Maryland's Global Budget Revenue Payment Model and Shifts in the Surgical Site of Care Among Medicare Beneficiaries.

OBJECTIVE: To assess the association between the Global Budget Revenue (GBR) payment model and shifts to the outpatient setting for surgical procedures among Medicare fee-for-service beneficiaries in Maryland versus control states. SUMMARY BACKGROUND DATA: The GBR model provides fixed global payments to hospitals to reduce spending growth and incentivize hospitals to reduce the costs of care while improving care quality. Since surgical care is a major contributor to hospital spending, the GBR model might accelerate the ongoing shift from the inpatient to the outpatient setting to generate additional savings. METHODS: A difference-in-differences (DiD) design was used to compare changes in surgical care settings over time from pre-GBR (2011-2013) to post-GBR (2014-2018) for Maryland versus control states for common surgeries that could be performed in the outpatient setting. A cross-sectional approach was used to compare the difference in care settings in 2018 for total knee arthroplasty which was on Medicare's Inpatient-Only List before then. RESULTS: We studied 47,542 surgical procedures from 44,410 beneficiaries in Maryland and control states. GBR's 2014 implementation was associated with an acceleration in the shift from inpatient to outpatient settings for surgical procedures in Maryland (DiD: 3.9 percentage points, 95% CI: 2.3, 5.4). Among patients undergoing total knee arthroplasty in 2018, the proportion of outpatient surgeries in Maryland was substantially higher than that in control states (difference: 27.6 percentage points, 95% CI: 25.6, 29.6). CONCLUSIONS: Implementing Maryland's GBR payment model was associated with an acceleration in the shift from inpatient to outpatient hospital settings for surgical procedures.

Using the Moving To Opportunity Experiment to Investigate the Long-Term Impact of Neighborhoods on Healthcare Use by Specific Clinical Conditions and Type of Service.

We performed a secondary analysis of the Moving To Opportunity (MTO) social experiment to investigate the impact of different types of housing assistance and neighborhood environments on long-term patterns of health care use for specific conditions and across different types of health care services. MTO participants, who were randomized at baseline, were linked to up to 21 years of all-payer hospital discharge and Medicaid data. Among the 9,170 children at the time of randomization, those who received a voucher had subsequent hospital admissions rates that were 36% lower for asthma and 30% lower for mental health disorders compared to the control group; rates of psychiatric services, outpatient hospital services, clinic services and durable medical equipment were also lower among the voucher groups. Findings for adults were not statistically significant. The results suggest that housing policies that reduce neighborhood poverty exposure as a child are associated with lower subsequent healthcare use for specific clinical conditions and types of services.

Trends in Episode-of-Care Spending for Cancer-Directed Surgery Among US Medicare Beneficiaries From 2011 to 2019.

This cross-sectional study examines trends in the number of cancer-directed surgeries from 2011 to 2019 among US patients aged 65 years or older and in Medicare spending for those surgeries overall and by inpatient vs outpatient sites of care.

Association of Chain Restaurant Advertising Spending With Obesity in US Adults.

