Multiple US States Research Articles

Ensemble modeling of the climate-energy nexus for renewable energy generation across multiple US states

Abstract The effects of climate change on renewable energy generation are of growing concern, as shifts in weather patterns and extreme events can significantly impact energy production. This study aims to leverage machine learning models to predict renewable energy generation based on the surrounding climate. We analyze data from four key states: California, New York, Florida, and Georgia, and focus on three critical renewable energy sources: hydroelectric, solar, and wind power. To determine the optimal model, we test six primary machine learning techniques, as well as an ensemble and a mean-only baseline. The results indicate that the ensemble approach improves the predictive accuracy of the model. Using this ensemble, we projected the changes to climate-sensitive portion of the renewable energy generation under climate change. Our results indicated that there was a wide variation of possible futures, depending on the state, source, and season. For example, the model projected a reduction in California's monthly total renewable energy generation in the summer by 0.5%, or about 30,000 MWh, under SSP5-8.5, the worst-case scenario, but an increase of 0.5%, or about 25,000 MWh, in New York's monthly total summer renewable energy generation under the same scenario.The modeling techniques detailed in this study can be applied across new regions, sources, or time periods. Ultimately, by understanding the influence of climate on renewable energy generation, we can improve the long-term planning process for the electricity grid, while building resilience and ensuring sustainable climate change mitigation and adaptation.

Clinical Course, Antifungal Susceptibility, and Genomic Sequencing of Trichophyton indotineae

Trichophyton indotineae is an emerging dermatophyte causing outbreaks of extensive tinea infections often unresponsive to terbinafine. This species has been detected worldwide and in multiple US states, yet detailed US data on infections with T indotineae are sparse and could improve treatment practices and medical understanding of transmission. To correlate clinical features of T indotineae infections with in vitro antifungal susceptibility testing results, squalene epoxidase gene sequence variations, and isolate relatedness using whole-genome sequencing. This retrospective cohort study of patients with T indotineae infections in New York City spanned May 2022 to May 2023. Patients with confirmed T indotineae infections were recruited from 6 New York City medical centers. Improvement or resolution at the last follow-up assessment. Among 11 patients with T indotineae (6 male and 5 female patients; median [range] age, 39 [10-65] years), 2 were pregnant; 1 had lymphoma; and the remainder were immunocompetent. Nine patients reported previous travel to Bangladesh. All had widespread lesions with variable scale and inflammation, topical antifungal monotherapy failure, and diagnostic delays (range, 3-42 months). Terbinafine treatment failed in 7 patients at standard doses (250 mg daily) for prolonged duration; these patients also had isolates with amino acid substitutions at positions 393 (L393S) or 397 (F397L) in squalene epoxidase that correlated with elevated terbinafine minimum inhibitory concentrations of 0.5 μg/mL or higher. Patients who were treated with fluconazole and griseofulvin improved in 2 of 4 and 2 of 5 instances, respectively, without correlation between outcomes and antifungal minimum inhibitory concentrations. Furthermore, 5 of 7 patients treated with itraconazole cleared or had improvement at the last follow-up, and 2 of 7 were lost to follow-up or stopped treatment. Based on whole-genome sequencing analysis, US isolates formed a cluster distinct from Indian isolates. The results of this case series suggest that disease severity, diagnostic delays, and lack of response to typically used doses and durations of antifungals for tinea were common in this primarily immunocompetent patient cohort with T indotineae, consistent with published data. Itraconazole was generally effective, and the acquisition of infection was likely in Bangladesh.

