Geographic Disparities in Availability of General and Specialized Pediatricians in the United States and Prevalence of Childhood Neurodevelopmental Disorders.

General pediatricians and those specialized in developmental-behavioral and neurodevelopmental disabilities support children with neurodevelopmental disorders, such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). We identified substantial geographic disparities in pediatrician availability (eg, urban > rural areas), as well as regions with low pediatrician access but high ASD/ADHD prevalence estimates (eg, the US Southeast).

A Hypothesis Test for Detecting Spatial Patterns in Categorical Areal Data.

The vast growth of spatial datasets in recent decades has fueled the development of many statistical methods for detecting spatial patterns. Two of the most commonly studied spatial patterns are clustering, loosely defined as datapoints with similar attributes existing close together, and dispersion, loosely defined as the semi-regular placement of datapoints with similar attributes. In this work, we develop a hypothesis test to detect spatial clustering or dispersion at specific distances in categorical areal data. Such data consists of a set of spatial regions whose boundaries are fixed and known (e.g., counties) associated with a categorical random variable (e.g. whether the county is rural, micropolitan, or metropolitan). We propose a method to extend the positive area proportion function (developed for detecting spatial clustering in binary areal data) to the categorical case. This proposal, referred to as the categorical positive areal proportion function test, can detect various spatial patterns, including homogeneous clusters, heterogeneous clusters, and dispersion. Our approach is the first method capable of distinguishing between different types of clustering in categorical areal data. After validating our method using an extensive simulation study, we use the categorical positive area proportion function test to detect spatial patterns in Boulder County, Colorado USA biological, agricultural, built and open conservation easements.

Predictors of Autism Spectrum Disorder and ADHD: Results from the National Survey of Children's Health.

BACKGROUND: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are two of the most common neurodevelopmental disorders with comorbidity rates of up to 70%. Population-based studies show differential rates of ADHD and ASD diagnosis based on sociodemographic variables. However, no studies to date have examined the role of sociodemographic factors on the likelihood of receiving an ADHD, ASD, or comorbid ASD + ADHD diagnosis in a large, nationally representative sample. OBJECTIVE: This study aims to examine the impact of sociodemographic factors on the odds of experiencing ASD-only, ADHD-only, or both diagnoses for children in the United States. METHODS: Using a mixed effects multinomial logistic modeling approach and data from the 2016-2018 National Survey of Children's Health, we estimated the association between sociodemographic variables and the log odds of being in each diagnostic group. RESULTS: Sociodemographic variables were differentially related to the three diagnostic groups: ASD-only, ADHD-only, and ASD + ADHD. Compared to girls, boys experienced higher odds of all three diagnosis categories. White children had higher odds of having an ADHD-only or ASD + ADHD diagnosis compared to non-Hispanic (NH) Black, NH multiple/other race, and Hispanic children. Odds ratios for levels of parent education, household income, and birth characteristics showed varying trends across diagnostic groups. CONCLUSIONS: Overall, our findings point to unique sets of risk factors differentially associated ASD and ADHD, with lower income standing out as an important factor associated with receiving a diagnosis of ASD + ADHD.

A Hypothesis Test for Detecting Distance-Specific Clustering and Dispersion in Areal Data.

Spatial clustering detection has a variety of applications in diverse fields, including identifying infectious disease outbreaks, pinpointing crime hotspots, and identifying clusters of neurons in brain imaging applications. Ripley's K-function is a popular method for detecting clustering (or dispersion) in point process data at specific distances. Ripley's K-function measures the expected number of points within a given distance of any observed point. Clustering can be assessed by comparing the observed value of Ripley's K-function to the expected value under complete spatial randomness. While performing spatial clustering analysis on point process data is common, applications to areal data commonly arise and need to be accurately assessed. Inspired by Ripley's K-function, we develop the positive area proportion function (PAPF) and use it to develop a hypothesis testing procedure for the detection of spatial clustering and dispersion at specific distances in areal data. We compare the performance of the proposed PAPF hypothesis test to that of the global Moran's I statistic, the Getis-Ord general G statistic, and the spatial scan statistic with extensive simulation studies. We then evaluate the real-world performance of our method by using it to detect spatial clustering in land parcels containing conservation easements and US counties with high pediatric overweight/obesity rates.