Importance: Restaurants spend billions of dollars on marketing. However, little is known about the association between restaurant marketing and obesity risk in adults. Objective: To examine associations between changes in per capita county-level restaurant advertising spending over time and changes in objectively measured body mass index (BMI) for adult patients. Design, Setting, and Participants: This cohort study used regression models with county fixed effects to examine associations between changes in per capita county-level (370 counties across 44 states) restaurant advertising spending over time with changes in objectively measured body mass index (BMI) for US adult patients from 2013 to 2016. Different media types and restaurant types were analyzed together and separately. The cohort was derived from deidentified patient data obtained from athenahealth. The final analytic sample included 5 987 213 patients, and the analysis was conducted from March 2018 to November 2019. Exposure: Per capita county-level chain restaurant advertising spending. Main Outcomes and Measures: Individual-level mean BMI during the quarter. Results: The included individuals were generally older (37.1% older than 60 years), female (56.8%), and commercially insured (53.5%). For the full population of 29 285 920 person-quarters, there was no association between changes in all restaurant advertising per capita (all media types, all restaurants) and changes in BMI. However, restaurant advertising spending was positively associated with weight gain for patients in low-income counties but not in high-income counties. A $1 increase in quarterly advertising per capita across all media and restaurant types was associated with a 0.053-unit increase in BMI (95% CI, 0.001-0.102) for patients in low-income counties, corresponding to a 0.12% decrease in BMI at the 10th percentile of changes in county advertising spending vs a 0.12% increase in BMI at the 90th percentile. Conclusions and Relevance: The results of this study suggest that restaurant advertising is associated with modest weight gain among adult patients in low-income counties. To date, there has been no public policy action or private sector action to limit adult exposure to unhealthy restaurant advertising. Efforts to decrease restaurant advertising in low-income communities should be intensified and rigorously evaluated to understand their potential for increasing health equity.

Impact of Changes in Chain Restaurant Calories over Time on Obesity Risk.

BACKGROUND: Prior research on the restaurant environment and obesity risk is limited by cross-sectional data and a focus on specific geographic areas. OBJECTIVE: To measure the impact of changes in chain restaurant calories over time on body mass index (BMI). DESIGN: We used a first-difference model to examine whether changes from 2012 to 2015 in chain restaurant calories per capita were associated with percent changes in BMI. We also examined differences by race and county income, restaurant type, and initial body weight categories. SETTING: USA (207 counties across 39 states). PARTICIPANTS: 447,873 adult patients who visited an athenahealth medical provider in 2012 and 2015 where BMI was measured. MAIN OUTCOMES MEASURED: Percent change in objectively measured BMI from 2012 to 2015. RESULTS: Across all patients, changes in chain restaurant calories per capita were not associated with percent changes in BMI. For Black or Hispanic adults, a 10% increase in exposure to chain restaurant calories per capita was associated with a 0.16 percentage-point increase in BMI (95% CI 0.03, 0.30). This translates into a predicted weight increase of 0.89 pounds (or a 0.53% BMI increase) for an average weight woman at the 90th percentile of increases in the restaurant environment from 2012 to 2015 versus an increase 0.39 pounds (or 0.23% BMI increase) at the 10th percentile. Greater increases in exposure to chain restaurant calories also significantly increased BMI for Black or Hispanic adults receiving healthcare services in lower-income counties (0.26, 95% CI 0.04, 0.49) and with overweight/obesity (0.16, 95% CI 0.04, 0.29). LIMITATIONS: Generalizability to non-chain restaurants is unknown and the sample of athenahealth patients is relatively homogenous. CONCLUSIONS: Increased exposure to chain restaurant calories per capita was associated with increased weight gain among Black or Hispanic adults.

Quantifying Overinsurance Tied to the Tax Exclusion for Employment-Based Health Insurance and Its Variation by Health Status.

The exclusion of employment-based health insurance from income and payroll taxes is thought to increase the generosity of insurance coverage and, in turn, increase the overutilization of low-value health care services. We examine this inefficiency of overinsurance by quantifying the change in expected utility across 4 benchmark plans varying in actuarial value (AV) and focus on the distribution of each of these estimates across different groups of people varying in health status. Specifically, we quantify the changes in health care spending due to moral hazard and the changes in uncertainty tied to risk aversion using data from the nationally representative sample of adults with employment-based coverage from the 2007-2016 Medical Expenditure Panel Survey, and produce estimates of expected utility for 24 groups of people based on their age, gender, and preexisting conditions. Our model suggests an average preferred AV of 78% without the tax exclusion, with 29.0% of the population preferring a 60% AV, 6.5% preferring a 70% AV, 18.1% preferring an 80% AV, and 46.4% preferring a 90% AV. When incorporating the distortionary effect of the employment-based tax exclusion, the preferred plan increases to an 83% AV for low-income people (with 71.0% of the population preferring a 90% AV) and an 84% AV for high-income people (with 76.0% of the population preferring a 90% AV). We estimate that policy changes to make subsidies independent of a plan's AV could result in increases in utility equal to about 2.7% of total health care spending, but with those net gains concentrated among the healthy.

