Medicaid Managed Care and Pediatric Dental Emergency Department Visits.

Importance: Millions of economically disadvantaged children depend on Medicaid for dental care, with states differing in whether they deliver these benefits using fee-for-service or capitated managed care payment models. However, there is limited research examining the association between managed care and the accessibility of dental services. Objective: To estimate the association between the adoption of managed care for dental services in Florida's Medicaid program and nontraumatic dental emergency department visits and associated charges. Design, Setting, and Participants: This cohort study used an event-study difference-in-differences design, leveraging Florida Medicaid's staggered adoption of managed care to examine its association with pediatric nontraumatic dental emergency department visits and associated charges. This study included all Florida emergency department visits from 2010 to 2014 in which the patient was 17 years or younger, the patient was a Florida resident, Medicaid paid for the visit, and a primary or secondary International Classification of Diseases, Ninth Revision, code was used to classify a nontraumatic dental condition. Analyses were conducted between May 2023 and April 2024. Exposure: The county of residence transitioning Medicaid dental services from fee-for-service to a fully capitated managed care program managed by a dental plan. Main Outcomes and Measures: The rate of nontraumatic dental emergency department visits per 100 000 pediatric Medicaid enrollees and the associated mean charges per visit. Nontraumatic dental emergency department visits are a well-documented proxy for access to dental care. Data on emergency department visit counts came from the Florida Agency for Health Care Administration. Medicaid population denominators were derived from the American Community Survey's 5-year estimates. Results: Among the 34 414 pediatric nontraumatic dental emergency department visits that met inclusion criteria across Florida's 67 counties, the mean (SD) age of patients was 8.11 (5.28) years, and 50.8% of patients were male. Of these, 10 087 visits occurred in control counties and 24 327 in treatment counties. Control counties generally had lower rates of NTDC ED visits per 100 000 enrollees compared with treatment counties (123.5 vs 132.7). Over the first 2.5 years of implementation, the adoption of managed care was associated with an 11.3% (95% CI, 4.0%-18.4%; P = .002) increase in nontraumatic dental emergency department visits compared with pre-implementation levels. There was no evidence that the average charge per visit changed. Conclusions and Relevance: In this cohort study, Florida Medicaid's adoption of managed care for pediatric dental services was associated with increased emergency department visits for children, which could be associated with decreased access to dental care.

Sources of variation in nutrient loads collected through street sweeping in the Minneapolis-St. Paul Metropolitan Area, Minnesota, USA.

Excess non-point nutrient loading continues to impair urban surface waters. Because of the potential contribution of tree litterfall to nutrient pollution in stormwater, street sweeping is a promising management tool for reducing eutrophication in urban and suburban regions. However, nutrient concentrations and loads of material removed through street sweeping have not been well characterized, impeding the development of pollution reduction credits and improvement of models for stormwater management. We evaluated the role of canopy cover over streets, street sweeper type, season, and sweeping frequency in contributing to variation in concentrations and loads of nitrogen (N), phosphorus (P), and solids recovered in street sweepings, using analyses of samples collected during regular street sweeping operations in five cities in the Minneapolis-St. Paul Metropolitan Area, Minnesota, USA. We expected that nutrient concentrations and loads would be highest in seasons and places of higher tree litterfall. We also expected that regenerative-air sweepers would recover higher loads compared to mechanical broom sweepers. Total N and P concentrations in sweepings increased most strongly with canopy cover in June, October, and November. Total N and P recovered in street sweepings similarly increased with canopy cover in June, October, and November, and peaked in early summer and autumn, times of high litterfall. In contrast, total dry mass in sweepings was greatest in early spring, following winter snowmelt. However, nutrient loads and concentrations did not differ between sweeper types. Our results add to growing evidence of the importance of street trees in contributing nutrient pollution to urban surface waters. Street sweeping focused on high-canopy streets during early summer and autumn is likely an effective management tool for stormwater nutrient pollution.

The U.S. Equity-First Vaccination Initiative: Impacts and Lessons Learned.