County-Level Prevalence Estimates of Autism Spectrum Disorder in Children in the United States.

Prevalence estimates of autism spectrum disorder (ASD) point to geographic and socioeconomic disparities in identification and diagnosis. Estimating national prevalence rates can limit understanding of local disparities, especially in rural areas where disproportionately higher rates of poverty and decreased healthcare access exist. Using a small area estimation approach from the 2016-2018 National Survey of Children's Health (N = 70,913), we identified geographic differences in ASD prevalence, ranging from 4.38% in the Mid-Atlantic to 2.71% in the West South-Central region. Cluster analyses revealed "hot spots" in parts of the Southeast, East coast, and Northeast. This geographic clustering of prevalence estimates suggests that local or state-level differences in policies, service accessibility, and sociodemographics may play an important role in identification and diagnosis of ASD.County-Level Prevalence Estimates of Autism Spectrum Disorder in Children in the United States.

County-level prevalence estimates of ADHD in children in the United States.

PURPOSE: Attention-deficit/hyperactivity disorder (ADHD) is a common childhood disorder often characterized by long-term impairments in family, academic, and social settings. Measuring the prevalence of ADHD is important as treatment options increase around the U.S. Prevalence data helps inform decisions by care providers, policymakers, and public health officials about allocating resources for ADHD. In addition, measuring geographic variation in prevalence estimates can facilitate hypothesis generation for future analytic work. Most U.S. studies of ADHD prevalence among children focus on national or demographic group rates. METHODS: Using a small area estimation approach and data from the 2016 to 2018 National Survey of Children's Health, we estimated childhood ADHD prevalence estimates at the census regional division, state, and county levels. The sample included approximately 70,000 children aged 5-17 years. RESULTS: The national ADHD rate was estimated to be 12.9% (95% Confidence Interval: 11.5%, 14.4%). Counties in the West South Central, East South Central, New England, and South Atlantic divisions had higher estimated rates of childhood ADHD (55.1%, 53.6%, 49.3%, and 46.2% of the counties had rates of 16% or greater, respectively) compared to counties in the Mountain, Mid Atlantic, West North Central, Pacific, and East North Central divisions (2.1%, 4%, 5.8%, 6.9%, and 11.7% of the counties had rates of 16% or greater, respectively). CONCLUSIONS: These local-level rates are useful for decision-makers to target programs and direct sufficient ADHD resources based on communities' needs.

Availability of hospital-based cancer services before and after rural hospital closure, 2008-2017.

INTRODUCTION: Rural populations have less access to cancer care services and experience higher cancer mortality rates than their urban counterparts, which may be exacerbated by hospital closures. Our objective was to examine the impact of hospital closures on access to cancer-relevant hospital services across hospital service areas (HSAs). METHODS: We used American Hospital Association survey data from 2008 to 2017 to examine the change in access to cancer-related screening and treatment services across rural HSAs that sustained hospitals over time, experienced any closures, or had all hospitals close. We performed a longitudinal analysis to assess the association between hospital closure occurrence and maintenance or loss of cancer-related service lines accounting for hospital and HSA-level characteristics. Maps were also developed to display changes in the availability of services across HSAs. RESULTS: Of the 2,014 rural HSAs, 3.8% experienced at least 1 hospital closure during the study period, most occurring in the South. Among HSAs that experienced hospital closure, the loss of surgery services lines was most common, while hospital closures did not affect the availability of overall oncology and radiation services. Screening services either were stable (mammography) or increased (endoscopy) in areas with no closures. DISCUSSION: Rural areas persistently experience less access to cancer treatment services, which has been exacerbated by hospital closures. Lack of Medicaid expansion in many Southern states and other policy impacts on hospital financial viability may play a role in this. Future research should explore the impact of closures on cancer treatment receipt and outcomes.