Association of Receipt of a Housing Voucher With Subsequent Hospital Utilization and Spending.

Importance: Although neighborhoods are thought to be an important health determinant, evidence for the relationship between neighborhood poverty and health care use is limited, as prior studies have largely used observational data without an experimental design. Objective: To examine whether housing policies that reduce exposure to high-poverty neighborhoods were associated with differences in long-term hospital use among adults and children. Design, Setting, and Participants: Exploratory analysis of the Moving to Opportunity for Fair Housing Demonstration Program, a randomized social experiment conducted in 5 US cities. From 1994 to 1998, 4604 families in public housing were randomized to 1 of 3 groups: a control condition, a traditional Section 8 voucher toward rental costs in the private market, or a voucher that could only be used in low-poverty neighborhoods. Participants were linked to all-payer hospital discharge data (1995 through 2014 or 2015) and Medicaid data (1999 through 2009). The final follow-up date ranged from 11 to 21 years after randomization. Exposures: Receipt of a traditional or low-poverty voucher vs control group. Main Outcomes and Measures: Rates of hospitalizations and hospital days, and hospital spending. Results: Among 4602 eligible individuals randomized as adults, 4072 (88.5%) were linked to health data (mean age, 33 years [SD, 9.0 years]; 98% female; median follow-up, 11 years). There were no significant differences in primary outcomes among adults randomized to receive a voucher compared with the control group (unadjusted hospitalization rate, 14.0 vs 14.7 per 100 person-years, adjusted incidence rate ratio [IRR], 0.95 [95% CI, 0.84-1.08; P = .45]; hospital days, 62.8 vs 67.0 per 100 person-years; IRR, 0.93 [95% CI, 0.77-1.13; P = .46]; yearly spending, $2075 vs $1977; adjusted difference, -$129 [95% CI, -$497 to $239; P = .49]). Among 11 290 eligible individuals randomized as children, 9118 (80.8%) were linked to health data (mean age, 8 years [SD, 4.6 years]; 49% female; median follow-up, 11 years). Receipt of a housing voucher during childhood was significantly associated with lower hospitalization rates (6.3 vs 7.3 per 100 person-years; IRR, 0.85 [95% CI, 0.73-0.99; P = .03]) and yearly inpatient spending ($633 vs $785; adjusted difference, -$143 [95% CI, -$256 to -$31; P = .01]) and no significant difference in hospital days (25.7 vs 28.8 per 100 person-years; IRR, 0.92 [95% CI, 0.77-1.11; P = .41]). Conclusions and Relevance: In this exploratory analysis of a randomized housing voucher intervention, adults who received a housing voucher did not experience significant differences in hospital use or spending. Receipt of a voucher during childhood was significantly associated with lower rates of hospitalization and less inpatient spending during long-term follow-up.

Experiment To Decrease Neighborhood Poverty Had Limited Effects On Emergency Department Use.

Neighborhood environments are increasingly thought to affect emergency department (ED) use. However, because people decide where to live based on a range of factors, it can be challenging to identify the causal impact of living in higher-poverty neighborhoods on increased rates of ED visits. Our study leveraged the Moving to Opportunity for Fair Housing Demonstration Program, a social experiment beginning in 1994 that randomly assigned approximately 4,600 households that received federal housing assistance to different neighborhood conditions. We linked program participants in four states with an average of twelve years of administrative data on ED use (up to twenty-one years after randomization). Contrary to our expectations, we did not find a consistently significant connection between neighborhood poverty and overall ED use during this follow-up period. This result was observed for both adults and people who were children at the time of randomization, as well as for various classifications of ED visits. The findings can help direct future research that seeks to clarify the relationship between neighborhood environments and health care use.

