Measuring the Impact of the Affordable Care Act Medicaid Expansion on Access to Primary Care Using an Interrupted Time Series Approach

BACKGROUND: The Patient Protection and Affordable Care Act of 2010, commonly referred to as the Affordable Care Act (ACA), was created to increase access to primary care, improve quality of care, and decrease healthcare costs. A key provision in the law that mandated expansion of state Medicaid programme changed when states were given the option to voluntarily expand Medicaid. Our study sought to measure the impact of ACA Medicaid expansion on preventable hospitalization (PH) rates, a measure of access to primary care. METHODS: We performed an interrupted time series analysis of quarterly hospitalization rates across eight states from 2012 to 2015. Segmented regression analysis was utilized to determine the impact of policy reform on PH rates. RESULTS: The Affordable Care Act\u27s Medicaid expansion led to decreased rates of PH (improved access to care); however, the finding was not significant (coefficient estimate: -0.0059, CI -0.0225, 0.0107, p = 0.4856). Healthcare system characteristics, such as Medicaid spending per enrollee and Medicaid income eligibility, were associated with a significant decrease in rates of PH (improved access to care). However, the Medicaid-to-Medicare fee index (physician reimbursement) and states with a Democratic state legislature had a significant increase in rates of PH (poor access to care). CONCLUSION: Health policy reform and healthcare delivery characteristics impact access to care. Researchers should continue evaluating such policy changes across more states over longer periods of time. Researchers should translate these findings into cost analysis for state policy-makers to make better-informed decisions for their constituents. CONTRIBUTION TO KNOWLEDGE: Ambulatory care-sensitive conditions are a feasible method for evaluating policy and measuring access to primary care. Policy alone cannot improve access to care. Other factors (trust, communication, policy-makers\u27 motivations and objectives, etc.) must be addressed to improve access

Are textbook lungs really normal? A cadaveric study on the anatomical and clinical importance of variations in the major lung fissures, and the incomplete right horizontal fissure.

INTRODUCTION: The lungs have three main fissures: the right oblique fissure (ROF), right horizontal fissure (RHF), and left oblique fissure (LOF). These can be complete, incomplete or absent; quantifying the degree of completeness of these fissures is novel. Standard textbooks often refer to the fissures as complete, but awareness of variation is essential in thoracic surgery. MATERIALS AND METHODS: Fissures in 81 pairs of cadaveric lungs were classified. Oblique fissures were measured from lung hila posteriorly to the lung hila anteriorly; and the RHF measured from the ROF to the anteromedial lung edge. The degree of completeness of fissures was expressed as a percentage of the total projected length were they to be complete. The frequency and location of accessory fissures was noted. RESULTS: LOF were complete in 66/81 (81.5%), incomplete in 13/81 (16.0%) and absent in 2/81 (2.47%); ROF were complete in 52/81 (64.2%), incomplete in 29/81 (35.8%) and never absent; RHF were more variable, complete in 18/81 (22.2%), incomplete in 54/81 (66.7%) and absent in 9/81 (11.1%). LOF and ROF were on average 97.1% and 91.6% complete, respectively, being deficient posteriorly at the lung hila. The RHF on average 69.4% complete, being deficient anteromedially. There were accessory fissures in 10 left and 19 right lungs. CONCLUSIONS: This study provides a projection of the anatomy thoracic surgeons may encounter at operation, in particular the variable RHF. This knowledge is essential for optimal outcomes in both benign and oncological procedures influenced by the fissures

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Measuring the Impact of the Affordable Care Act Medicaid Expansion on Access to Primary Care Utilizing Preventable Hospitalizations: An Interrupted Time Series

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Conservation agriculture: a further step in sustainable agricultural intensification in the northern Ethiopian Highlands

status: publishe

Quantifying the Impact of Gestational Diabetes Mellitus, Maternal Weight and Race on Birthweight via Quantile Regression

<div><p>Background</p><p>Quantile regression, a robust semi-parametric approach, was used to examine the impact of gestational diabetes mellitus (GDM) across birthweight quantiles with a focus on maternal prepregnancy body mass index (BMI) and gestational weight gain (GWG).</p><p>Methods</p><p>Using linked birth certificate, inpatient hospital and prenatal claims data we examined live singleton births to non-Hispanic white (NHW, 135,119) and non-Hispanic black (NHB, 76,675) women in South Carolina who delivered 28–44 weeks gestation in 2004–2008.</p><p>Results</p><p>At a maternal BMI of 30 kg/m² at the 90^th quantile of birthweight, exposure to GDM was associated with birthweights 84 grams (95% CI 57, 112) higher in NHW and 132 grams (95% CI: 104, 161) higher in NHB. Results at the 50^th quantile were 34 grams (95% CI: 17, 51) and 78 grams (95% CI: 56, 100), respectively. At a maternal GWG of 13.5 kg at the 90^th quantile of birthweight, exposure to GDM was associated with birthweights 83 grams (95% CI: 57, 109) higher in NHW and 135 grams (95% CI: 103, 167) higher in NHB. Results at the 50^th quantile were 55 grams (95% CI: 40, 71) and 69 grams (95% CI: 46, 92), respectively.</p><p>Summary</p><p>Our findings indicate that GDM, maternal prepregnancy BMI and GWG increase birthweight more in NHW and NHB infants who are already at the greatest risk of macrosomia or being large for gestational age (LGA), that is those at the 90^th rather than the median of the birthweight distribution.</p></div