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Decision support techniques and online algorithms aim to help individuals predict costs and facilitate their choice of health insurance coverage. Self-reported health status (SHS), whereby patients rate their own health, could improve cost-prediction estimates without requiring individuals to share personal health information or know about undiagnosed conditions. We compared the predictive accuracy of several models: (1) SHS only, (2) a "basic" model adding health-related variables, and (3) a "full" model adding measures of healthcare access. The Medical Expenditure Panel Survey was used to predict 2015 health expenditures from 2014 data. Relative performance was assessed by comparing adjusted-R 2 values and by reporting the predictive accuracy of the models for a new cohort (2015-2016 data). In the SHS-only model, those with better SHS were less likely to incur expenditures. However, after accounting for health variables, those with better SHS were more likely to incur expenses. In the full model, SHS was no longer predictive of incurring expenses. Variables indicating better access to care were associated with higher likelihood of spending and higher spending. The full model ( R 2 = 0.290) performed slightly better than the basic model ( R 2 = 0.240), but neither performed well at the upper tail of the cost distribution. While our SHS-based models perform well in the aggregate, predicting population-level risk well, they are not sufficiently accurate to guide individuals' insurance shopping decisions in all cases. Policies that rely heavily on health insurance consumers making individually optimal choices cannot assume that decision tools can accurately anticipate high costs.

Protoporphyrinogen oxidase (PPO) is a critical enzyme across life as the last common step in the synthesis of many metalloporphyrins. The reaction mechanism of PPO was assessed in silico and the unstructured loop near the binding pocket was investigated. The substrate, intermediates, and product were docked in the catalytic domain of PPO using a modified Autodock method, introducing flexibility in the macrocycles. Sixteen PPO protein sequences across phyla were aligned and analyzed with Phyre2 and ProteinPredict to study the unstructured loop from residue 204-210 in the H. sapiens structure. Docking of the substrate, intermediates, and product all resulted in negative binding energies, though the substrate had a lower energy than the others by 40%. The α-H of C10 was found to be 1.4 angstroms closer to FAD than the β-H, explaining previous reports of the reaction occurring on the meso face of the substrate. A lack of homology in sequence or length in the unstructured loop indicates a lack of function for the protein reaction. This docking study supports a reaction mechanism proposed previously whereby all hydride abstractions occur on the C10 of the tetrapyrrole followed by tautomeric rearrangement to prepare the intermediate for the next reaction.

Objective: To add to the evidence base on causal linkages between health insurance coverage and health status, controlling for sociodemographic factors, by analyzing longitudinal data., Data Source: Secondary data from the Panel Study of Income Dynamics (PSID), 2009-17, which is a longitudinal, multigenerational study covering a wide array of socioeconomic topics that began in 1968 but has only recently begun collecting useful information on individual health insurance., Study Design: 2017 data on self-reported health status, work limitations, and death were analyzed as outcomes based upon the degree of exposure to health insurance in 2011-17. All variables were collected biannually for four years beginning in 2011. Having health insurance at each point in time was, in turn, modeled as a function of several sociodemographic factors., Data Extraction Methods: Data were downloaded using the crosswalk tool available at the PSID website. Because individual health insurance questions were only asked of heads and spouses in households beginning in 2011, we analyzed only these records., Principal Findings: Among respondents who were not in fair or poor health in 2009, each additional 2 years of subsequent reported insurance coverage reduced the chance of reporting fair or poor health in 2017 by 10 percent; however, this effect was not present for black respondents., Conclusions: Our results suggest that the effect of health insurance on health status may compound over time, although unevenly by race. Since people who report fair or poor health status represent the bulk of utilization and spending, our findings provide evidence in support of viewing coverage expansions as investments that will pay dividends in the form of lower utilization over time. More work is needed to produce detailed estimates of cost savings, which may in turn influence policy, as well as to understand and address the source of racial disparity., (© 2020 The Authors. Health Services Research published by Wiley Periodicals LLC on behalf of Health Research and Educational Trust.)

