This study used a British cohort (n = ∼13,000) to investigate the association between child care during infancy and later cognition while controlling for social selection and missing data. It was found that attending child care (informal or center based) at 9 months was positively associated with cognitive outcomes at age 3 years, but only for children of mothers with low education. These effects did not persist to ages 5 or 7 years. Early center-based care was associated with better cognitive outcomes than informal care at ages 3 and 5 years, but not at 7 years. Effect sizes were larger among children whose mother had low education. Propensity score matching and multiple imputation revealed significant findings undetected using regression and complete-case approaches.

To better understand how early work experience shapes subsequent employment outcomes for young people (ages 18 to 20) with disabilities, we analyzed longitudinal data from the Youth Transition Demonstration (YTD) evaluation to test whether the employment experiences of 1,053 youth during the initial year after entry affected their employment during the third year after entry. To derive causal estimates, we used a dynamic-panel estimation model to account for timeinvariant unobserved individual characteristics that may be correlated with youth's self-selection into both early and later employment. We also controlled for other socioeconomic and health factors that may affect later employment. We found that early work experience increases the probability of being employed 2 years later by 17 percentage points. This estimate is an important advancement over the correlational approaches that characterize the current literature and provides stronger evidence that early work experience is a key determinant of subsequent labor market success.

A survey conducted with data from 2008 found that physicians often do not communicate with each other at the time of referral or after consultation. Communication between physicians might have improved since then, with the dissemination of electronic health records (EHRs), but this is not known. We used 2019 survey data to measure primary care physicians' perceptions of communication at the time of referral and after consultation. We found that large gaps in communication persist. The similarity between these survey results suggests that despite the dissemination of EHRs, physicians still do not consistently communicate with each other about the patients they share.

Research Objective Identifying characteristics of beneficiaries, primary care physicians, and primary care practice sites that predict highly fragmented ambulatory care (that is, care spread across multiple providers without a dominant provider) is essential to develop effective interventions targeted at reducing fragmentation. High care fragmentation is associated with unnecessary procedures and testing, increased emergency department visits and hospitalizations, and increased medical costs. Study Design This study was conducted in the context of the Comprehensive Primary Care Plus Model (CPC+), a large primary care redesign initiative. We used Medicare claims data from January through December 2018 on Medicare fee‐for‐service (FFS) beneficiaries attributed to primary care practice sites participating in CPC+ and to comparison practices that were similar at baseline. We used hierarchical linear models to predict the likelihood of a beneficiary receiving highly fragmented care, defined as having a fragmentation score (measured by the reversed Bice‐Boxerman Index) ≥ 0.85. We used an extensive set of explanatory variables at each level (74 total variables) and group‐level random intercepts to understand how characteristics at each level help explain variation in fragmentation. We estimated separate models for the two CPC+ transformation/payment tracks. Population Studied 3,541,136 Medicare FFS beneficiaries attributed to 26,344 primary care physicians in 9300 primary care practice sites. Principal Findings The three sets of explanatory variables (beneficiary, physician, and practice site) together only explained about 5 percent of the variation in the likelihood of high care fragmentation. Unobserved differences between primary care physicians and between primary care practice sites together accounted for only 4 percent of the variation. Instead, more than 91 percent of the variation in fragmentation consisted of unobserved residual variance. We identified several characteristics of beneficiaries (age, reason for original Medicare entitlement, and dual status), physicians (gender and measures of comprehensiveness of care), and practice sites (size, being part of a system/hospital, and census region) that had small associations with high fragmentation. Findings were similar by track. Conclusions Although we identified a number of characteristics that predict high care fragmentation, most of the variation in fragmentation was not explained by observed beneficiary, primary care physician, or primary care practice characteristics. This suggests other providers and beneficiaries' preferences may be important factors. Implications for Policy or Practice Our findings show that primary care physician and practice site characteristics explain only a small share of variation in care fragmentation. Behaviors of other health care providers not captured by regional controls, as well as unmeasured patient preferences, are likely to be important predictors of high care fragmentation. One implication of these findings is that inte...

Objective: To determine the association between a large-scale, multi-payer primary care redesign-the Comprehensive Primary Care (CPC) Initiative-on outpatient emergency department (ED) and urgent care center (UCC) use and to identify the types of visits that drive the overall trends observed. Data Sources: Medicare claims data capturing characteristics and outcomes of 565 674 Medicare fee-for-service (FFS) beneficiaries attributed to 497 CPC practices and 1 165 284 beneficiaries attributed to 908 comparison practices. Study Design: We used an adjusted difference-indifferences framework to test the association between CPC and beneficiaries' ED and UCC use from October 2012 through December 2016. Regression models controlled for baseline practice and patient characteristics and practice-level clustering of standard errors. Our key outcomes were all-cause and primary care substitutable (PC substitutable) outpatient ED and UCC visits, and potentially primary care preventable (PPC preventable) ED visits, categorized by the New York University Emergency Department Algorithm. We used a propensity score-matched comparison group of practices that were similar to CPC practices before CPC on multiple dimensions. Both groups of practices had similar growth in ED and UCC visits in the two-year period before CPC. Principal Findings: Comprehensive Primary Care practices had 2% (P = .06) lower growth in all-cause ED visits than comparison practices. They had 3% (P = .02) lower growth in PC substitutable ED visits, driven by lower growth in weekday PC substitutable visits (4%, P = .002). There was 3% (P = .04) lower growth in PPC preventable ED visits with no weekday/nonweekday differential. As expected, our falsification test showed no difference in ED visits for injuries. UCC visits had 9% lower growth for both all-cause (P = .08) and PC substitutable visits (P = .07). Conclusions: Our results suggest that greater access to the practice and more effective primary care both contributed to the lower growth in ED and UCC visits during the initiative.