The one-year U.S. Equity-First Vaccination Initiative (EVI), launched in April 2021, aimed to reduce racial inequities in coronavirus disease 2019 (COVID-19) vaccination across five demonstration cities (Baltimore, Chicago, Houston, Newark, and Oakland) and over the longer term strengthen the United States' public health system to achieve more-equitable outcomes. This initiative comprised nearly 100 community-based organizations (CBOs), who led hyper-local work to increase vaccination access and confidence in communities of individuals who identify as Black, Indigenous, and People of Color. In this study, the second of two on the initiative, the authors examine the results of the EVI. They look at the initiative's activities, effects, and challenges, and provide recommendations for how to support and sustain this hyper-local community-led approach and strengthen the public health system in the United States.

Strategies to Improve the Impact of Artificial Intelligence on Health Equity: Scoping Review.

BACKGROUND: Emerging artificial intelligence (AI) applications have the potential to improve health, but they may also perpetuate or exacerbate inequities. OBJECTIVE: This review aims to provide a comprehensive overview of the health equity issues related to the use of AI applications and identify strategies proposed to address them. METHODS: We searched PubMed, Web of Science, the IEEE (Institute of Electrical and Electronics Engineers) Xplore Digital Library, ProQuest U.S. Newsstream, Academic Search Complete, the Food and Drug Administration (FDA) website, and ClinicalTrials.gov to identify academic and gray literature related to AI and health equity that were published between 2014 and 2021 and additional literature related to AI and health equity during the COVID-19 pandemic from 2020 and 2021. Literature was eligible for inclusion in our review if it identified at least one equity issue and a corresponding strategy to address it. To organize and synthesize equity issues, we adopted a 4-step AI application framework: Background Context, Data Characteristics, Model Design, and Deployment. We then created a many-to-many mapping of the links between issues and strategies. RESULTS: In 660 documents, we identified 18 equity issues and 15 strategies to address them. Equity issues related to Data Characteristics and Model Design were the most common. The most common strategies recommended to improve equity were improving the quantity and quality of data, evaluating the disparities introduced by an application, increasing model reporting and transparency, involving the broader community in AI application development, and improving governance. CONCLUSIONS: Stakeholders should review our many-to-many mapping of equity issues and strategies when planning, developing, and implementing AI applications in health care so that they can make appropriate plans to ensure equity for populations affected by their products. AI application developers should consider adopting equity-focused checklists, and regulators such as the FDA should consider requiring them. Given that our review was limited to documents published online, developers may have unpublished knowledge of additional issues and strategies that we were unable to identify.

Increasing Subsidies and Expanding Health Insurance Options in Connecticut.

Policymakers in Connecticut are considering various options to increase the affordability of insurance in the state, such as expansions to premium and cost-sharing reduction subsidies on the state's health insurance marketplace, as well as expanded plan offerings, including extending eligibility for the state employee health plan (SEHP) to other groups and a publicly contracted, privately operated plan (the public option plan) offered to individuals on the marketplace. The authors used the RAND Corporation's COMPARE microsimulation model to estimate the impacts of such policy options. For each policy scenario, they calculated enrollment, premiums, consumer spending, and state spending and considered whether the results differed by race, ethnicity, or income group. The individual market reforms substantially increased affordability for people with incomes between 175 and 200 percent of the federal poverty level (FPL), reducing out-of-pocket spending as a share of income by 50 percent in some scenarios. Changes to affordability for higher-income groups were smaller, in part because the proposed policy changes for people with incomes between 200 and 400 percent of FPL were relatively modest and focused only on reducing cost-sharing (not premiums). New costs to the state for 2023 ranged from $19 million to $94 million, depending on the scenario. All four SEHP specifications led to the same bottom-line conclusion that offering a SEHP plan would improve insurance coverage and affordability for those eligible for the plan. Expanding eligibility for the SEHP holds promise for stabilizing or reducing consumer costs, improving plan generosity, and bringing more people into the market.

Racial And Ethnic Disparities In COVID-19 Booster Uptake.