Outcomes of Shared Decision-Making for Low-Dose Screening for Lung Cancer in an Academic Medical Center.

Shared decision-making (SDM) helps patients weigh risks and benefits of screening approaches. Little is known about SDM visits between patients and healthcare providers in the context of lung cancer screening. This study explored the extent that patients were informed by their provider of the benefits and harms of lung cancer screening and expressed certainty about their screening choice. We conducted a survey with 75 patients from an academic medical center in the Southeastern U.S. Survey items included knowledge of benefits and harms of screening, patients' value elicitation during SDM visits, and decisional certainty. Patient and provider characteristics were collected through electronic medical records or self-report. Descriptive statistics, Kruskal-Wallis tests, and Pearson correlations between screening knowledge, value elicitation, and decisional conflict were calculated. The sample was predominately non-Hispanic White (73.3%) with no more than high school education (53.4%) and referred by their primary care provider for screening (78.7%). Patients reported that providers almost always discussed benefits of screening (81.3%), but infrequently discussed potential harms (44.0%). On average, patients had low knowledge about screening (score = 3.71 out of 8) and benefits/harms. Decisional conflict was low (score = - 3.12) and weakly related to knowledge (R= - 0.25) or value elicitation (R= - 0.27). Black patients experienced higher decisional conflict than White patients (score = - 2.21 vs - 3.44). Despite knowledge scores being generally low, study patients experienced low decisional conflict regarding their decision to undergo lung cancer screening. Additional work is needed to optimize the quality and consistency of information presented to patients considering screening.

Low-dose CT lung cancer screening uptake: A rural-urban comparison.

PURPOSE: The US Preventive Services Task Force recommends lung cancer screening with Low-Dose Computed Tomography (LDCT) in high-risk individuals. Our objective was to identify demographic, health, and financial factors associated with screening uptake, with a focus on urban-rural differences. METHODS: We analyzed data from the 2018 and 2019 Behavioral Risk Factor Surveillance System and its optional Lung Cancer Screening Module to examine factors associated with screening uptake among 20 states that administered the optional module. We compared differences in factors associated with uptake overall and by geographical regions and conducted multivariable logistic mixed-effects regression, accounting for participant clustering by state to assess the impact of these factors on uptake. FINDINGS: Overall 1,268 participants underwent LDCT screening with no significant differences observed between rural (16.3%) and urban residents (17.7%, p = 0.67). In multivariable models, rural residents did not differ significantly in their LDCT screening uptake (OR = 0.85; 95% CI: 0.67-1.09, p = 0.20), but uptake was significantly higher for participants with underlying chronic respiratory conditions, veterans, those with higher pack-year history, and those with poor/fair general health and prior history of cancer. Uptake declined with age, higher education level, concerns about paying for medical care, and lack of primary care. CONCLUSIONS: Modifiable targets can be leveraged to increase LDCT screening. Based on significant predictors of screening uptake, clinicians should prioritize interventions that effectively consider smoking history as well as those identified as effective in veterans' health settings. Additionally, reducing structural barriers to care related to insurance and income will be key to reducing disparities.

Trends in Cancer Treatment Service Availability Across Critical Access Hospitals and Prospective Payment System Hospitals.