Measuring Nonprofit Hospitals' Provision of Charity Care Using IRS and CMS Data.

EXECUTIVE SUMMARY: We explore whether nonprofit hospitals report similar amounts of charity care to the Internal Revenue Service (IRS) and Centers for Medicare & Medicaid Services (CMS). We use nonprofit hospitals' financial reports to the IRS and the CMS Medicare costs report for 2011 and 2012. In 2012, hospitals reported spending 7.6% more in charity care to the IRS than to CMS: 2.54% of revenues ($5.74 million per hospital) to the IRS versus 2.36% ($5.16 million) to CMS. While the averages are close, there are wide discrepancies for individual hospitals. For example, despite efforts for standardization, 80% of hospitals reported charity care to the CMS that was 40% greater in absolute value than what they reported to the IRS, and only 10% of hospitals reported charity care to CMS that was within 20% of what they reported to the IRS. Our findings suggest that individual hospitals routinely report different amounts of charity care to the IRS and CMS, yet we find relatively few hospital or market characteristics that may explain these differences.

Do health insurance and hospital market concentration influence hospital patients' experience of care?

OBJECTIVE: To examine the effects of insurance and hospital market concentration on hospital patients' experience of care, as hospitals may compete on quality for favorable insurance contracts. DATA SOURCES/STUDY SETTING: Secondary data for 2008-2015 on patient experience from Hospital Compare's patient survey data, hospital characteristics from the American Hospital Association (AHA) Annual Survey, and insurance market characteristics from HealthLeaders-InterStudy. STUDY DESIGN: Hospital/year-level regressions predict each hospital's patient experience measure as a function of insurance and hospital market concentration and hospital fixed effects. The model is identified by longitudinal variation in insurance and hospital concentration. DATA COLLECTION/EXTRACTION METHODS: Hospital/year-level data from Hospital Compare and the AHA merged by market/year to insurance and hospital concentration measures. PRINCIPAL FINDINGS: Changes in patient satisfaction are positively associated with increases in insurance concentration and negatively associated with increases in hospital concentration. Moving from a market with 20th percentile insurance concentration and 80th percentile hospital concentration to a market with 80th percentile insurance concentration and 20th percentile hospital concentration increases the share of patients that rated the hospital highly from 66.9 percent (95% CI: 66.5-67.2 percent) to 67.9 percent (95% CI: 67.5-68.3 percent) and the share of patients that definitely recommend the hospital from 69.7 percent (95% CI: 69.4-70.0 percent) to 70.8 percent (95% CI: 70.5-71.2 percent). The relationship for insurance concentration is stronger in more concentrated hospital markets, while the relationship for hospital concentration is stronger in less concentrated hospital markets. CONCLUSIONS: These findings add to the evidence on the harms of hospital consolidation but suggest that insurer consolidation may improve patient experience.

Association of a Beverage Tax on Sugar-Sweetened and Artificially Sweetened Beverages With Changes in Beverage Prices and Sales at Chain Retailers in a Large Urban Setting.