We investigated racial and ethnic disparities in COVID-19 vaccine uptake, using data from the Centers for Disease Control and Prevention. As of March 29, 2022, uptake of the first dose was higher among Hispanic and Asian people than among White and Black people. In contrast, uptake rates of the booster were higher among Asian and White people than among Black and Hispanic people.

Reopening Under Uncertainty: Stress-Testing California's COVID-19 Exit Strategy.

The coronavirus disease 2019 pandemic required significant public health interventions from local governments. Early in the pandemic, RAND researchers developed a decision support tool to provide policymakers with insight into the trade-offs they might face when choosing among nonpharmaceutical intervention levels. Using an updated version of the model, the researchers performed a stress-test of a variety of alternative reopening plans, using California as an example. This article presents the general lessons learned from these experiments and discusses four characteristics of the best reopening strategies.

Artificial intelligence applications used in the clinical response to COVID-19: A scoping review.

Research into using artificial intelligence (AI) in health care is growing and several observers predicted that AI would play a key role in the clinical response to the COVID-19. Many AI models have been proposed though previous reviews have identified only a few applications used in clinical practice. In this study, we aim to (1) identify and characterize AI applications used in the clinical response to COVID-19; (2) examine the timing, location, and extent of their use; (3) examine how they relate to pre-pandemic applications and the U.S. regulatory approval process; and (4) characterize the evidence that is available to support their use. We searched academic and grey literature sources to identify 66 AI applications that performed a wide range of diagnostic, prognostic, and triage functions in the clinical response to COVID-19. Many were deployed early in the pandemic and most were used in the U.S., other high-income countries, or China. While some applications were used to care for hundreds of thousands of patients, others were used to an unknown or limited extent. We found studies supporting the use of 39 applications, though few of these were independent evaluations and we found no clinical trials evaluating any application's impact on patient health. Due to limited evidence, it is impossible to determine the extent to which the clinical use of AI in the pandemic response has benefited patients overall. Further research is needed, particularly independent evaluations on AI application performance and health impacts in real-world care settings.

A transition management framework to stimulate a circular phosphorus system.

As the global population is projected to increase by two billion people by 2050, so will the demand for phosphorus (P), an essential nutrient for all living organisms and a major driver of eutrophication. To sustainably meet these challenges, we apply the conceptual framework of transition management (TM) to demonstrate how the trajectory of the current linear P use system could be strategically shifted toward a more circular P system. We present US case studies to examine P transitions management in intensive agriculture, wastewater disposal, and food waste management. Our goal is twofold. By first understanding past transitions in P management in the USA, we can build upon these insights for future management. This can then be applied to other global regions such as developing countries to bypass stages of transition as they intensify agriculture, incorporate sewers into cities, and expand waste management, to avoid becoming entrenched in unsustainable P management. We suggest how spaces for experimentation and collaboration can be created, how and which actor networks can be mobilized, and what action strategies and policies can be recommended to accelerate their transition to P sustainability. Our case studies show that while substantial improvements have been made, the transition toward a circular economy of P is far from complete. Our findings point to the value of utilizing TM for future progress in the US Development of TM frameworks for managing P in other regions of the world may enable them to achieve sustainable P development faster and more effectively than the USA.

Reopening California: Seeking robust, non-dominated COVID-19 exit strategies.

The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty.

Reopening California : Seeking Robust, Non-Dominated COVID-19 Exit Strategies.

Amid global scarcity of COVID-19 vaccines and the threat of new variant strains, California and other jurisdictions face the question of when and how to implement and relax COVID-19 Nonpharmaceutical Interventions (NPIs). While policymakers have attempted to balance the health and economic impacts of the pandemic, decentralized decision-making, deep uncertainty, and the lack of widespread use of comprehensive decision support methods can lead to the choice of fragile or inefficient strategies. This paper uses simulation models and the Robust Decision Making (RDM) approach to stress-test California's reopening strategy and other alternatives over a wide range of futures. We find that plans which respond aggressively to initial outbreaks are required to robustly control the pandemic. Further, the best plans adapt to changing circumstances, lowering their stringent requirements to reopen over time or as more constituents are vaccinated. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower.

