Variations in Receipt of Contraceptives by Insurance Status and Race/Ethnicity.

BACKGROUND Although use of contraceptives has increased among young women in the United States, more than half of pregnancies remain unplanned. The goal of this study was to examine the association between insurance status and receipt of contraceptives among young women receiving care within a large integrated health care system in the Southeastern United States to better inform strategies for increasing access to contraception.METHODS This retrospective study used electronic medical record data from an integrated health care system based in Charlotte, North Carolina. Data were analyzed for 51,900 women aged 18-29 who lived in Mecklenburg County and had at least 1 primary care visit between 2014 and 2016. Contraceptive orders were identified by service and procedure codes and grouped into long-acting reversible contraceptives (LARC) and non-LARC categories. Adjusted multinomial logistic regression models were used to assess the association between receipt of contraceptives and insurance status.RESULTS Compared to non-Hispanic White women with commercial insurance, non-Hispanic Black (OR = 1.25; 95% CI, 1.13-1.38) and Hispanic (OR = 2.25; 95% CI, 1.93-2.61) women with Medicaid had higher odds of receiving LARC. Similar variations by insurance and race/ethnicity were observed for the non-LARC group.LIMITATIONS Data were limited to a single health care system and did not capture contraceptive orders by unaffiliated providers. Analyses used the most frequent payor and did not account for changes in insurance status.CONCLUSION Findings indicate an important role of race/ethnicity and insurance coverage in contraceptive care. Higher receipt of LARC among Black and Hispanic women also suggests that implicit biases may influence contraception counseling and promotion practices. Future study is warranted to further delineate these relationships.

Social and demographic characteristics of frequent or high-charge emergency department users: A quantile regression application.

OBJECTIVE: Heavy users of the emergency department (ED) are a heterogeneous population. Few studies have captured the social and demographic complexity of patients with the largest burden of ED use. Our objective was to model associations between social and demographic patient characteristics and quantiles of the distributions of ED use, defined as frequent and high-charge. METHODS: We conducted a cross-sectional analysis of electronic health and billing records of 99 637 adults residing in an urban North Carolina county who visited an ED within Atrium Health, a large integrated health care system, in 2017. Mid-quantile and standard quantile regression models were used for count and continuous responses, respectively. Frequent and high-charge use outcomes were defined as the median (0.50) and upper quantiles (0.75, 0.95, 0.99) of the outcome distributions for total billed ED visits and associated charges during the study period. Patient characteristic predictors were: insurance coverage (Medicaid, Medicare, private, uninsured), total visits to ambulatory care during the study period (0, 1, >1), and patient demographics: age, gender, race, ethnicity, and living in an underprivileged community called a public health priority area (PHPA). RESULTS: Results showed heterogeneous relationships that were stronger at higher quantiles. Having Medicaid or Medicare insurance was positively associated with ED visits and ED charges at most quantiles. Racial and geographic disparities were observed. Black patients had more ED visits and lower ED charges than their White counterparts at most quantiles of the outcome distributions. Patients living in PHPAs, had lower charges than their counterparts at the median but higher charges at the 0.95 and 0.99 quantiles. CONCLUSIONS: The relationships between patient characteristics and frequent and high-charge use of the ED vary based on the level of use. These findings can be used to inform targeted interventions, tailored policy, and population health management initiatives.

Ambulatory care, insurance, and avoidable emergency department utilization in North Carolina.