Code is law: how COMPAS affects the way the judiciary handles the risk of recidivism

AbstractJudges in multiple US states, such as New York, Pennsylvania, Wisconsin, California, and Florida, receive a prediction of defendants’ recidivism risk, generated by the COMPAS algorithm. If judges act on these predictions, they implicitly delegate normative decisions to proprietary software, even beyond the previously documented race and age biases. Using the ProPublica dataset, we demonstrate that COMPAS predictions favor jailing over release. COMPAS is biased against defendants. We show that this bias can largely be removed. Our proposed correction increases overall accuracy, and attenuates anti-black and anti-young bias. However, it also slightly increases the risk that defendants are released who commit a new crime before tried. We argue that this normative decision should not be buried in the code. The tradeoff between the interests of innocent defendants and of future victims should not only be made transparent. The algorithm should be changed such that the legislator and the courts do make this choice.

Anaplasma bovis-Like Infections in Humans, United States, 2015-2017.

We detected the DNA of an Anaplasma bovis-like bacterium in blood specimens from 4 patients from the United States with suspected tickborne illnesses. Initial molecular characterization of this novel agent reveals identity to A. bovis-like bacteria detected in Dermacentor variabilis ticks collected from multiple US states.

Patterns in the Development of Pediatric Allergy.

Describe clinical and epidemiologic patterns of pediatric allergy using longitudinal electronic health records (EHRs) from a multistate consortium of US practices. Using the multistate Comparative Effectiveness Research through Collaborative Electronic Reporting EHR database, we defined a cohort of 218 485 children (0-18 years) who were observed for ≥5 years between 1999 and 2020. Children with atopic dermatitis (AD), immunoglobulin E-mediated food allergy (IgE-FA), asthma, allergic rhinitis (AR), and eosinophilic esophagitis (EoE) were identified using a combination of diagnosis codes and medication prescriptions. We determined age at diagnosis, cumulative incidence, and allergic comorbidity. Allergic disease cumulative (and peak age of) incidence was 10.3% (4 months) for AD, 4.0% (13 months) for IgE-FA, 20.1% (13 months) for asthma, 19.7% (26 months) for AR, and 0.11% (35 months) for EoE. The most diagnosed IgE-FAs were peanut (1.9%), egg (0.8%), and shellfish (0.6%). A total of 13.4% of children had ≥2 allergic conditions, and respiratory allergies (ie, asthma, AR) were commonly comorbid with each other, and with other allergic conditions. We detail pediatric allergy patterns using longitudinal, health care provider-based data from EHR systems across multiple US states and varied pediatric practice types. Our results support the population-level allergic march progression and indicate high rates of comorbidity among children with food and respiratory allergies.

Cannabis Retail Market Indicators in Five Legal States in the United States: A Public Health Perspective

Adult-use cannabis markets are operating in multiple US states and abroad. Sales and licensing data for alcohol and tobacco are often used to understand consumption patterns and evaluate policy changes. Cannabis market data may provide similar insights, although these newly legal markets are complex and evolving, and the state data structures can differ. This study describes variations in market indicators and discusses the utility of cannabis market metrics from a public health perspective. We collected data from 5 early-adopting adult-use cannabis states: Alaska, Colorado, Massachusetts, Oregon, and Washington. Analyses focused on licensed retail outlets and retail sales revenues (pretax). Monthly data were collected from the opening of each state's adult-use market through June 2022. Joinpoint software was used to assess state trends and identify points of inflection in trends. Average sales per retailer for June 2019 and June 2022 were compared. Also described are retailers and revenue per population for 2022. All states showed 4 distinct periods of growth in retail licensee numbers. The greatest increases typically occurred in the first 3 to 4 months. Growth rates slowed to <1% per month for Colorado, Oregon, and Washington at months 25, 24, and 34, respectively. The number of cannabis retailers per 100,000 residents in June 2022 ranged widely, from 16.8 in Oregon to 3.0 in Massachusetts. Colorado, Oregon, and Washington each showed 4 distinct trend periods in adult-use retail sales: early rapid growth lasting <1 year, subsequent varied growth periods, and then declining sales in the most recent months, following early coronavirus disease 2019 period increases. Sales in Alaska and Massachusetts displayed more stable, consistent growth patterns. Sales per state resident for July 2021 to June 2022 also ranged widely, from $382.97 in Alaska to $180.94 in Washington. We found some consistencies and some variations in both point-in-time measures and trends in states' adult-use cannabis markets. Differences may relate to varied state policies and general contexts (eg, economies). Market data can be useful for public health monitoring, including understanding the effects of policies intended to protect health and safety. States providing publicly accessible cannabis market data create opportunities for such use. Our results underscore the importance of considering individual state regulatory frameworks and implementation timelines in studies of cannabis legalization.