Importance: Policy makers have implemented beverage taxes to generate revenue and reduce consumption of sweetened drinks. In January 2017, Philadelphia, Pennsylvania, became the second US city to implement a beverage excise tax (1.5 cents per ounce). Objectives: To compare changes in beverage prices and sales following the implementation of the tax in Philadelphia compared with Baltimore, Maryland (a control city without a tax) and to assess potential cross-border shopping to avoid the tax in neighboring zip codes. Design, Setting, and Participants: This study used a difference-in-differences approach and analyzed sales data to compare changes between January 1, 2016, before the tax, and December 31, 2017, after the tax. Differences by store type, beverage sweetener status, and beverage size were examined. The commercial retailer sales data included large chain store sales in Philadelphia, Baltimore, and the Pennsylvania zip codes bordering Philadelphia. These data reflect approximately 25% of the ounces of taxed beverages sold in Philadelphia. Exposures: Philadelphia's tax on sugar-sweetened and artificially sweetened beverages. Main Outcomes and Measures: Change in taxed beverage prices and volume sales. Results: A total of 291 stores (54 supermarkets, 20 mass merchandise stores, 217 pharmacies) were analyzed. The mean price per ounce of taxed beverages in Philadelphia increased from 5.43 cents in 2016 to 6.24 cents in 2017 at supermarkets; from 5.28 cents to 6.24 cents at mass merchandise stores, and from 6.60 cents to 8.28 cents at pharmacies. The mean price per ounce in Baltimore increased from 5.33 cents in 2016 to 5.50 cents in 2017 at supermarkets, from 6.34 cents to 6.52 cents at mass merchandise stores, and from 6.76 cents to 6.93 cents at pharmacies. The mean per-ounce difference in price between the 2 cities was 0.65 cents (95% CI, 0.60 cents-0.69 cents; P<.001) at supermarkets; 0.87 cents (95 % CI, 0.72 cents-1.02 cents; P<.001) at mass merchandise stores, and 1.56 cents (95% CI, 1.50 cents-1.62 cents; P<.001) at pharmacies. Total volume sales of taxed beverages in Philadelphia decreased by 1.3 billion ounces (from 2.475 billion to 1.214 billion) or by 51.0% after tax implementation. Volume sales in the Pennsylvania border zip codes, however, increased by 308.2 million ounces (from 713.1 million to 1.021 billion), offsetting the decrease in Philadelphia's volume sales by 24.4%. In Philadelphia, beverage volume sales in ounces per 4-week period between before and after tax periods decreased from 4.85 million to 1.99 million at supermarkets, from 2.98 million to 1.72 million at mass merchandise stores, and from 0.16 million to 0.13 million at pharmacies. In Baltimore, the beverage volume sales in ounces decreased from 2.83 million to 2.81 million at supermarkets, from 1.05 million to 1.00 million at mass merchandise stores, and from 0.14 million to 0.13 million at pharmacies. This was a 58.7% reduction at supermarkets (difference-in-differences, -2.85 million ounces; 95% CI, -4.10 million to -1.60 million ounces; P < .001), 40.4% reduction at mass merchandise stores (difference-in-differences, -1.20 million ounces; 95% CI, -2.04 million to -0.36 million ounces; P = .001), and 12.6% reduction in pharmacies (difference-in-differences, -0.02 million ounces; 95% CI, -0.03 million to -0.01 million ounces; P < .001). Conclusions and Relevance: In Philadelphia in 2017, the implementation of a beverage excise tax on sugar-sweetened and artificially sweetened beverages was associated with significantly higher beverage prices and a significant and substantial decline in volume of taxed beverages sold. This decrease in taxed beverage sales volume was partially offset by increases in volume of sales in bordering areas.

The effects of global budget payments on hospital utilization in rural Maryland.

OBJECTIVE: To assess the effect of Maryland's 2010 Total Patient Revenue (TPR) global budget reform in eight rural hospitals on population-level hospital rates of utilization three years after implementation. DATA SOURCES/STUDY SETTING: Data on all inpatient discharges and outpatient department visits from the Health Services Cost Review Commission, population data from Claritas Demographic Reports, and county-level data from the Area Health Resource File. STUDY DESIGN: We use a difference-in-differences approach to compare changes in utilization rates over time in the reform areas comprising 125 Zip Code Tabulation Areas (ZCTAs) and in two control hospital areas (66 ZCTAs and 327 ZCTAs, respectively). We examine several inpatient and outpatient measures and distinguish between relatively discretionary and nondiscretionary utilization. DATA COLLECTION: Admissions data are hospital-reported discharge abstracts of all encounters in Maryland during 2008-2013. Population data are derived from the US Census. PRINCIPAL FINDINGS: We find no statistically significant changes in admissions, either overall or discretionary. We find a statistically significant 8.9 percent (95%CI = [1.8, 16.0]) reduction in outpatient visits, with a statistically significant reduction of 14.8 percent (95%CI = [5.3, 24.3]) visits not to the Emergency Department. CONCLUSIONS: We find that the TPR reform decreased outpatient utilization but did not affect inpatient utilization.