This study represents a successful approach toward employing polycaprolactone-polyamidoamine (PCL-PAMAM) linear dendritic block copolymer (LDBC) nanoparticles as small-molecule carriers in NIR imaging and photothermal therapy. A feasible and robust synthetic strategy was used to synthesize a library of amphiphilic LDBCs with well-controlled hydrophobic-to-hydrophilic weight ratios. Systems with a hydrophobic weight ratio higher than 70% formed nanoparticles in aqueous media, which show hydrodynamic diameters of 51.6 and 96.4 nm. These nanoparticles exhibited loading efficiencies up to 21% for a hydrophobic molecule and 64% for a hydrophilic molecule. Furthermore, successful cellular uptake was observed via trafficking into endosomal and lysosomal compartments with an encapsulated NIR theranostic agent (C3) without inducing cell death. A preliminary photothermal assessment resulted in cell death after treating the cells with encapsulated C3 and exposing them to NIR light. The results of this work confirm the potential of these polymeric materials as promising candidates in theranostic nanomedicine.

Background: The utilization of total hip arthroplasty (THA) and total knee arthroplasty (TKA) increased after Medicaid expansion under the U.S. Affordable Care Act (ACA), suggesting a potential unmet need for THA and TKA. We examined the timing of THA and TKA in patients after obtaining Medicaid expansion insurance coverage. We hypothesized that patients with Medicaid expansion insurance would undergo a surgical procedure sooner than patients in traditional Medicaid populations., Methods: We used administrative data from a Medicaid managed care company to determine the timing of primary THA and TKA in patients who were 18 to 64 years of age in 4 states with Medicaid expansion (Illinois, Ohio, Oregon, and Washington) and 4 states without Medicaid expansion (Louisiana, Mississippi, Texas, and Wisconsin) from 2008 to 2015. The insurance types were Medicaid expansion, Medicaid plans for Supplemental Security Income (SSI), or Temporary Assistance for Needy Families (TANF). Roughly, these 3 groups correspond to relatively healthy childless adults, relatively unhealthy disabled adults, and parents of children with Medicaid insurance. The main outcome measure was time from enrollment to the surgical procedure. The primary exposure of interest was insurance type. We used a generalized linear regression model to adjust for patient age, sex, social deprivation, surgeon supply and reimbursement, and state-level Medicaid enrollment., Results: In the unadjusted analysis of 4,117 patients, there was a significantly shorter time from enrollment to THA and TKA for the expansion group (median, 7.5 months) relative to the SSI group (median, 16.1 months; p < 0.0001) and the TANF group (median, 12.2 months; p < 0.0001). In the adjusted analysis, the time from enrollment to THA and TKA was significantly shorter in the expansion group (β, -1.21 [95% confidence interval (CI), -1.35 to -1.07]; p < 0.001) compared with the TANF group (β, -0.27 [95% CI, -0.38 to -0.17]; p < 0.001) and the SSI group (reference). Compared with the SSI group, these coefficients are equivalent to a 70% shorter time to the surgical procedure in the expansion group and a 24% shorter time to the surgical procedure in the TANF group., Conclusions: Our findings suggest an unmet need for THA and TKA among newly enrolled Medicaid expansion beneficiaries. This need should be considered by surgeons, hospitals, and policymakers in ensuring access to care. Furthermore, consideration should be given to existing insurance-based disparities in access to orthopaedic care, as these may be exacerbated by an increased demand for THA and TKA from Medicaid expansion beneficiaries.