Short term exposure to air pollution and mortality in the US: a double negative control analysis

RationaleStudies examining the association of short-term air pollution exposure and daily deaths have typically been limited to cities and used citywide average exposures, with few using causal models.ObjectivesTo estimate the associations between short-term exposures to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) and all-cause and cause-specific mortality in multiple US states using census tract or address exposure and including rural areas, using a double negative control analysis.MethodsWe conducted a time-stratified case-crossover study examining the entire population of seven US states from 2000–2015, with over 3 million non-accidental deaths. Daily predictions of PM2.5, O3, and NO2 at 1x1 km grid cells were linked to mortality based on census track or residential address. For each pollutant, we used conditional logistic regression to quantify the association between exposure and the relative risk of mortality conditioning on meteorological variables, other pollutants, and using double negative controls.ResultsA 10 μg/m3 increase in PM2.5 exposure at the moving average of lag 0–2 day was significantly associated with a 0.67% (95%CI: 0.34–1.01%) increase in all-cause mortality. 10 ppb increases in NO2 or O3 exposure at lag 0–2 day were marginally associated with and 0.19% (95%CI: −0.01-0.38%) and 0.20 (95% CI-0.01, 0.40), respectively. The adverse effects of PM2.5 persisted when pollution levels were restricted to below the current global air pollution standards. Negative control models indicated little likelihood of omitted confounders for PM2.5, and mixed results for the gases. PM2.5 was also significantly associated with respiratory mortality and cardiovascular mortality.ConclusionsShort-term exposure to PM2.5 and possibly O3 and NO2 are associated with increased risks for all-cause mortality. Our findings delivered evidence that risks of death persisted at levels below currently permissible.

Unrecognized introductions of SARS-CoV-2 into the US state of Georgia shaped the early epidemic.

In early 2020, as diagnostic and surveillance responses for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ramped up, attention focused primarily on returning international travelers. Here, we build on existing studies characterizing early patterns of SARS-CoV-2 spread within the USA by analyzing detailed clinical, molecular, and viral genomic data from the state of Georgia through March 2020. We find evidence for multiple early introductions into Georgia, despite relatively sparse sampling. Most sampled sequences likely stemmed from a single or small number of introductions from Asia three weeks prior to the state’s first detected infection. Our analysis of sequences from domestic travelers demonstrates widespread circulation of closely related viruses in multiple US states by the end of March 2020. Our findings indicate that the exclusive focus on identifying SARS-CoV-2 in returning international travelers early in the pandemic may have led to a failure to recognize locally circulating infections for several weeks and point toward a critical need for implementing rapid, broadly targeted surveillance efforts for future pandemics.

Perfluorooctane Sulfonate in US Ambient Surface Waters: A Review of Occurrence in Aquatic Environments and Comparison to Global Concentrations