OBJECTIVE: To examine whether and how avoidable emergency department (ED) utilization is associated with ambulatory or primary care (APC) utilization, insurance, and interaction effects. DESIGN AND SAMPLE: A cross-sectional analysis of electronic health records from 70,870 adults residing in Mecklenburg County, North Carolina, who visited an ED within a large integrated healthcare system in 2017. METHODS: APC utilization was measured as total visits, categorized as: 0, 1, and > 1. Insurance was defined as the method of payment for the ED visit as: Medicaid, Medicare, private, or uninsured. Avoidable ED utilization was quantified as a score (aED), calculated as the sum of New York University Algorithm probabilities multiplied by 100. Quantile regression models were used to predict the 25th, 50th, 75th, 95th, and 99th percentiles of avoidable ED scores with APC visits and insurance as predictors (Model 1) and with an interaction term (Model 2). RESULTS: Having >1 APC visit was negatively associated with aED at the lower percentiles and positively associated at higher percentiles. A higher aED was associated with having Medicaid insurance and a lower aED was associated with having private insurance, compared to being uninsured. In stratified models, having >1 APC visit was negatively associated with aED at the 25th percentile for the uninsured and privately insured, but positively associated with aED at higher percentiles among the uninsured, Medicaid-insured, and privately insured. CONCLUSIONS: The association between APC utilization and avoidable ED utilization varied based on segments of the distribution of ED score and differed significantly by insurance type.

Patch dynamics modeling framework from pathogens' perspective: Unified and standardized approach for complicated epidemic systems.

Mathematical models are powerful tools to investigate, simulate, and evaluate potential interventions for infectious diseases dynamics. Much effort has focused on the Susceptible-Infected-Recovered (SIR)-type compartment models. These models consider host populations and measure change of each compartment. In this study, we propose an alternative patch dynamic modeling framework from pathogens' perspective. Each patch, the basic module of this modeling framework, has four standard mechanisms of pathogen population size change: birth (replication), death, inflow, and outflow. This framework naturally distinguishes between-host transmission process (inflow and outflow) and within-host infection process (replication) during the entire transmission-infection cycle. We demonstrate that the SIR-type model is actually a special cross-sectional and discretized case of our patch dynamics model in pathogens' viewpoint. In addition, this patch dynamics modeling framework is also an agent-based model from hosts' perspective by incorporating individual host's specific traits. We provide an operational standard to formulate this modular-designed patch dynamics model. Model parameterization is feasible with a wide range of sources, including genomics data, surveillance data, electronic health record, and from other emerging technologies such as multiomics. We then provide two proof-of-concept case studies to tackle some of the existing challenges of SIR-type models: sexually transmitted disease and healthcare acquired infections. This patch dynamics modeling framework not only provides theoretical explanations to known phenomena, but also generates novel insights of disease dynamics from a more holistic viewpoint. It is also able to simulate and handle more complicated scenarios across biological scales such as the current COVID-19 pandemic.

Four Challenges Associated With Current Mathematical Modeling Paradigm of Infectious Diseases and Call for a Shift.

Mathematical models are critical tools to characterize COVID-19 dynamics and take action accordingly. We identified 4 major challenges associated with the current modeling paradigm (SEIR) that hinder the efforts to accurately characterize the emerging COVID-19 and future epidemics. These challenges included (1) lack of consistent definition of "case"; (2) discrepancy between patient-level clinical insights and population-level modeling efforts; (3) lack of adequate inclusion of individual behavioral and social influence; and (4) allowing little flexibility of including new evidence and insights when our knowledge evolved rapidly during the pandemic. Therefore, these challenges made the current SEIR modeling paradigm less practical to handle the complex COVID-19 and future pandemics. Novel and more reliable data sources and alternative modeling paradigms are needed to address these issues.

BMI at birth and overweight at age four.