Importance: Despite evidence of improved insurance coverage under the Affordable Care Act and Medicaid expansion among adults with cancer, little is known regarding the association of these policies with coverage among children with cancer., Objective: To assess the association of early Medicaid expansion with rates of Medicaid coverage, private coverage, and no uninsurance among children with cancer., Design, Setting, and Participants: This cross-sectional study used data from the Surveillance, Epidemiology, and End Results (SEER) database from January 1, 2007, to December 31, 2015, to identify children diagnosed with cancer at ages 0 to 14 years in the United States. Data were analyzed from July 27, 2017, to October 7, 2019., Exposures: Changes in insurance status at diagnosis after early Medicaid expansion in California, Connecticut, Washington, and New Jersey (EXP states) were compared with changes in nonexpansion (NEXP) states (Arkansas, Georgia, Hawaii, Iowa, Kentucky, Louisiana, Michigan, New Mexico, and Utah)., Main Outcomes and Measures: Difference-in-differences (DID) analyses were used to compare absolute changes in insurance status (uninsured, Medicaid, private/other) at diagnosis before (2007 to 2009) and after (2011 to 2015) expansion in EXP relative to NEXP states., Results: A total of 21 069 children (11 265 [53.5%] male; mean [SD] age, 6.18 [4.57] years) were included. A 5.25% increase (95% CI, 2.61%-7.89%; P < .001) in Medicaid coverage in children with cancer was observed in EXP vs NEXP states, with larger increases among children of counties with middle to high (adjusted DID estimates, 10.18%; 95% CI, 4.22%-16.14%; P = .005) and high (adjusted DID estimates, 6.13%; 95% CI, 1.10%-11.15%; P = .05) poverty levels (P = .04 for interaction). Expansion-associated reductions of children reported as uninsured (-0.73%; 95% CI, -1.49% to 0.03%; P = .06) and with private or other insurance (-4.52%; 95% CI, -7.16% to -1.88%; P < .001) were observed. For the latter, the decrease was greater for children from counties with middle to high poverty (-9.00%; 95% CI, -14.98% to -3.02%) and high poverty (-6.38%; 95% CI, -11.36% to -1.40%) (P = .04 for interaction)., Conclusions and Relevance: In this study, state Medicaid expansions were associated with increased Medicaid coverage in children with cancer overall and in some subgroups primarily owing to switching from private coverage, particularly in counties with higher levels of poverty but also through reductions in the uninsured.

Routine esophagogastroduodenoscopy (EGD) is an area of continued controversy in the preoperative evaluation for bariatric surgery; more information is needed regarding its impact on surgical management and associated costs. This systematic review and meta-analysis reports rates of abnormalities detected on preoperative EGD that changed operative management or delayed bariatric surgery. Sensitivity analysis examined the impact of controversial findings of hiatal hernia, Helicobacter pylori, gastritis, peptic ulcer disease. Data were used to calculate the cost per surgical alteration made due to abnormalities detected by routine EGD, compactly termed "cost-of-routine-EGD." Thirty-one retrospective observational studies were included. Meta-analysis found 3.9% of EGDs resulted in a change in operative management; this proportion decreased to 0.3% after sensitivity analysis, as detection of hiatal hernia comprised 85.7% of findings that changed operative management. Half of the 7.5% of cases that resulted in surgical delay involved endoscopic detection of H. pylori. Gastric pathology was detected in a significantly greater proportion of symptomatic patients (65.0%) than in asymptomatic patients (34.1%; P<0.001). Cost-of-routine-EGD to identify an abnormality that changed operative management was $601,060, after excluding controversial findings. The cost-of-routine-EGD to identify any abnormality that led to a change in type of bariatric operation was $281,230 and $766,352 when controversial findings were included versus excluded, respectively. Cost-of-routine-EGD to identify a malignancy was $2,554,506. Cost-of-routine-EGD is high relative to the low proportion of abnormalities that alter bariatric surgery. Our results highlight the need to develop alternative strategies to preoperative screening, in order to improve access and decrease cost associated with bariatric surgery.