Perfluorooctane sulfonate (PFOS) is one of the dominant perfluoroalkyl substances (PFAS) detected in aquatic ecosystems. It has been used in a wide range of industrial and consumer products for decades. The unique properties of PFOS, including its stability and resistance to degradation, have made it highly persistent in the aquatic environment. Because of its persistence, potential toxicity, and occurrence in aquatic ecosystems, interest in PFOS has increased in recent decades. Despite this interest, current information on the environmental distribution of PFOS in ambient surface waters of the United States is fairly limited. This critical review summarizes the currently available literature on PFOS occurrence in surface waters across the United States and highlights existing data gaps. Available data are largely from a handful of study areas with known PFAS manufacturing or industrial uses, with much of the data collected from freshwater systems in eastern states and the upper Midwest. Measured PFOS concentrations in surface waters vary widely, over 8 orders of magnitude, with the highest concentrations occurring downstream from manufacturing and industrial use plants, areas near aqueous film-forming foam-use sites, and sites where PFOS precursors were used in textile treatment. Non-point source-related occurrences are highest near urbanized areas with high population densities. Current data illustrate the occurrence of PFOS in surface waters across multiple US states. Additional data are needed to better understand PFOS occurrence in US aquatic ecosystems, particularly in estuarine and marine systems and where monitoring data are not available (e.g., southwestern, central, and western United States). Additional PFOS occurrence data would provide valuable information on potential spatial and temporal variability in surface waters and possible risks posed to aquatic ecosystems. Environ Toxicol Chem 2021;40:2425-2442. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

Life-limiting fetal conditions and pregnancy continuation: parental decision-making processes

ObjectivesWhen parents are facing a life-limiting fetal condition (LLFC), decision making about prenatal and neonatal care is very stressful. To participate in successful shared decision making, interdisciplinary care teams need...

The Effects of Social Distancing Policies on Non-SARS-CoV-2 Respiratory Pathogens.

BackgroundThe initial focus of the US public health response to coronavirus disease 2019 (COVID-19) was the implementation of numerous social distancing policies. While COVID-19 was the impetus for imposing these policies, it is not the only respiratory disease affected by their implementation. This study aimed to assess the impact of social distancing policies on non–severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) respiratory pathogens typically circulating across multiple US states.MethodsLinear mixed-effect models were implemented to explore the effects of 5 social distancing policies on non-SARS-CoV-2 respiratory pathogens across 9 states from January 1 through May 1, 2020. The observed 2020 pathogen detection rates were compared week by week with historical rates to determine when the detection rates were different.ResultsModel results indicate that several social distancing policies were associated with a reduction in total detection rate, by nearly 15%. Policies were associated with decreases in pathogen circulation of human rhinovirus/enterovirus and human metapneumovirus, as well as influenza A, which typically decrease after winter. Parainfluenza viruses failed to circulate at historical levels during the spring. The total detection rate in April 2020 was 35% less than the historical average. Many of the pathogens driving this difference fell below the historical detection rate ranges within 2 weeks of initial policy implementation.ConclusionsThis analysis investigated the effect of multiple social distancing policies implemented to reduce transmission of SARS-CoV-2 on non-SARS-CoV-2 respiratory pathogens. These findings suggest that social distancing policies may be used as an impactful public health tool to reduce communicable respiratory illness.

