Beyond Testing: Empirical Models of Insurance Markets

We describe recent advances in the empirical analysis of insurance markets. This new research proposes ways to estimate individual demand for insurance and the relationship between prices and insurer costs in the presence of adverse and advantageous selection. We discuss how these models permit the measurement of welfare distortions arising from asymmetric information and the welfare consequences of potential government policy responses. We also discuss some challenges in modeling imperfect competition between insurers, and outline a series of open research questions.

Correlates of Parental Antibiotic Knowledge, Demand, and Reported Use

Clinicians cite parental misconceptions and requests for antibiotics as reasons for inappropriate prescribing. To identify misconceptions regarding antibiotics and predictors of parental demand for antibiotics and to determine if parental knowledge and attitudes are associated with use. Survey of parents in 16 Massachusetts communities. Domains included antibiotic-related knowledge, attitudes about antibiotics, antibiotic use during a 12-month period, demographics, and access to health information. Bivariate and multivariate analyses evaluated predictors of knowledge and proclivity to demand antibiotics. A multivariate model evaluated the associations of knowledge, demand, and demographic factors with parent-reported antibiotic use. A total of 1106 surveys were returned (response rates: 54% and 32% for commercially-insured and Medicaid-insured families). Misconceptions were common regarding bronchitis (92%) and green nasal discharge (78%). Two hundred sixty-five (24%) gave responses suggesting a proclivity to demand antibiotics. Antibiotic knowledge was associated with increased parental age and education, having more than 1 child, white race, and receipt of media information on resistance. Factors associated with a proclivity to demand antibiotics included decreased knowledge, pressure from day-care settings, lack of alternatives offered by clinicians, and lack of access to media information. Among all respondents, reported antibiotic use was associated with younger child age and day-care attendance. Among Medicaid-insured children only, less antibiotic knowledge and tendency to demand antibiotics were associated with higher rates of antibiotic use. Misconceptions regarding antibiotic use are widespread and potentially modifiable by clinicians and media sources. Particular attention should be paid to Medicaid-insured patients in whom such misconceptions may contribute to inappropriate prescribing

Child care center policies and practices for management of ill children

OBJECTIVES: The objectives of this study were to 1) describe child care staff knowledge and beliefs regarding upper respiratory tract infections and antibiotic indications and 2) evaluate child care staff reported reasons for a) exclusion from child care, b) referral to a health care provider, and c) recommending antibiotics for an ill child. METHODS: A longitudinal study based in randomly selected child care centers in Massachusetts. Staff completed a survey to assess knowledge regarding common infections. For six weeks, staff completed a record of absences each day, describing the reason for an absence, and advice given to the parents regarding exclusion, referral to a health care provider, and obtaining antibiotics. Exclusions for the specific illness/symptom were defined as appropriate or inappropriate based on national guidelines. RESULTS: A large proportion of child care staff incorrectly believed that antibiotics are indicated for bronchitis (80.5%) and green rhinorrhea (80.5%) in children. For 82.2% of absences, the circumstances or reasons for the absence were discussed with a child care staff member. Of 538 absences due to illness that child care staff discussed with parents, there were 45 inappropriate exclusions (8.4% of illnesses discussed), 91 appropriate exclusions (16.9% of illnesses discussed), and 402 cases (74.7%) in which no recommendation for exclusion was made. CONCLUSIONS: Misconceptions regarding the need for antibiotics for URIs are common among child care staff. However, day care staff do not pressure parents to seek medical attention or antibiotics

Attributable healthcare utilization and cost of pneumonia due to drug-resistant streptococcus pneumonia: a cost analysis

Background: The burden of disease due to S. pneumoniae (pneumococcus), particularly pneumonia, remains high despite the widespread use of vaccines. Drug resistant strains complicate clinical treatment and may increase costs. We estimated the annual burden and incremental costs attributable to antibiotic resistance in pneumococcal pneumonia. Methods: We derived estimates of healthcare utilization and cost (in 2012 dollars) attributable to penicillin, erythromycin and fluoroquinolone resistance by taking the estimate of disease burden from a previously described decision tree model of pneumococcal pneumonia in the U.S. We analyzed model outputs assuming only the existence of susceptible strains and calculating the resulting differences in cost and utilization. We modeled the cost of resistance from delayed resolution of illness and the resulting additional health services. Results: Our model estimated that non-susceptibility to penicillin, erythromycin and fluoroquinolones directly caused 32,398 additional outpatient visits and 19,336 hospitalizations for pneumococcal pneumonia. The incremental cost of antibiotic resistance was estimated to account for 4% ($91 million) of direct medical costs and 5$233 million) of total costs including work and productivity loss. Most of the incremental medical cost ($82 million) was related to hospitalizations resulting from erythromycin non-susceptibility. Among patients under age 18 years, erythromycin non-susceptibility was estimated to cause 17$38 million in costs, or 39% of pneumococcal pneumonia costs attributable to resistance. Conclusions: We estimate that antibiotic resistance in pneumococcal pneumonia leads to substantial healthcare utilization and cost, with more than one-third driven by macrolide resistance in children. With 5% of total pneumococcal costs directly attributable to resistance, strategies to reduce antibiotic resistance or improve antibiotic selection could lead to substantial savings