Purpose: The Medicare Advantage (MA) program allows Medicare beneficiaries to receive benefits from private plans rather than from traditional fee-for-service (FFS) Medicare. Little is known about the rural and urban differences in the populations that enroll in the MA program, and these differences may be important for setting policy. This brief uses data from the 2012-13 Medicare Current Beneficiary Survey (MCBS) to describe these differences, and combined with county-level data on MA issuer participation, this dataset also allows us to assess the degree to which issuers may engage in selective MA market entry on the basis of demographic characteristics., Key Findings: (1) Rural and urban MA and FFS populations did not differ much on average by any characteristics reported in the data, including age, self-reported health status, cancer diagnosis, smoking status, Medicaid status, or by other variables assessing frailty and presence of chronic conditions. (2) Most measures of access were similar across rural and urban respondents. However, in terms of cost, urban enrollees were less likely to pay an additional premium (beyond Medicare Part A and B) to obtain MA coverage: 42 percent reported doing so in urban places, while 54 percent did so in rural places. (3) While rurality on its own was often a significant predictor of lower issuer participation in a county’s MA market, the addition of other demographic characteristics did not influence the prediction. In other words, we found no evidence, based upon MCBS data, that issuers exclude rural counties due to other demographics.

In this work we demonstrate that time domain techniques can be used successfully to monitor realtively weak modulations of the fluorescence in sensing applications. The metal sensing complex Newport Green DCF™ can detect selected transition metals in vivo as well as in vitro. Incremental addition of Ni and/or Zn (in vitro) lead to a substantial reduction in the yield of the fast component in a bi-exponential fluorescence decay (τ 1  = 150-250 ps) from 60% to 30-35%. This is rationalised as an inhibition of intra-molecular electron transfer in the NPG sensing complex due to metal complexation. In order to explore this effect in cellulo, NIH 3 T3 mouse skin fibroplast cells were pre-incubated with set levels of Ni and Zn, at a constant concentration of NPG. The fluorescence modulation in cellullo was subsequently studied employing both time-resolved fluorescence microscopy and confocal fluorescence microscopy. In correlation with the in vitro observations, similar effects were observed on the fluorescence decay in cellulo.

Purpose: Since 2014, when the Health Insurance Marketplaces (HIMs) authorized by the Patient Protection and Affordable Care Act (PPACA) were implemented, considerable premium changes have been observed in the marketplaces across the 50 states and the District of Columbia. This policy brief assesses the changes in average HIM plan premiums from 2014 to 2018, before accounting for subsidies, with an emphasis on the widening variation across rural and urban places, providing information during Congressional debates on the future of the program., Key Findings: (1) Insurance issuers reduced HIM participation across both rural and urban places (with 1.7 and 2.2 issuers, respectively), both in states that expanded Medicaid under the PPACA and in non-expansion states. (2) The average adjusted premium (before premium subsidy) continues to rise across all of the above categories, and the gap has widened between the 32 Medicaid expansion and 19 non-expansion states. Average premiums in rural counties are higher than average premiums in urban counties in both expansion and non-expansion states (by $43 per month and $27 per month, respectively). (3) Prior trends of lower premium changes at greater population densities are no longer observed in the 2018 data. (4) In 2018, 1,581 counties (52 perent) have one participating insurance issuer. Nationwide, 42 percent of all urban counties and 55 percent of all rural counties only have one issuer.

Purpose. From October 2013—before implementation of the Affordable Care Act (ACA)—to November 2016, Medicaid enrollment grew by 27 percent. However, very little attention has been paid to date to how changes in Medicaid enrollment vary within states across the rural-urban continuum. This brief reports and analyzes changes in enrollment in metropolitan, micropolitan, and rural (noncore) areas in both expansion states (those that used ACA funding to expand Medicaid coverage) and nonexpansion states (those that did not use ACA funding to expand Medicaid coverage). The findings suggest that growth has been uneven across rural-urban geography, and that Medicaid enrollment growth is lower in rural counties, particularly in nonexpansion states. Key Findings. (1) Medicaid growth rates in metropolitan counties in nonexpansion states from 2012 to 2015 were twice as large as in rural counties (14 percent compared to 7 percent). (2) In contrast, the differential in growth rates between metropolitan, micropolitan, and rural counties was much less dramatic in expansion states (growth rates of 43 percent, 38 percent, and 38 percent, respectively). (3) Analysis at the state level shows much variability across the states, even when controlling for expansion status. For example, some states with an above-average rural population, such as Tennessee and Idaho, had higher-than-average enrollment increases, with strong rural increases, while other states with similar proportions of rural residents, such as Nebraska, Oklahoma, Maine, and Wyoming, experienced enrollment decreases in micropolitan and/or rural counties. (4) States’ pre-ACA Medicaid eligibility levels for parents and children affected the potential for growth. For example, some states that had higher eligibility levels (e.g., Maryland and Illinois) experienced lower Medicaid growth rates from 2012 to 2015, in part because their baseline enrollment was higher. (5) In the expansion states of Colorado and Nevada, which both have State-Based Marketplaces (SBMs), enrollment increases were over four times the overall average.