BACKGROUND: Rural residents experience worse cancer prognosis and access to cancer care providers than their urban counterparts. Critical access hospitals (CAHs) represent over half of all rural community hospitals. However, research on cancer services provided within CAHs is limited. OBJECTIVE: The objective of this study was to investigate trends in cancer services availability in urban and rural Prospective Payment System (PPS) hospitals and CAHs. DESIGN: Retrospective, time-series analysis using data from 2008 to 2017 American Hospital Association Annual Surveys. Multivariable logistic regressions were used to examine differential trends in cancer services between urban PPS, rural PPS, and CAHs, overall and among small (<25 beds) hospitals. SUBJECTS: All US acute care and cancer hospitals (4752 in 2008 to 4722 in 2017). MEASURES: Primary outcomes include whether a hospital provided comprehensive oncology services, chemotherapy, and radiation therapy each year. RESULTS: In 2008, CAHs were less likely to provide all cancer services, especially chemotherapy (30.4%) and radiation therapy (2.9%), compared with urban (64.4% and 43.8%, respectively) and rural PPS hospitals (42.0% and 23.3%, respectively). During 2008-2017, compared with similarly sized PPS hospitals, CAHs were more likely to provide oncology services and chemotherapy, but with decreasing trends. Radiation therapy availability between small PPS hospitals and CAHs did not differ. CONCLUSIONS: Compared with all PPS hospitals, CAHs offered fewer cancer treatment services and experienced a decline in service capability over time. These differences in chemotherapy services were mainly driven by hospital size, as small urban and rural PPS hospitals had lower rates of chemotherapy than CAHs. Still, the lower rates of radiotherapy in CAHs highlight disproportionate challenges facing CAHs for some specialty services.

Multilevel predictors of guideline concordant needle biopsy use for non-metastatic breast cancer.

PURPOSE: Persistent breast cancer disparities, particularly geographic disparities, may be explained by diagnostic practice patterns such as utilization of needle biopsy, a National Quality Forum-endorsed quality metric for breast cancer diagnosis. Our objective was to assess the relationship between patient- and facility-level factors and needle biopsy receipt among women with non-metastatic breast cancer in the United States. METHODS: We examined characteristics of women diagnosed with breast cancer between 2004 and 2015 in the National Cancer Database. We assessed the relationship between patient- (e.g., race/ethnicity, stage, age, rurality) and facility-level (e.g., facility type, breast cancer case volume) factors with needle biopsy utilization via a mixed effects logistic regression model controlling for clustering by facility. RESULTS: In our cohort of 992,209 patients, 82.96% received needle biopsy. In adjusted models, the odds of needle biopsy receipt were higher for Hispanic (OR 1.04, Confidence Interval 1.01-1.08) and Medicaid patients (OR 1.04, CI 1.02-1.08), and for patients receiving care at Integrated Network Cancer Programs (OR 1.21, CI 1.02-1.43). Odds of needle biopsy receipt were lower for non-metropolitan patients (OR 0.93, CI 0.90-0.96), patients with cancer stage 0 or I (at least OR 0.89, CI 0.86-0.91), patients with comorbidities (OR 0.93, CI 0.91-0.94), and for patients receiving care at Community Cancer Programs (OR 0.84, CI 0.74-0.96). CONCLUSION: This study suggests a need to account for sociodemographic factors including rurality as predictors of utilization of evidence-based diagnostic testing, such as needle biopsy. Addressing inequities in breast cancer diagnosis quality may help improve breast cancer outcomes in underserved patients.

Estimates of Childhood Overweight and Obesity at the Region, State, and County Levels: A Multilevel Small-Area Estimation Approach.

Local-level childhood overweight and obesity data are often used to implement and evaluate community programs, as well as allocate resources to combat overweight and obesity. The most current substate estimates of US childhood obesity use data collected in 2007. Using a spatial multilevel model and the 2016 National Survey of Children's Health, we estimated childhood overweight and obesity prevalence rates at the Census regional division, state, and county levels using small-area estimation with poststratification. A sample of 24,162 children aged 10-17 years was used to estimate a national overweight and obesity rate of 30.7% (95% confidence interval: 27.0%, 34.9%). There was substantial county-to-county variability (range, 7.0% to 80.9%), with 31 out of 3,143 counties having an overweight and obesity rate significantly different from the national rate. Estimates from counties located in the Pacific region had higher uncertainty than other regions, driven by a higher proportion of underrepresented sociodemographic groups. Child-level overweight and obesity was related to race/ethnicity, sex, parental highest education (P < 0.01 for all), county-level walkability (P = 0.03), and urban/rural designation (P = 0.02). Overweight and obesity remains a vital issue for US youth, with substantial area-level variability. The additional uncertainty for underrepresented groups shows surveys need to better target diverse samples.