Hidden Parameters Impacting&amp;nbsp;Resurgence of SARS-CoV-2 Pandemic

The spread of the SARS-CoV-2 virus has had an enormous impact on the world's health and socioeconomic system. While a lockdown, which severely limits the movement of the population, has been implemented in March 2020 and again in late 2020, the psychological and economic costs are severe. Removal of these restrictions had varying degrees of success. To understand the impact of health policy, we study parameters that contribute to the resurgence of the virus upon removal of lockdown. Mandates and guidance on removal of lockdown varied across the United States. Along with social distancing mandates, active infections and the fraction of susceptible population remaining are identified as important factors in the resurgence of infections. We consider an epidemiological model that incorporates the set of people in lockdown, a population that is released linearly upon removal of lockdown. This model further incorporates a dynamic social distance metric based on progression of the infections; it reflects the dynamic propensity of infection spread based on the current infections relative to the susceptible population. It is determined that this model fits the data with more accuracy than the standard SIR model, where data on growth of infections, hospitalizations and death was obtained from 24 counties in multiple US states, along with a categorization of the lockdown removal policies after the first lockdown. Mobility data from the counties illustrates the relationship between policy mandates and visits to establishments like restaurants and personal care establishments. Model parameters are used to determine the rate at which the susceptible population increases, due to removal of lockdown, to fit the rate of infections. We also studied infection growth in the 24 US counties with respect to a two-phase release policy derived from CDC guidelines and compared against strategies that delay the removal of lockdown. Results: The efficacy of the lockdown removal policy is measured via a ratio, Peak Infection Ratio (PIR). This ratio evaluates to less than one for counties where social distancing measures were mandated and which delayed complete re-opening of closed spaces like restaurants and personal care establishments. For other counties this ratio is greater than one. Our results also show that not all counties respected the two-phase policy rule that we devised using CDC guidelines. Furthermore, delaying reopening in these counties by 30 days would have resulted in at least 40% less infections. Conclusions: Results illustrate that guidelines for deciding when lockdown rules are to be relaxed should consider the current state of the actively infectious population and the remaining susceptible population which are hidden parameters that are deducible from epidemiological models such as the one we consider, the SIR-SD-L model. This contrasts with policies that measure the reduction in growth of infections; the growth rate being correlated primarily to immediate non-pharmaceutical (NPI) interventions. This is especially true for counties where the growth rate of the virus is initially slow and misleading. Emphasis and mandates on social distancing is critical. Funding Statement: Research sponsored by NSF. grant No. 2028274. Declaration of Interests: None to declare.

Association of Homelessness with Hospital Readmissions-an Analysis of Three Large States.

Individuals experiencing homelessness have higher hospitalization and mortality rates compared with the housed. Whether they also experience higher readmission rates, and if readmissions vary by region or cause of hospitalization is unknown. Evaluate the association of homelessness with readmission rates across multiple US states. Retrospective analysis of administrative claims PATIENTS: All inpatient hospitalizations in Florida, Massachusetts, and New York from January 2010 to October 2015 MAIN MEASURES: Thirty- and 90-day readmission rates KEY RESULTS: Out of a total of 23,103,125 index hospitalizations, 515,737 were for patients who were identified as homeless at the time of discharge. After adjusting for cause of index hospitalization, state, demographics, and clinical comorbidities, 30-day and 90-day readmission rates were higher for index hospitalizations in the homeless compared with those in the housed group. The difference in 30-day readmission rates between homeless and housed groups was the largest in Florida (30.4% vs. 19.3%; p < 0.001), followed by Massachusetts (23.5% vs. 15.2%; p < 0.001) and New York (15.7% vs. 13.4%; p < 0.001) (combined 17.3% vs. 14.0%; p < 0.001). Among the most common causes of hospitalization, 30-day readmission rates were 4.1 percentage points higher for the homeless group for mental illness, 4.9 percentage points higher for diseases of the circulatory system, and 2.4 percentage points higher for diseases of the digestive system. After adjusting for demographic and clinical characteristics, homelessness is associated with significantly higher 30- and 90-day readmission rates, with a significant variation across the three states. Interventions to reduce the burden of readmissions among individuals experiencing homelessness are urgently needed. Differences across states point to the potential of certain public policies to impact health outcomes for individuals experiencing homelessness.

Gender Norms, Roles and Relations and Cannabis-Use Patterns: A Scoping Review.

Currently, boys and men use cannabis at higher rates than girls and women, but the gender gap is narrowing. With the legalization of recreational cannabis use in Canada and in multiple US states, these trends call for urgent attention to the need to consider how gender norms, roles and relations influence patterns of cannabis use to inform health promotion and prevention responses. Based on a scoping review on sex, gender and cannabis use, this article consolidates existing evidence from the academic literature on how gender norms, roles and relations impact cannabis-use patterns. Evidence is reviewed on: adherence to dominant masculine and feminine norms and cannabis-use patterns among adolescents and young adults, and how prevailing norms can be both reinstated or reimagined through cannabis use; gendered social dynamics in cannabis-use settings; and the impact of gender roles and relations on cannabis use among young adults of diverse sexual orientations and gender identities. Findings from the review are compared and contrasted with evidence on gender norms, roles and relations in the context of alcohol and tobacco use. Recommendations for integrating gender transformative principles in health promotion and prevention responses to cannabis use are provided.