Purpose. In this brief, cumulative county-level enrollment in Health Insurance Marketplaces (HIMs) through March 2016 is presented for state HIMs operated as Federally Facilitated Marketplaces (FFMs) and for those operated as Federally Supported State-Based Marketplaces (FS-SBMs). Enrollment rates in metropolitan and non-metropolitan areas of each state, defined as the percentage of “potential market” participants selecting plans, are presented. Monitoring annual enrollment rates provides a gauge of how well state outreach and enrollment efforts are proceeding and helps identify states with strong non-metropolitan enrollment as models for other states to emulate. Key Findings. (1) Cumulative enrollment in the HIMs in non-metropolitan counties has grown to about 1.4 million in 2016, representing 40 percent of the potential market in non-metropolitan counties. (2) Estimated enrollment rates varied considerably across the United States. In particular, estimated enrollment rates in non-metropolitan areas were substantially higher than in metropolitan areas in Hawaii, Illinois, Michigan, Montana, Maine, Nebraska, Wisconsin, and Wyoming. (3) The states that achieved the highest absolute non-metropolitan enrollment totals were Michigan, Georgia, Missouri, North Carolina, Texas, and Wisconsin. Of these, Michigan, North Carolina, and Wisconsin also had non-metropolitan enrollment rates above 50 percent. (4) About half of all states, evenly distributed by Medicaid expansion status but mostly concentrated in the Midwestern census region, had higher enrollment growth in non-metropolitan areas from 2015 to 2016, and in fact aggregated non-metropolitan growth was greater than metropolitan growth in both expansion categories.

Purpose. In this policy brief, we assess variation in Medicare’s star quality ratings of Medicare Advantage (MA) plans that are available to rural beneficiaries. Evidence from the recent Centers for Medicare & Medicaid Services (CMS) quality demonstration suggests that market dynamics, i.e., firms entering and exiting the MA marketplace, play a role in quality improvement. Therefore, we also discuss how market dynamics may impact the smaller and less wealthy populations that are characteristic of rural places. Key Data Findings. (1) Highly rated MA plans serving rural Medicare beneficiaries are more likely to be health maintenance organizations (HMOs) and local preferred provider organizations (PPOs), as opposed to regional PPOs. HMOs and local PPOs may be better able to improve their quality scores strategically in response to the bonus payment incentive due to existing internal monitoring mechanisms. (2) On average, the rural enrollment rate is lower in plans with higher quality scores (59 percent) than the corresponding urban rate (71 percent). This differential is likely due, in part, to lack of availability of highly rated plans in rural areas: 17.8 percent of rural counties lacked access to a plan with four or more (out of five) stars, while just 3.7 percent of urban counties lacked such access. (3) MA plans with high quality scores have been operating longer, on average, and have a lower percentage of rural counties within their contract service areas than plans with lower quality scores.

Since 2014, when the Health Insurance Marketplaces (HIMs) authorized by the Patient Protection and Affordable Care Act (ACA) were implemented, considerable premium changes have been observed in the marketplaces across the 50 states and the District of Columbia. This policy brief assesses the changes in average HIM plan premiums from 2014 to 2016, before accounting for subsidies, with an emphasis on the widening variation across rural and urban places. Since this brief focuses on premiums without accounting for subsidies, this is not intended to be an analysis of the "affordability" of ACA premiums, as that would require assessment of premiums, cost-sharing adjustments, and other factors.

