Major Traffic Safety Reform and Road Traffic Injuries Among Low-Income New York Residents, 2009-2021.

Objectives. To evaluate the effects of a comprehensive traffic safety policy-New York City's (NYC's) 2014 Vision Zero-on the health of Medicaid enrollees. Methods. We conducted difference-in-differences analyses using individual-level New York Medicaid data to measure traffic injuries and expenditures from 2009 to 2021, comparing NYC to surrounding counties without traffic reforms (n = 65 585 568 person-years). Results. After Vision Zero, injury rates among NYC Medicaid enrollees diverged from those of surrounding counties, with a net impact of 77.5 fewer injuries per 100 000 person-years annually (95% confidence interval = -97.4, -57.6). We observed marked reductions in severe injuries (brain injury, hospitalizations) and savings of $90.8 million in Medicaid expenditures over the first 5 years. Effects were largest among Black residents. Impacts were reversed during the COVID-19 period. Conclusions. Vision Zero resulted in substantial protection for socioeconomically disadvantaged populations known to face heightened risk of injury, but the policy's effectiveness decreased during the pandemic period. Public Health Implications. Many cities have recently launched Vision Zero policies and others plan to do so. This research adds to the evidence on how and in what circumstances comprehensive traffic policies protect public health. (Am J Public Health. 2024;114(6):633-641. https://doi.org/10.2105/AJPH.2024.307617).

Housing-Sensitive Health Conditions Can Predict Poor-Quality Housing.

Improving housing quality may improve residents' health, but identifying buildings in poor repair is challenging. We developed a method to improve health-related building inspection targeting. Linking New York City Medicaid claims data to Landlord Watchlist data, we used machine learning to identify housing-sensitive health conditions correlated with a building's presence on the Watchlist. We identified twenty-three specific housing-sensitive health conditions in five broad categories consistent with the existing literature on housing and health. We used these results to generate a housing health index from building-level claims data that can be used to rank buildings by the likelihood that their poor quality is affecting residents' health. We found that buildings in the highest decile of the housing health index (controlling for building size, community district, and subsidization status) scored worse across a variety of housing quality indicators, validating our approach. We discuss how the housing health index could be used by local governments to target building inspections with a focus on improving health.

Variation in Preterm Birth Rates Across Prenatal Care Sites in New York.

OBJECTIVE: To investigate variation in preterm birth rates by the site at which prenatal care was received. DESIGN: Cross-sectional cohort study. SETTING: New York State. PARTICIPANTS: Claims and encounter data on singleton live births that were covered by New York Medicaid (N = 154,377). METHODS: We analyzed data from New York Medicaid and the American Community Survey. We established sites of prenatal care using geocoded billing addresses for prenatal visits. We calculated descriptive statistics and conducted logistic regression analyses to determine variation in crude and risk-adjusted preterm birth rates by prenatal care site. RESULTS: The crude preterm birth rates averaged 7.8% (range = 2.0%-18.7%) by prenatal care site. The adjusted preterm birth rate was 8.0% (range = 2.8%-18.5%) by prenatal care site. Risk-adjusted preterm birth site-level rates at the 90th percentile were 2.7 times higher than those in the 10th percentile. The variation in risk-adjusted preterm birth site-level rates was not fully explained by birth volume, rural site location, or racial and ethnic composition of the patients who received prenatal care at the site. CONCLUSION: Wide variation in risk-adjusted preterm birth rates across prenatal care sites exists, and factors beyond known individual demographics and medical factors contribute to the variation. Further research is warranted to identify why receiving care at some prenatal sites is associated with higher risk of preterm birth than receiving care at others.

Association of Insurance Mix and Diagnostic Coding Practices in New York State Hospitals.