Disparities in Meeting USPSTF Breast, Cervical, and Colorectal Cancer Screening Guidelines Among Women in the United States.

INTRODUCTION: Many sociodemographic factors affect women's ability to meet cancer screening guidelines. Our objective was to examine which sociodemographic characteristics were associated with women meeting US Preventive Services Task Force (USPSTF) guidelines for breast, cervical, and colorectal cancer screening. METHODS: We used 2018 Behavioral Risk Factor Surveillance System data to examine the association between sociodemographic variables, such as race/ethnicity, rurality, education, and insurance status, and self-reported cancer screening for breast, cervical, and colorectal cancer. We used multivariable log-binomial regression models to estimate adjusted prevalence ratios and 95% CIs. RESULTS: Overall, the proportion of women meeting USPSTF guidelines for breast, cervical, and colorectal cancer screening was more than 70%. The prevalence of meeting screening guidelines was 6% to 10% greater among non-Hispanic Black women than among non-Hispanic White women across all 3 types of cancer screening. Women who lacked health insurance had a 26% to 39% lower screening prevalence across screening types than women with health insurance. Compared with women with $50,000 or more in annual household income, women with less than $50,000 in annual household income had a 3% to 8% lower screening prevalence across all 3 screening types. For colorectal cancer, the prevalence of screening was 7% less among women who lived in rural counties than among women in metropolitan counties. CONCLUSION: Many women still do not meet current USPSTF guidelines for breast, cervical, and colorectal cancer screening. Screening disparities are persistent among socioeconomically disadvantaged groups, especially women with low incomes and without health insurance. To increase the prevalence of cancer screening and reduce disparities, interventions must focus on reducing economic barriers and improving access to care.

The Intersection of Rural Residence and Minority Race/Ethnicity in Cancer Disparities in the United States.

One in every twenty-five persons in America is a racial/ethnic minority who lives in a rural area. Our objective was to summarize how racism and, subsequently, the social determinants of health disproportionately affect rural racial/ethnic minority populations, provide a review of the cancer disparities experienced by rural racial/ethnic minority groups, and recommend policy, research, and intervention approaches to reduce these disparities. We found that rural Black and American Indian/Alaska Native populations experience greater poverty and lack of access to care, which expose them to greater risk of developing cancer and experiencing poorer cancer outcomes in treatment and ultimately survival. There is a critical need for additional research to understand the disparities experienced by all rural racial/ethnic minority populations. We propose that policies aim to increase access to care and healthcare resources for these communities. Further, that observational and interventional research should more effectively address the intersections of rurality and race/ethnicity through reduced structural and interpersonal biases in cancer care, increased data access, more research on newer cancer screening and treatment modalities, and continued intervention and implementation research to understand how evidence-based practices can most effectively reduce disparities among these populations.

Predictors of Lung Cancer Screening Utilization in a Population-Based Survey.