BACKGROUND: Extensive investigation has established that an elevated weight at birth is associated with subsequent obesity and obesity related negative health outcomes. The significance of overweight at birth, however, remains ill-defined. Historically, it has been difficult to approximate adiposity in infancy in a way that is both simple and meaningful. Body-mass-index (BMI) growth charts for children younger than two years of age only became available in 2006 when published by the WHO. METHODS: This retrospective cohort analysis utilised anthropometric data extracted from the electronic medical record of a large integrated healthcare system in North Carolina. BMI and weight-for-age (WFA) >85% of WHO growth charts measured newborn overweight and macrosomia respectively. Logistic regression models assessed the associations between newborn macrosomia and overweight and overweight at 4 years of age, as well as associations with maternal BMI. Models included demographic data, gestational age, and maternal diabetes status as covariates. RESULTS: Both BMI and WFA >85% at birth were significantly associated with overweight at age 4 years. However, the greater odds of overweight was associated with newborn BMI >85%, with an adjusted odds ratio (AOR) of 2.08 (95% confidence interval [CI]: 1.4-3.08) versus 1.57 (95% CI: 1.08-2.27). Maternal obesity was also more robustly correlated with newborn BMI >85%, AOR of 4.14 (95% CI: 1.6-10.7), than with newborn WFA >85%, AOR of 3.09 (95% CI: 1.41-6.77). CONCLUSIONS: BMI >85% at birth is independently associated with overweight at 4 years. Newborn overweight is perhaps superior to newborn macrosomia in predicting overweight at age 4.

Psychometric Properties of the Mini Pediatric Asthma Quality of Life Questionnaire in a US Sample.

The 13-item Mini Pediatric Asthma Quality of Life Questionnaire (MiniPAQLQ) was developed to measure asthma-specific quality of life in children. However, no validation studies have been conducted in the United States. This study aimed at determining the psychometric properties of the MiniPAQLQ in a US sample. Children aged 7-17 years and with an asthma diagnosis (n = 193) were identified from primary care clinics within an integrated healthcare system in the Southeastern United States. Participants completed surveys consisting of the MiniPAQLQ and the control module of the Asthma Therapy Assessment Questionnaire (ATAQ). Convergent validity was determined based on association between the MiniPAQLQ and ATAQ scores. Internal consistency reliability was determined from Cronbach's alpha coefficients for the MiniPAQLQ subscales (symptoms, emotions, and activities). Item-convergent validity was examined based on corrected item-total correlations. Item-discriminant validity was determined by comparing corrected item-total correlations and item-to-other-scale correlations. Floor and ceiling effects were examined based on the percentage of respondents having the lowest and highest scores on the MiniPAQLQ. A negative association was observed between quality of life scores from the MiniPAQLQ and asthma control as determined from the ATAQ, providing evidence of convergent validity. Internal consistency reliability was good with Cronbach's alpha values of above 0.8 for the MiniPAQLQ subscales. Item-convergent validity was confirmed, whereas item-discriminant validity was not confirmed. Floor effects were absent, whereas ceiling effects were present. The MiniPAQLQ possesses moderately good psychometric properties among children and adolescents in the United States and could be a useful tool for asthma management in clinical practice.

Planning for Action: The Impact of an Asthma Action Plan Decision Support Tool Integrated into an Electronic Health Record (EHR) at a Large Health Care System.

INTRODUCTION: Asthma is a chronic airway disease that can be difficult to manage, resulting in poor outcomes and high costs. Asthma action plans assist patients with self-management, but provider compliance with this recommendation is limited in part because of guideline complexity. This project aimed to embed an electronic asthma action plan decision support tool (eAAP) into the medical record to streamline evidence-based guidelines for providers at the point of care, create individualized patient handouts, and evaluate effects on disease outcomes. METHODS: eAAP development occurred in 4 phases: web-based prototype creation, multidisciplinary team engagement, pilot, and system-wide dissemination. Medical record and hospital billing data compared frequencies of asthma exacerbations before and after eAAP receipt with matched controls. RESULTS: Between December 2012 and September 2014, 5174 patients with asthma (∼10%) received eAAPs. Results showed an association between eAAP receipt and significant reductions in pediatric asthma exacerbations, including 33% lower odds of requiring oral steroids (P < .001), compared with controls. Equivalent adult measures were not statistically significant. CONCLUSIONS: This study supports existing evidence that patient self-management plays an important role in reducing asthma exacerbations. We show the feasibility of leveraging technology to provide guideline-based decision support through an eAAP, addressing known challenges of implementation into routine practice.