Association of a Beverage Tax on Sugar-Sweetened and Artificially Sweetened Beverages With Changes in Beverage Prices and Sales at Chain Retailers in a Large Urban Setting.

Importance: Policy makers have implemented beverage taxes to generate revenue and reduce consumption of sweetened drinks. In January 2017, Philadelphia, Pennsylvania, became the second US city to implement a beverage excise tax (1.5 cents per ounce). Objectives: To compare changes in beverage prices and sales following the implementation of the tax in Philadelphia compared with Baltimore, Maryland (a control city without a tax) and to assess potential cross-border shopping to avoid the tax in neighboring zip codes. Design, Setting, and Participants: This study used a difference-in-differences approach and analyzed sales data to compare changes between January 1, 2016, before the tax, and December 31, 2017, after the tax. Differences by store type, beverage sweetener status, and beverage size were examined. The commercial retailer sales data included large chain store sales in Philadelphia, Baltimore, and the Pennsylvania zip codes bordering Philadelphia. These data reflect approximately 25% of the ounces of taxed beverages sold in Philadelphia. Exposures: Philadelphia's tax on sugar-sweetened and artificially sweetened beverages. Main Outcomes and Measures: Change in taxed beverage prices and volume sales. Results: A total of 291 stores (54 supermarkets, 20 mass merchandise stores, 217 pharmacies) were analyzed. The mean price per ounce of taxed beverages in Philadelphia increased from 5.43 cents in 2016 to 6.24 cents in 2017 at supermarkets; from 5.28 cents to 6.24 cents at mass merchandise stores, and from 6.60 cents to 8.28 cents at pharmacies. The mean price per ounce in Baltimore increased from 5.33 cents in 2016 to 5.50 cents in 2017 at supermarkets, from 6.34 cents to 6.52 cents at mass merchandise stores, and from 6.76 cents to 6.93 cents at pharmacies. The mean per-ounce difference in price between the 2 cities was 0.65 cents (95% CI, 0.60 cents-0.69 cents; P<.001) at supermarkets; 0.87 cents (95 % CI, 0.72 cents-1.02 cents; P<.001) at mass merchandise stores, and 1.56 cents (95% CI, 1.50 cents-1.62 cents; P<.001) at pharmacies. Total volume sales of taxed beverages in Philadelphia decreased by 1.3 billion ounces (from 2.475 billion to 1.214 billion) or by 51.0% after tax implementation. Volume sales in the Pennsylvania border zip codes, however, increased by 308.2 million ounces (from 713.1 million to 1.021 billion), offsetting the decrease in Philadelphia's volume sales by 24.4%. In Philadelphia, beverage volume sales in ounces per 4-week period between before and after tax periods decreased from 4.85 million to 1.99 million at supermarkets, from 2.98 million to 1.72 million at mass merchandise stores, and from 0.16 million to 0.13 million at pharmacies. In Baltimore, the beverage volume sales in ounces decreased from 2.83 million to 2.81 million at supermarkets, from 1.05 million to 1.00 million at mass merchandise stores, and from 0.14 million to 0.13 million at pharmacies. This was a 58.7% reduction at supermarkets (difference-in-differences, -2.85 million ounces; 95% CI, -4.10 million to -1.60 million ounces; P < .001), 40.4% reduction at mass merchandise stores (difference-in-differences, -1.20 million ounces; 95% CI, -2.04 million to -0.36 million ounces; P = .001), and 12.6% reduction in pharmacies (difference-in-differences, -0.02 million ounces; 95% CI, -0.03 million to -0.01 million ounces; P < .001). Conclusions and Relevance: In Philadelphia in 2017, the implementation of a beverage excise tax on sugar-sweetened and artificially sweetened beverages was associated with significantly higher beverage prices and a significant and substantial decline in volume of taxed beverages sold. This decrease in taxed beverage sales volume was partially offset by increases in volume of sales in bordering areas.