Data-driven curation process for describing the blood glucose management in the intensive care unit.

Analysis of real-world glucose and insulin clinical data recorded in electronic medical records can provide insights into tailored approaches to clinical care, yet presents many analytic challenges. This work makes publicly available a dataset that contains the curated entries of blood glucose readings and administered insulin on a per-patient basis during ICU admissions in the Medical Information Mart for Intensive Care (MIMIC-III) database version 1.4. Also, the present study details the data curation process used to extract and match glucose values to insulin therapy. The curation process includes the creation of glucose-insulin pairing rules according to clinical expert-defined physiologic and pharmacologic parameters. Through this approach, it was possible to align nearly 76% of insulin events to a preceding blood glucose reading for nearly 9,600 critically ill patients. This work has the potential to reveal trends in real-world practice for the management of blood glucose. This data extraction and processing serve as a framework for future studies of glucose and insulin in the intensive care unit.

Modeling COVID-19 Nonpharmaceutical Interventions: Exploring periodic NPI strategies.

We developed a COVID-19 transmission model used as part of RAND's web-based COVID-19 decision support tool that compares the effects of nonpharmaceutical public health interventions (NPIs) on health and economic outcomes. An interdisciplinary approach informed the selection and use of multiple NPIs, combining quantitative modeling of the health/economic impacts of interventions with qualitative assessments of other important considerations (e.g., cost, ease of implementation, equity). This paper provides further details of our model, describes extensions, presents sensitivity analyses, and analyzes strategies that periodically switch between a base NPI level and a higher NPI level. We find that a periodic strategy, if implemented with perfect compliance, could have produced similar health outcomes as static strategies but might have produced better outcomes when considering other measures of social welfare. Our findings suggest that there are opportunities to shape the tradeoffs between economic and health outcomes by carefully evaluating a more comprehensive range of reopening policies.

Could periodic nonpharmaceutical intervention strategies produce better COVID-19 health and economic outcomes?

We developed a COVID-19 transmission model to compare the effects of nonpharmaceutical public health interventions (NPIs) on health and economic outcomes. An interdisciplinary approach informed the selection and use of multiple NPIs, combining quantitative modeling of the health and economic impacts of interventions with qualitative assessments of other important considerations (e.g., cost, ease of implementation, equity). We used our model to analyzed strategies that periodically switch between a base NPI and a high NPI level. We find that this systematic strategy could have produced similar health outcomes as static strategies but better social welfare and economic outcomes. Our findings suggest that there are opportunities to shape the tradeoffs between economic and health outcomes by carefully evaluating a more comprehensive range of reopening policies.

Desarrollamos un modelo de transmisión de COVID-19 para comparar los efectos de las intervenciones de salud pública (NPI) no farmacéuticas en los resultados económicos y de salud. Un enfoque interdisciplinario informó la selección y el uso de múltiples ISFL, combinando modelos cuantitativos de los impactos económicos y de salud de las intervenciones con evaluaciones cualitativas de otras consideraciones importantes (por ejemplo, costo, facilidad de implementación, equidad). Usamos nuestro modelo para analizar estrategias que cambian periódicamente entre un NPI base y un nivel alto de NPI. Encontramos que esta estrategia sistemática podría haber producido resultados de salud similares a los de las estrategias estáticas, pero mejores resultados económicos y de bienestar social. Nuestros hallazgos sugieren que existen oportunidades para dar forma a las compensaciones entre los resultados económicos y de salud al evaluar cuidadosamente una gama más completa de políticas de reapertura.

Estimating the Cost of Industry Investment in Drug Research and Development: A Review of Methods and Results.