Transcription-mediated amplification blood donation screening for Babesia.

Transfusion-transmitted Babesia microti is well recognized in the Northeast and upper Midwestern United States. Blood donation screening in Babesia-endemic states has occurred under investigational protocols prior to US Food and Drug Administration-licensed test availability. Here, we provide a prospective screening summary of nucleic acid testing (NAT) as part of a multicenter Babesia pivotal trial followed by extended investigational use. From June 2017 to February 2018, 176,928 donation samples were tested with Procleix Babesia Assay (Grifols Diagnostic Solutions), a blood screening NAT for Babesia species ribosomal RNA detection using whole blood samples. During the pivotal trial, donations were collected in 11 endemic states plus Washington, DC, and Florida (nonendemic). Whole blood lysate samples were either tested in pools of 16 or individually. Reactive samples were confirmed by Babesia microti antibody and polymerase chain reaction (PCR) testing. If unconfirmed, further testing used a second PCR assay capable of detecting multiple Babesia species. Follow-up samples were also tested. Extended investigational testing followed pivotal trial completion. The pivotal trial identified 61 confirmed positives (176,608 donations): 35 (57%) PCR positive, 59 (97%) antibody positive, and two (3%) NAT positive/antibody negative, for a total yield of one positive per 2895 donations, including one Florida resident; others were from seven endemic states. During extended investigational testing of 496,270 donations in endemic states through January 2019, 211 (1:2351) repeat reactive donations were identified. Babesia was detected in donors from multiple US states, including one previously not associated with positive blood donors. This study supports the use of the Procleix Babesia Assay using individual testing or pools of up to 16.

Hepatitis B Virus Mutant Infections in Hemodialysis Patients: A Case Series

Rationale & ObjectiveHepatitis B virus (HBV) transmission in hemodialysis units has become a rare event since implementation of hemodialysis-specific infection control guidelines: performing hemodialysis for hepatitis B surface antigen (HBsAg)-positive patients in an HBV isolation room, vaccinating HBV-susceptible (HBV surface antibody and HBsAg negative) patients, and monthly HBsAg testing in HBV-susceptible patients. Mutations in HBsAg can result in false-negative HBsAg results, leading to failure to identify HBsAg seroconversion from negative to positive. We describe 4 unique cases of HBsAg seroconversion caused by mutant HBV infection or reactivation in hemodialysis patients.Study DesignFollowing identification of a possible HBsAg seroconversion and mutant HBV infection, public health investigations were launched to conduct further HBV testing of case patients and potentially exposed patients. A case patient was defined as a hemodialysis patient with suspected mutant HBV infection because of false-negative HBsAg testing results. Confirmed case patients had HBV DNA sequences demonstrating S-gene mutations.Setting & ParticipantsCase patients and patients potentially exposed to the case patient in the respective hemodialysis units in multiple US states.Results4 cases of mutant HBV infection in hemodialysis patients were identified; 3 cases were confirmed using molecular sequencing. Failure of some HBsAg testing platforms to detect HBV mutations led to delays in applying HBV isolation procedures. Testing of potentially exposed patients did not identify secondary transmissions.LimitationsLack of access to information on past HBsAg testing platforms and results led to challenges in ascertaining when HBsAg seroconversion occurred and identifying and testing all potentially exposed patients.ConclusionsMutant HBV infections should be suspected in patients who test HBsAg negative and concurrently test positive for HBV DNA at high levels. Dialysis providers should consider using HBsAg assays that can also detect mutant HBV strains for routine HBV testing.