Importance: Given higher reimbursement rates, hospitals primarily serving privately insured patients may invest more in intensive coding than hospitals serving publicly insured patients. This may lead these hospitals to code more diagnoses for all patients. Objective: To estimate whether, for the same Medicaid enrollee with multiple hospitalizations, a hospital's share of privately insured patients is associated with the number of diagnoses on claims. Design, Setting, and Participants: This cross-sectional study used patient-level fixed effects regression models on inpatient Medicaid claims from Medicaid enrollees with at least 2 admissions in at least 2 different hospitals in New York State between 2010 and 2017. Analyses were conducted from 2019 to 2021. Exposures: The annual share of privately insured patients at the admitting hospital. Main Outcomes and Measures: Number of diagnostic codes per admission. Probability of diagnoses being from a list of conditions shown to be intensely coded in response to payment incentives. Results: This analysis included 1 614 630 hospitalizations for Medicaid-insured patients (mean [SD] age, 48.2 [20.1] years; 829 684 [51.4%] women and 784 946 [48.6%] men). Overall, 74 998 were Asian (4.6%), 462 259 Black (28.6%), 375 591 Hispanic (23.3%), 486 313 White (30.1%), 128 896 unknown (8.0%), and 86 573 other (5.4%). When the same patient was seen in a hospital with a higher share of privately insured patients, more diagnoses were recorded (0.03 diagnoses per percentage point [pp] increase in share of privately insured; 95% CI, 0.02-0.05; P < .001). Patients discharged from hospitals in the bottom quartile of privately insured patient share received 1.37 more diagnoses when they were subsequently discharged from hospitals in the top quartile, relative to patients whose admissions were both in the bottom quartile (95% CI, 1.21-1.53; P < .001). Those going from hospitals in the top quartile to the bottom had 1.67 fewer diagnoses (95% CI, -1.84 to -1.50; P < .001). Diagnoses in hospitals with a higher private payer share were more likely to be for conditions sensitive to payment incentives (0.08 pp increase for each pp increase in private share; 95% CI, 0.06-0.10; P < .001). These findings were replicated in 2016 to 2017 data. Conclusions and Relevance: In this cross-sectional study of Medicaid enrollees, admission to a hospital with a higher private payer share was associated with more diagnoses on Medicaid claims. This suggests payment policy may drive differential investments in infrastructure to document diagnoses. This may create a feedback loop that exacerbates resource inequity.

Identifying New York City Neighborhoods at Risk of Being Overlooked for Interventions.

Public health agencies are often faced with difficult decisions about where and how to allocate funding and resources. This question of resource allocation is central to public health policy; however, decisions related to resource allocation are sometimes made via informal or subjective approaches. We walk readers through a process of identifying needs across different neighborhoods in New York City (NYC) by examining community district-level health outcomes using data from published Community Health Profile reports released by the NYC Department of Health and Mental Hygiene (DOHMH) in 2015. In NYC, community districts are represented by community boards that provide a forum for addressing the needs of the community, making them a useful geographic unit for examining health information and turning data into action. We examined prevalence estimates and 95% confidence intervals of health indicators in each community district to identify significant disparities and calculated relative disparities in rates or prevalence to understand the relative magnitude of each disparity. Lastly, we demonstrate an application of this approach by identifying a cluster of neighborhoods with a high chance of being overlooked for public health interventions by conventional methods because of the relative number of disparities that exist in these neighborhoods. We present information on the disparity profile (number of disparities and relative disparity) for each neighborhood within the cluster and discuss potential public health implications. This approach can be applied to other jurisdictions to inform public health planning and resource allocation.

Renovating Subsidized Housing: The Impact On Tenants' Health.

Many public and subsidized housing developments in the US are aging and in need of significant repairs. Some observers worry that their poor condition threatens the health of residents. We evaluated a recent renovation of public housing that was undertaken through the transfer of six housing developments from the New York City Housing Authority to a public-private partnership. We studied whether the renovation and transfer to private managers led to improvements in tenants' health over three years, as measured by Medicaid claims. While we did not find significant improvements in individual health outcomes, we found significant relative improvements in overall disease burden when measured using an index of housing-sensitive conditions. These findings are not surprising. Given that broad-based housing renovations address a diverse set of health conditions, we should not expect them to have a significant impact on any single condition in the short run. Yet they may significantly improve residents' overall well-being over time.

Gentrification And The Health Of Low-Income Children In New York City.

Although the pace of gentrification has accelerated in cities across the US, little is known about the health consequences of growing up in gentrifying neighborhoods. We used New York State Medicaid claims data to track a cohort of low-income children born in the period 2006-08 for the nine years between January 2009 and December 2017. We compared the 2017 health outcomes of children who started out in low-income neighborhoods that gentrified in the period 2009-15 with those of children who started out in other low-income neighborhoods, controlling for individual child demographic characteristics, baseline neighborhood characteristics, and preexisting trends in neighborhood socioeconomic status. Our findings suggest that the experience of gentrification has no effects on children's health system use or diagnoses of asthma or obesity, when children are assessed at ages 9-11, but that it is associated with moderate increases in diagnoses of anxiety or depression-which are concentrated among children living in market-rate housing.