Research and development (R&D) costs factor into considerations of the tradeoffs between prices, intellectual property protection, and incentivizing innovation, all of which can have implications for policy development. Yet, there is little consensus on the actual cost of R&D for new drugs. We review and synthesize papers estimating drug R&D costs incurred by industry. We find a substantial range of per-drug costs, from $113 million to just over $6 billion in 2018 dollars. This range includes estimates covering all new drugs, new molecular entities, and drugs in specific therapeutic classes. The range is narrower-$318 million to $2.8 billion-for estimates of the per-drug cost for new molecular entities. We discuss the data sources, methods, and assumptions used in each study to provide context for the wide range in existing estimates. Differences in definitions, methods, and assumptions lead to large divergences in the main estimates, and the combination of fragmented data sources and different assumptions across studies means that the resulting estimates that can rarely be directly compared. We suggest areas for future research and data collection that would result in more comparable and robust estimates to inform ongoing policy discussion.

Real-world characterization of blood glucose control and insulin use in the intensive care unit.

The heterogeneity of critical illness complicates both clinical trial design and real-world management. This complexity has resulted in conflicting evidence and opinion regarding the optimal management in many intensive care scenarios. Understanding this heterogeneity is essential to tailoring management to individual patients. Hyperglycaemia is one such complication in the intensive care unit (ICU), accompanied by decades of conflicting evidence around management strategies. We hypothesized that analysis of highly-detailed electronic medical record (EMR) data would demonstrate that patients vary widely in their glycaemic response to critical illness and response to insulin therapy. Due to this variability, we believed that hyper- and hypoglycaemia would remain common in ICU care despite standardised approaches to management. We utilized the Medical Information Mart for Intensive Care III v1.4 (MIMIC) database. We identified 19,694 admissions between 2008 and 2012 with available glucose results and insulin administration data. We demonstrate that hyper- and hypoglycaemia are common at the time of admission and remain so 1 week into an ICU admission. Insulin treatment strategies vary significantly, irrespective of blood glucose level or diabetic status. We reveal a tremendous opportunity for EMR data to guide tailored management. Through this work, we have made available a highly-detailed data source for future investigation.

Estimated energy and nutrient composition of different sources of food waste and their potential for use in sustainable swine feeding programs.

About 40% of the total food produced in the United States is wasted throughout the supply chain. The objective of this study was to determine the energy and nutrient content and variability of food waste sources generated at different stages within the food supply chain in the Minneapolis-St. Paul, MN, metropolitan area, and their potential for use in swine diets. A total of four waste sources were selected: supermarket (SM; retail to consumer), university residential dining hall (RH; consumer to postconsumer), a city waste transfer station (TS; postconsumer to municipal waste disposal), and household source-separated organic recycling program (SSO; postconsumer to municipal waste). Samples were collected (SM: n = 22; RH: n = 60; TS: n = 27; SSO: n =12) and analyzed for GE, proximate analyses, minerals, amino acids, and fatty acid concentrations along with lipid peroxidation indicators including peroxide value (PV) and thiobarbituric reactive substances (TBARS). Data were analyzed using a general linear model that included food waste source as the main factor, and least squared means with adjustment were used for multiple comparisons. Samples of SM food waste contained the greatest (P < 0.05) concentration of GE (5,909 kcal/kg) compared with RH, TS, and SSO sources. Calculated NE of SM (3,740 kcal/kg) was also the greatest compared with the three other food waste sources. Food waste from SM, RH, and SSO, but not TS, had greater (P < 0.05) calculated NE than published values for corn and soybean meal. Concentrations of Lys (1.82%), Met (0.53%), Thr (1.07%), and Trp (0.27) content were greater in SM than in RH, TS, and SSO, but these concentrations were less than published values for soybean meal. There were no differences (P > 0.05) in the phosphorus content of samples among food waste sources (0.30% to 0.64%). PV and TBARS were greatest (P < 0.05) in the SSO samples (PV = 82.4 meq/kg oil; TBARS = 2.44 mg malondialdehyde (MDA) eq/g oil) compared with the other three food waste sources. Although the concentrations of nutrients and calculated energy values of the food waste sources were moderately high compared with corn and soybean meal, their composition was more variable (i.e., greater SD of means). Food waste generated upstream (SM) in the food supply chain appears to have greater nutritional value than postconsumer food waste (RH, TS, and SSO), but all sources appear suitable for use in commercial swine diets provided that ME, NE, and nutrient digestibility values are well characterized.