Payment to Medicare Advantage (MA) plans was fundamentally altered in the Patient Protection and Affordable Care Act of 2010 (ACA). MA plans now operate under a new formula for county-level payment area benchmarks, and in 2012 began receiving quality-based bonus payments. The Medicare Advantage Quality Bonus Payment Demonstration expanded the bonus payments to most MA plans through 2014; however, with the end of the demonstration bonus payments has been reduced for intermediate quality MA plans. This brief examines the impact that these changes in MA baseline payment are having on MA plans and beneficiaries in rural and urban areas. Key Data Findings. (1) Payments to plans in rural areas were 3.9 percent smaller under ACA payment policies in 2015 than they would have been in the absence of the ACA. For plans in urban areas, the payments were 8.8 percent smaller than they would have been. These figures were determined using hypothetical pre-ACA and actual ACA-mandated benchmarks for 2015. (2) MA plans in rural areas received an average annual bonus payment of $326.77 per enrollee in 2014, but only $63.76 per enrollee in 2015, with the conclusion of the demonstration. (3) In 2014, 92 percent of rural MA beneficiaries were in a plan that received quality-based bonus payments under the demonstration, while in March 2015, 56 percent of rural MA beneficiaries were in a plan that was eligible for quality-based bonus payments.

Since passage of the Patient Protection and Affordable Care Act (ACA), much attention has been focused on the functioning of Health Insurance Marketplaces (HIMs). In this brief, cumulative county-level enrollment in HIMs through March 2015 is presented for state HIMs operated as Federally Facilitated Marketplaces (FFMs) and Federally Supported State-Based Marketplaces (FS-SBMs). We provide comparisons between enrollment in urban and rural areas of each state and corresponding percentages of "potential market" participants enrolled. Given differences in populations eligible for HIM enrollment, we analyzed Medicaid expansion states separately. This analysis provides a gauge of how well outreach and enrollment efforts are proceeding in the states. Key Findings. (1) Overall, people living in metropolitan areas were more likely to enroll in HIMs than were people in non-metropolitan areas, as 38.9 percent of potentially eligible metropolitan residents in Medicaid expansion states and 47.5 percent in non-expansion states were enrolled in HIMs, compared to 33.9 percent and 37.3 percent in nonmetropolitan areas, respectively. (2) Estimated enrollment rates varied considerably across the United States. In particular, estimated enrollment rates in non-metropolitan areas are higher than in metropolitan areas in Illinois, Maine, Michigan, Montana, Nebraska, Nevada, New Hampshire, North Dakota, Wisconsin, and Wyoming. (3) The states with the highest rural enrollment percentages were Maine, Michigan, Montana, North Carolina, New Hampshire, South Carolina, and Wisconsin. States with high absolute rural enrollment were about as likely to be Medicaid expansion states to be as non-expansion states, and they were slightly less likely to belong to the South census region.

The Patient Protection and Affordable Care Act established Health Insurance Marketplaces (HIMs) in all 50 states and the District of Columbia. This policy brief assesses the changes in HIMs from 2014 to 2015 in terms of choices offered and premiums charged, with emphasis on how these measures vary across rural and urban places. Key Findings. (1) In 74 percent of HIM rating areas, the number of firms operating increased by at least one, while the number of firms decreased in only about 6 percent of rating areas. Further, 64 percent of rating areas with fewer than 50 persons per square mile gained at least one firm. (2) There was no consistent pattern of premium increases with respect to rating area population density (used as a proxy here for the degree of "ruralness" of the rating areas). Nationally, rural areas are not experiencing higher premium increases than their urban counterparts. In fact, the lowest increases in second-lowest cost silver plan premiums occurred in the medium-density population rating areas of 51 to 300 persons per square mile. (3) Average adjusted premiums increased from 2014 to 2015 by 6.7 percent in Federally-Facilitated Marketplaces (FFMs) compared to just 1.4 percent in State-Based Marketplaces (SBMs). Regardless of SBM or FFM status, premium increases across the United States were negatively correlated with the number of firms entering the market. (4) Analysis of the most rural states, in terms of percentage of the population classified as nonmetropolitan, shows that, in general, premiums fell significantly in rural places where they had been rather high, and they increased in rural places where they had been rather low. The five rural states with the lowest premium increases had an average of 0.17 firms entering the market, while the five with the highest premium increases had an average of 0.50 firms exiting the market.

