcoming challenges to lead transdisciplinary research teams

Increasingly, scientific funding agencies are requiring that researchers move toward an integrated, transdisciplinary team science paradigm. While the barriers to and rewards of conducting this type of research have been discussed in the literature, examples of how nurse investigators have led these teams to reconcile the differences in theoretical, methodological, and/or analytic perspectives that inevitably exist are lacking. In this article, we describe these developmental trajectory challenges through a case study of one transdisciplinary team, focusing on team member characteristics and the leadership tasks associated with successful transdisciplinary science teams in the literature. Specifically, we describe how overcoming these challenges has been essential to examining the complex, and potentially cumulative effects that key intersections between legal, social welfare, and labor market systems may have on the health of disadvantaged women. Finally, we discuss this difficult, but rewarding work within the context of lessons learned and transdisciplinary team research in relation to the future of nursing science

COVID-19 symptoms at time of testing and association with positivity among outpatients tested for SARS-CoV-2

Introduction Symptoms associated with SARS-CoV-2 infection remain incompletely understood, especially among ambulatory, non-hospitalized individuals. With host factors, symptoms predictive of SARS-CoV-2 could be used to guide testing and intervention strategies. Methods Between March 16 and September 3, 2020, we examined the characteristics and symptoms reported by individuals presenting to a large outpatient testing program in the Southeastern US for nasopharyngeal SARS-CoV-2 RNA RT-PCR testing. Using self-reported symptoms, demographic characteristics, and exposure and travel histories, we identified the variables associated with testing positive using modified Poisson regression. Results Among 20,177 tested individuals, the proportion positive was 9.4% (95% CI, 9.0–9.8) and was higher for men, younger individuals, and racial/ethnic minorities (all P<0.05); the positivity proportion was higher for Hispanics (26.9%; 95% CI. 24.9–29.0) compared to Blacks (8.6%; 95% CI, 7.6–9.7) or Whites (5.8%; 95% CI, 5.4–6.3). Individuals reporting contact with a COVID-19 case had the highest positivity proportion (22.8%; 95% CI, 21.5–24.1). Among the subset of 8,522 symptomatic adults who presented for testing after May 1, when complete symptom assessments were performed, SARS-CoV-2 RNA PCR was detected in 1,116 (13.1%). Of the reported symptoms, loss of taste or smell was most strongly associated with SARS-CoV-2 RNA detection with an adjusted risk ratio of 3.88 (95% CI, 3.46–4.35). The presence of chills, fever, cough, aches, headache, fatigue and nasal congestion also significantly increased the risk of detecting SARS-CoV-2 RNA, while diarrhea or nausea/vomiting, although not uncommon, were significantly more common in those with a negative test result. Symptom combinations were frequent with 67.9% experiencing ≥4 symptoms, including 19.8% with ≥8 symptoms; report of greater than three symptoms increased the risk of SARS-CoV-2 RNA detection. Conclusions In a large outpatient population in the Southeastern US, several symptoms, most notably loss of taste or smell, and greater symptom burden were associated with detection of SARS-CoV-2 RNA. Persons of color and those with who were a contact of a COVID-19 case were also more likely to test positive. These findings suggest that, given limited SARS-CoV-2 testing capacity, symptom presentation and host characteristics can be used to guide testing and intervention prioritization

Public health insurance and entry into self-employment

We estimate the impact of a differential treatment of paid employees versus self-employed workers in a public health insurance system on the entry rate into entrepreneurship. In Germany, the public health insurance system is mandatory for most paid employees, but not for the selfemployed, who usually buy private health insurance. Private health insurance contributions are relatively low for the young and healthy, and until 2013 also for males, but less attractive at the other ends of these dimensions and if membership in the public health insurance allows other family members to be covered by contribution-free family insurance. Therefore, the health insurance system can create incentives or disincentives to starting up a business depending on the family’s situation and health. We estimate a discrete time hazard rate model of entrepreneurial entry based on representative household panel data for Germany, which include personal health information, and we account for non- random sample selection. We estimate that an increase in the health insurance cost differential between self-employed workers and paid employees by 100 euro per month decreases the annual probability of entry into selfemployment by 0.38 percentage points, i.e. about a third of the average annual entry rate. The results show that the phenomenon of entrepreneurship lock, which an emerging literature describes for the system of employer provided health insurance in the USA, can also occur in a public health insurance system. Therefore, entrepreneurial activity should be taken into account when discussing potential health care reforms, not only in the USA and in Germany

Evaluation of a COVID-19 convalescent plasma program at a U.S. academic medical center

Amidst the therapeutic void at the onset of the COVID-19 pandemic, a critical mass of scientific and clinical interest coalesced around COVID-19 convalescent plasma (CCP). To date, the CCP literature has focused largely on safety and efficacy outcomes, but little on implementation outcomes or experience. Expert opinion suggests that if CCP has a role in COVID-19 treatment, it is early in the disease course, and it must deliver a sufficiently high titer of neutralizing antibodies (nAb). Missing in the literature are comprehensive evaluations of how local CCP programs were implemented as part of pandemic preparedness and response, including considerations of the core components and personnel required to meet demand with adequately qualified CCP in a timely and sustained manner. To address this gap, we conducted an evaluation of a local CCP program at a large U.S. academic medical center, the University of North Carolina Medical Center (UNCMC), and patterned our evaluation around the dimensions of the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to systematically describe key implementation-relevant metrics. We aligned our evaluation with program goals of reaching the target population with severe or critical COVID-19, integrating into the structure of the hospital-wide pandemic response, adapting to shifting landscapes, and sustaining the program over time during a compassionate use expanded access program (EAP) era and a randomized controlled trial (RCT) era. During the EAP era, the UNCMC CCP program was associated with faster CCP infusion after admission compared with contemporaneous affiliate hospitals without a local program: median 29.6 hours (interquartile range, IQR: 21.2–48.1) for the UNCMC CCP program versus 47.6 hours (IQR 32.6–71.6) for affiliate hospitals; (P<0.0001). Sixty-eight of 87 CCP recipients in the EAP (78.2%) received CCP containing the FDA recommended minimum nAb titer of ≥1:160. CCP delivery to hospitalized patients operated with equal efficiency regardless of receiving treatment via a RCT or a compassionate-use mechanism. It was found that in a highly resourced academic medical center, rapid implementation of a local CCP collection, treatment, and clinical trial program could be achieved through redeployment of highly trained laboratory and clinical personnel. These data provide important pragmatic considerations critical for health systems considering the use of CCP as part of an integrated pandemic response

Dynamic panel data estimation of an integrated Grossman and Becker-Murphy model of health and addiction

We propose a dynamic panel data approach to estimate a model that integrates the Becker-Murphy theory of rational addiction with the Grossman model of health investment. We define an individual’s lifetime smoking consumption and investments in health capital as simultaneous choices within a single optimisation problem. We show that this can be estimated using GMM system estimation of two stand-alone single fourth-order difference equations of health capital and smoking. These preserve roots and fundamental dynamics of the original system of four interrelated first-order equations. Monte Carlo simulations confirm that this reduced-form dynamic estimation also produces very similar estimates to the ones of the initial system of equations. We argue that, in the presence of long panel data, this approach may provide a feasible alternative for the estimation of a complex life-cycle model of human capital