CLEAR II: Evidence for Early Formation of the Most Compact Quiescent Galaxies at High Redshift

The origin of the correlations between mass, morphology, quenched fraction, and formation history in galaxies is difficult to define, primarily due to the uncertainties in galaxy star-formation histories. Star-formation histories are better constrained for higher redshift galaxies, observed closer to their formation and quenching epochs. Here we use "non-parametric" star-formation histories and a nested sampling method to derive constraints on the formation and quenching timescales of quiescent galaxies at $0.7<z<2.5$. We model deep HST grism spectroscopy and photometry from the CLEAR (CANDELS Lyman$-\alpha$ Emission at Reionization) survey. The galaxy formation redshifts, $z_{50}$ (defined as the point where they had formed 50\% of their stellar mass) range from $z_{50}\sim 2$ (shortly prior to the observed epoch) up to $z_{50} \simeq 5-8$. \editone{We find that early formation redshifts are correlated with high stellar-mass surface densities, $\log \Sigma_1 / (M_\odot\ \mathrm{kpc}^{-2}) >$10.25, where $\Sigma_1$ is the stellar mass within 1~pkpc (proper kpc). Quiescent galaxies with the highest stellar-mass surface density, $\log\Sigma_1 / (M_\odot\ \mathrm{kpc}^{-2}) > 10.25$, } show a \textit{minimum} formation redshift: all such objects in our sample have $z_{50} > 2.9$. Quiescent galaxies with lower surface density, $\log \Sigma_1 / (M_\odot\ \mathrm{kpc}^{-2}) = 9.5 - 10.25$, show a range of formation epochs ($z_{50} \simeq 1.5 - 8$), implying these galaxies experienced a range of formation and assembly histories. We argue that the surface density threshold$\log\Sigma_1/(M_\odot\ \mathrm{kpc}^{-2})>10.25$ uniquely identifies galaxies that formed in the first few Gyr after the Big Bang, and we discuss the implications this has for galaxy formation models.Comment: 13 pages, 7 figures, accepted for publication in ApJ. Includes an interactive online appendix (https://vince-ec.github.io/appendix/appendix

Are the ultra-high-redshift galaxies at z > 10 surprising in the context of standard galaxy formation models?

A substantial number of ultra-high redshift (8 < z < 17) galaxy candidates have been detected with JWST, posing the question: are these observational results surprising in the context of current galaxy formation models? We address this question using the well-established Santa Cruz semi-analytic models, implemented within merger trees from the new suite of cosmological N-body simulations GUREFT, which were carefully designed for ultra-high redshift studies. Using our fiducial models calibrated at z=0, we present predictions for stellar mass functions, rest-frame UV luminosity functions, and various scaling relations. We find that our (dust-free) models predict galaxy number densities at z~11 (z~ 13) that are an order of magnitude (a factor of ~30) lower than the observational estimates. We estimate the uncertainty in the observed number densities due to cosmic variance, and find that it leads to a fractional error of 30-70% at z=11 (25-150% at z=13) for the available observed fields. We explore which processes in our models are most likely to be rate-limiting for the formation of luminous galaxies at these early epochs, considering the halo formation rate, gas cooling, star formation, and stellar feedback, and conclude that it is mainly efficient stellar-driven winds. We find that a modest boost of a factor of ~4 to the UV luminosities, which could arise from a top-heavy stellar initial mass function characteristic of Pop III stars, would bring our current models into agreement with the observations.Comment: 20 pages, 15 figures, submitted to MNRA

Transition experiences and health care utilization among young adults with type 1 diabetes

Background: The purpose of this study was to describe the current status of adult diabetes care in young adults with type 1 diabetes and examine associations between health care transition experiences and care utilization. Methods: We developed a survey to assess transition characteristics and current care in young adults with type 1 diabetes. We mailed the survey to the last known address of young adults who had previously received diabetes care at a tertiary pediatric center. Results: Of 291 surveys sent, 83 (29%) were undeliverable and three (1%) were ineligible. Of 205 surveys delivered, 65 were returned (response rate 32%). Respondents (mean age 26.6 ± 3.0 years, 54% male, 91% Caucasian) transitioned to adult diabetes care at a mean age of 19.2 ± 2.8 years. Although 71% felt mostly/completely prepared for transition, only half received recommendations for a specific adult provider. Twenty-six percent reported gaps exceeding six months between pediatric and adult diabetes care. Respondents who made fewer than three diabetes visits in the year prior to transition (odds ratio [OR] 4.5, 95% confidence interval [CI] 1.2–16.5) or cited moving/relocation as the most important reason for transition (OR 6.3, 95% CI 1.3–31.5) were more likely to report gaps in care exceeding six months. Patients receiving current care from an adult endocrinologist (79%) were more likely to report at least two diabetes visits in the past year (OR 6.0, 95% CI 1.5–24.0) compared with those receiving diabetes care from a general internist/adult primary care doctor (17%). Two-thirds (66%) reported receiving all recommended diabetes screening tests in the previous year, with no difference according to provider type. Conclusion: In this sample, transition preparation was variable and one quarter reported gaps in obtaining adult diabetes care. Nevertheless, the majority endorsed currently receiving regular diabetes care, although visit frequency differed by provider type. Because locating patients after transition was incomplete, our findings suggest the need for standardized methods to track transitioning patients