Geographic modeling of best transport options for treatment of acute ischemic stroke patients applied to policy decision making in the USA and Northern Ireland

Ischemic stroke is a treatable disease with alteplase, a clot-busting medical treatment, and endovascular therapy (EVT), mechanical removal of the clot through a minimally invasive procedure. The effectiveness of both treatments is time dependent, and they are usually given together. Alteplase is less effective than EVT, but is widely available at community hospitals; EVT is highly effective, but it is only available at large urban tertiary hospitals. There is uncertainty if it is better to receive alteplase early and delay EVT or vice versa. We developed a conditional probability model based on decay curves that were generated from pooled clinical trials, and then created a software solution using C# that interfaced with ArcGIS’s Software Development Kit and Google’s Distance Matrix API. The maps were developed based on pre-specified time interval variables to determine the best transportation for multiple US states (Colorado, Arizona, Tennessee, and Massachusetts/Rhode Island) and Northern Ireland. The overall objective of this work was to determine if these maps could be used to influence health policy decision making for acute stroke patients.

PDB25 - Variation in Characteristics And A1C Outcomes of Patients with Type 2 Diabetes Mellitus (T2DM) Treated with Canagliflozin in Multiple US States: A Descriptive, Retrospective Cohort Study

PDB25 - Variation in Characteristics And A1C Outcomes of Patients with Type 2 Diabetes Mellitus (T2DM) Treated with Canagliflozin in Multiple US States: A Descriptive, Retrospective Cohort Study

Assessment of nutrition and physical activity practices using self-report and observation in early care and education across multiple US states.

The National Early Care and Education Learning Collaboratives (ECELC) Project aims to promote healthy physical activity and nutrition environments, policies and practices in early care and education (ECE) programmes across multiple states. The present pilot study sought to assess changes to the physical activity and nutrition practices in a sub-sample of ECE programmes participating in the ECELC using the Environment and Policy Assessment and Observation (EPAO). Additionally, it sought to compare results with the Nutrition and Physical Activity Self-Assessment for Child Care (NAP SACC). Quasi-experimental pre-post pilot study where paired-sample t tests examined changes to physical activity and nutrition practices from pre-assessment to post-assessment (P<0·05). Pearson correlation coefficients examined change scores from EPAO compared with NAP SACC with statistical significance set at a two-sided α level of P<0·10 to account for sample size. The study occurred among ECE programmes. Pre-school classrooms in nineteen ECE programmes across four US states were observed. EPAO data demonstrated an increase in total score from pre-assessment to post-assessment (150 (sd 30) to 176 (sd 35)). NAP SACC change scores demonstrated little relationship with EPAO domain change scores, with exceptions in Nutrition Policy and Physical Activity Policy (r=-0·4 and -0·6, respectively). The overall improvements reported through the EPAO suggest participation in the ECELC resulted in changes in critical nutrition- and physical activity-related practices. However, considerable differences in data reported using the NAP SACC compared with the EPAO suggest subjective data should be interpreted with caution and objective measurement should be used when feasible.

Assessing the Quality of Service Using Big Data Analytics

Abstract Many industries are riding the wave of big data as the new era of data-driven decision making is unveiling. The field of big data analytics is gaining fast traction in industry, academia and the government; the healthcare arena is no different. In this paper, big data analytics are applied to healthcare data that is collected from multiple sources to gain quality insights and apprehend best practices of the field (using new healthcare specific big data tools). The US states are unceasingly pursuing potential improvements to their healthcare's Quality of Service (QoS). Recent changes in data sharing provisions, such as the disposition of the recent Affordable Health Care Act (ACA), changed the rules of the game, and provided the US states with a new set of measurable health quality variables that they couldn't overlook anymore. Individuals in those states without health insurance tend to ignore visiting the clinic even if they feel symptoms of a disease; healthy young individuals with insurance can also have the same behavior. Health experts constantly recommend closer immersion in one's health and more engagement with preventive healthcare. In three experimental studies, this multidisciplinary paper examines historical health data from all over the country, assesses the medical QoS for multiple US states using a new healthcare-specific analytical infrastructure, delivers forecasts and correlations for future healthcare activities, and provides data-driven