Key Data Findings. (1) Reclassification of rural and urban county designations (due to the switch from 2000 census data to 2010 census data) resulted in a 10 percent decline in the number of Medicare eligible Americans living in rural counties in 2014 (from roughly 10.7 million to 9.6 million). These changes also resulted in a decline in the number of MA enrollees considered to be living in a rural area, from 2.19 million to 1.95 million. However, the percentage of Medicare beneficiaries enrolled in MA and prepaid plans in rural areas declined only slightly from 20.6 percent to 20.3 percent. (2) Rural Medicare Advantage (MA) and other prepaid plan enrollment in March 2014 was nearly 1.95 million, or 20.3 percent of all rural Medicare beneficiaries, an increase of more than 216,000 from March 2013. Enrollment increased to 1.99 million (20.4 percent) in October 2014. (3) In March 2014, 56 percent of rural MA enrollees were enrolled in Preferred Provider Organization (PPO) plans, 29 percent were enrolled in Health Maintenance Organization (HMO) or Point-of-Service (POS) plans, 7 percent were enrolled in Private Fee-for-Service (PFFS) plans, and 8 percent were enrolled in other prepaid plans, including Cost plans and Program of All-Inclusive Care for the Elderly (PACE) plans. (4) States with the highest percentage of rural Medicare beneficiaries enrolled in MA and other prepaid plans include Minnesota (49.1 percent), Hawaii (41.1 percent), Pennsylvania (35.4 percent), Wisconsin (34.3 percent), New York (30.4 percent), and Ohio (30.1 percent).

This policy brief analyzes the 2014 premiums associated with qualified health plans (QHPs) made available through new health insurance marketplaces (HIMs), an implementation of the Patient Protection and Affordable Care Act (ACA) of 2010. We report differences in premiums by insurance rating areas while controlling for other important factors such as the actuarial value of the plan (metal level), cost-of-living differences, and state-level decisions over type of rating area. While market equilibrium, based on experience and understanding of the characteristics of the new market, should not be expected this soon, preliminary results give policymakers key issues to monitor.

Key Findings. (1) State-level decisions in implementing the Patient Protection and Affordable Care Act of 2010 (ACA) have led to significant state variation in the design of Health Insurance Marketplace (HIM) rating areas. In some designs, rural counties are grouped together, while in others, rural and urban counties have been deliberately mixed. (2) Urban counties have, on average, approximately one more firm participating in the marketplaces, representing about 11 more plan offerings, than rural counties have. (3) The highest-valued "platinum" plan types are less likely to be available in rural areas. Thus, the overall mix of plan types should be factored into the reporting of average premiums. (4) Levels of competition are likely to have a greater impact on the decisions of firms considering whether to operate in higher-cost areas or not, as those firms must determine how they can pass such costs on to consumers, conditional on the market share they are likely to control.

Key Findings. (1) Assuming Medicaid expansion in each of the fifty states and the District of Columbia, a larger proportion of the rural (non-metropolitan) uninsured (43.5%) than the urban uninsured (38.5%) would be eligible for Medicaid. (2) In both urban and rural places, across the adult non-elderly population, uninsured rates decline dramatically with age. (3) Within each age group of the uninsured, rural people are less likely to have incomes above 400% of the federal poverty level (FPL), meaning that overall more rural uninsured would be eligible for some form of health insurance assistance under the Patient Protection and Affordable Care Act (ACA), either subsidized coverage in new marketplaces, or through Medicaid if all states were to implement expansion. (4) While over half of the uninsured in both rural and urban areas are younger than 40 years, the uninsured in rural areas are disproportionately older across all income categories, which reflects the age distribution in the population.