PURPOSE: Annual low-dose CT (LDCT) screening in high-risk individuals has been recommended to detect lung cancer earlier and reduce mortality. The objective of this study was to identify demographic, financial, and health care factors associated with screening uptake in a population-based survey. METHODS: Data from the Lung Cancer Screening Module and core modules of the 2017 Behavioral Risk Factor Surveillance System, a population-based survey administered via cell phone and landline, were analyzed to examine demographic, health, and financial factors associated with screening uptake among the 10 states that administered the screening module. Weighted frequencies and confidence intervals (CIs) were produced, and weighted Wald χ2 tests were used to compare differences in screening utilization by patient characteristics. A multivariate logistic mixed-effects model was constructed, in which participant clustering by state was accounted for with a random intercept. RESULTS: The uninsured were less likely to undergo LDCT screening (odds ratio [OR], 0.28; 95% CI, 0.12-0.65). LDCT screening uptake was higher for participants with chronic respiratory conditions (OR, 4.14; 95% CI, 2.33-7.35); those who were divorced, separated, widowed, or refused to answer (OR, 1.41; 95% CI, 1.05-1.86); those who had previous cancer diagnoses (OR, 1.90; 95% CI, 1.40-2.56); and those aged 65 to 69 years (OR, 1.23; 95% CI, 1.06-1.44) or 70 to 74 years (OR, 1.17; 95% CI, 1.00-1.37). Utilization also varied significantly across states. CONCLUSIONS: Having a related health condition whereby participants were sensitized to the benefits of early screening (ie, another cancer diagnosis, presence of chronic respiratory conditions) and having insurance coverage were associated with higher LDCT screening uptake. Providers should engage LDCT-eligible patients through informed and shared decision making to increase preference-sensitive screening decisions.

Financial hardship among rural cancer survivors: An analysis of the Medical Expenditure Panel Survey.

Some cancer survivors report spending 20% of their annual income on medical care. Undue financial burden that patients face related to the cost of care is referred to as financial hardship, which may be more prevalent among rural cancer survivors. This study examined contrasts in financial hardship among 1419 rural and urban cancer survivors using the 2011 Medical Expenditure Panel Survey supplement - The Effects of Cancer and Its Treatment on Finances. We combined four questions, creating a measure of material financial hardship, and examined one question on financial worry. We conducted multivariable logistic regression analyses, which produced odds ratios (OR) for factors associated with financial hardship and worry, and then generated average adjusted predicted probabilities. We focused on rural and urban differences classified by metropolitan statistical area (MSA) designation, controlling for age, education, race, marital status, health insurance, family income, and time since last cancer treatment. More rural cancer survivors reported financial hardship than urban survivors (23.9% versus 17.1%). However, our adjusted models revealed no significant impact of survivors' MSA designation on financial hardship or worry. Average adjusted predicted probabilities of financial hardship were 18.6% for urban survivors (Confidence Interval [CI]: 11.9%-27.5%) and 24.2% for rural survivors (CI: 15.0%-36.2%). For financial worry, average adjusted predicted probabilities were 19.9% for urban survivors (CI: 12.0%-31.0%) and 18.8% for rural survivors (CI: 12.1%-28.0%). Improving patient-provider communication through decision aids and/or patient navigators may be helpful to reduce financial hardship and worry regardless of rural-urban status.

Different evidence summaries have implications for contextualizing findings of meta-analysis of diagnostic tests.

OBJECTIVE: To evaluate diagnostic tests, analysts use meta-analyses to provide inputs to parameters in decision models. Choosing parameter estimands from meta-analyses requires understanding the meta-analytic and decision-making contexts. STUDY DESIGN AND SETTING: We expand on an analysis comparing positron emission tomography (PET), PET with computed tomography (PET/CT), and conventional workup (CW) in women with suspected recurrent breast cancer. We discuss Bayesian meta-analytic summaries (posterior mean over a set of existing studies, posterior estimate in an existing study, posterior predictive mean in a new study) used to estimate diagnostic test parameters (prevalence, sensitivity, specificity) needed to calculate quality-adjusted life years in a decision model contextualizing PET, PET/CT, and CW. RESULTS: The mean and predictive mean give similar estimates, but the latter displays greater uncertainty. Namely, PET/CT outperforms CW on average but may not do better than CW when implemented in future settings. CONCLUSION: Selecting estimands for decision model parameters from meta-analyses requires understanding the relationship between decision settings and meta-analysis studies' settings, specifically whether the former resemble one or all study settings or represents new settings. We provide an algorithm recommending appropriate estimands as input parameters in decision models for diagnostic tests to obtain output parameters consistent with the decision context.