Key Data Findings. (1) The average rural Medicare Advantage (MA) plan enrollee in 2012 experienced a quality rating of 3.60 stars (of a potential 5.0), compared with a rating of 3.71 stars experienced by urban enrollees. (2) The measured rural-urban difference in the MA plan quality is a result of the difference in the composition of the enrollment and plan availability in MA markets, rather than differences between MA plans of the same type. (a) In general, rural Medicare beneficiaries often have limited MA plans available from which to choose, and typically have lower quality ratings than urban MA plans. (b) Rural MA beneficiaries are more likely to be enrolled in preferred provider organization (PPO) plans than in health maintenance organization (HMO) plans. (c) PPO plans have lower quality ratings on average than HMO plans. (d) HMO plans had the highest average quality rating at 3.83 and 3.78 stars, respectively, in rural and urban areas. PPO plans had lower quality ratings, at 3.52 and 3.50, respectively. (3) In rural areas, 32% of the MA population is enrolled in a plan with a star rating of 4.0 or higher, and 92% are enrolled in a plan with a star rating of at least 3.0, as contrasted to urban enrollment of 36% and 94% respectively, making these plans eligible for quality based bonus payments. (4) The quality rating of rural MA plans varies significantly across the country, with the highest quality ratings in rural areas in Minnesota, Iowa, Wisconsin, Oregon, Pennsylvania, and Maine.

Key Data Findings. (1) From March 2012 to March 2013, rural enrollment in Medicare Advantage (MA) and other prepaid plans increased by over 200,000 enrollees, to more than 1.9 million. (2) Preferred provider organization (PPO) plan enrollment increased to nearly one million enrollees, accounting for more than 51% of the rural MA market (up from 48% in March 2012). (3) Health maintenance organization (HMO) enrollment continued to grow in 2013, with over 31% of the rural MA market, while private fee-for-service (PFFS) plan enrollment decreased to less than 10% of market share. (4) Despite recent changes to MA payment, rural MA enrollment continues to increase.

Key Findings. (1) A larger proportion of the rural population than the urban population is uninsured and low income (living at or below 138% of the federal poverty line [FPL]) (9.9% as compared to 8.5%) and a larger proportion of the rural population than the urban population will be eligible for subsidized Health Insurance Marketplace (HIM) coverage due to income levels and current lack of insurance (10.7% as compared to 9.6%). (2) Assuming full Medicaid expansion, a larger proportion of the rural uninsured than the urban uninsured would be eligible for Medicaid (43.5% as compared to 38.5%). (3) A smaller proportion of the rural uninsured than the urban uninsured has income above 400% FPL and thus will not qualify for either Medicaid or HIM subsidies (10% as compared to 14.1%). (4) The proportion of the uninsured population potentially eligible for Medicaid expansion is highest in the rural South (47.5%) and lowest in the urban Northeast (32.5%) and the rural Northeast (35.8%).

Key Data Findings. (1) Rural Medicare Advantage (MA) enrollment grew to over 1.7 million in June 2012 (17% of eligible beneficiaries), while total MA enrollment grew to nearly 13.4 million (27% of eligible beneficiaries). (2) Rural preferred provider organization (PPO) and health maintenance organization (HMO) enrollment grew to over 840 thousand (48% of the market) and 532 thousand (31% of the market), respectively, while private fee-for-service (PFFS) enrollment fell to 230 thousand in rural areas (13% of the market). (3) Rural MA enrollment varies across the country with concentrations of enrollment on the West Coast, the Great Lakes, and the Northeast regions of the United States. (4) The average monthly weighted premium for rural MA plans with prescription drugs fell in 2012 to $48 from $52 in 2011, but it remains significantly higher than the urban average which also fell during the same time from $38 to $34. (5) Zero premium plans are available to 73% of rural MA beneficiaries and to 95% of urban beneficiaries; however, only 48% of rural beneficiaries that have this option choose these plans compared to 63% of urban beneficiaries. The resulting average non-zero premium was $72 in rural areas in 2012, while the average non-zero premium in urban areas was $81. (6) Roughly a third (35%) of rural MA beneficiaries receive their MA coverage including prescription drugs without having to pay a premium, however this is significantly lower than 60% of urban beneficiaries that do not have to pay a premium.