Does Limiting Allowable Rating Variation in the Small Group Health Insurance Market Affect Employer Self-Insurance?

The Affordable Care Act (ACA) imposes adjusted community rating in the small group market, which employers can avoid by self-insuring, raising concerns about adverse selection. We evaluate the impact of limiting allowable rating variation on employer self-insurance across industries with varied health risk, using cross-state variation in pre-ACA rating regulations, the nationally-representative 2008-2013 KFF/HRET Employer Health Benefits survey, and a triple-difference regression approach. We find that lower-risk employers subject to laws limiting allowable premium rating variation have a predicted probability of self-insurance that is about 18 percentage points higher than otherwise-similar higher-risk employers, suggesting that these selection concerns are warranted.

Comparing the Value of Nonprofit Hospitals' Tax Exemption to Their Community Benefits.

The tax-exempt status of nonprofit hospitals has received increased attention from policymakers interested in examining the value they provide instead of paying taxes. We use 2012 data from the Internal Revenue Service (IRS) Form 990, Centers for Medicare and Medicaid Services (CMS) Hospital Cost Reports, and American Hospital Association's (AHA) Annual Survey to compare the value of community benefits with the tax exemption. We contrast nonprofit's total community benefits to what for-profits provide and distinguish between charity and other community benefits. We find that the value of the tax exemption averages 5.9% of total expenses, while total community benefits average 7.6% of expenses, incremental nonprofit community benefits beyond those provided by for-profits average 5.7% of expenses, and incremental charity alone average 1.7% of expenses. The incremental community benefit exceeds the tax exemption for only 62% of nonprofits. Policymakers should be aware that the tax exemption is a rather blunt instrument, with many nonprofits benefiting greatly from it while providing relatively few community benefits.

Explaining the Growth in US Health Care Spending Using State-Level Variation in Income, Insurance, and Provider Market Dynamics.

The slowed growth in national health care spending over the past decade has led analysts to question the extent to which this recent slowdown can be explained by predictable factors such as the Great Recession or must be driven by some unpredictable structural change in the health care sector. To help address this question, we first estimate a regression model for state personal health care spending for 1991-2009, with an emphasis on the explanatory power of income, insurance, and provider market characteristics. We then use the results from this simple predictive model to produce state-level projections of health care spending for 2010-2013 to subsequently compare those average projected state values with actual national spending for 2010-2013, finding that at least 70% of the recent slowdown in health care spending can likely be explained by long-standing patterns. We also use the results from this predictive model to both examine the Great Recession's likely reduction in health care spending and project the Affordable Care Act's insurance expansion's likely increase in health care spending.

How do health insurer market concentration and bargaining power with hospitals affect health insurance premiums?

The US health insurance industry is highly concentrated, and health insurance premiums are high and rising rapidly. Policymakers have focused on the possible link between the two, leading to ACA provisions to increase insurer competition. However, while market power may enable insurers to include higher profit margins in their premiums, it may also result in stronger bargaining leverage with hospitals to negotiate lower payment rates to partially offset these higher premiums. We empirically examine the relationship between employer-sponsored fully-insured health insurance premiums and the level of concentration in local insurer and hospital markets using the nationally-representative 2006-2011 KFF/HRET Employer Health Benefits Survey. We exploit a unique feature of employer-sponsored insurance, in which self-insured employers purchase only administrative services from managed care organizations, to disentangle these different effects on insurer concentration by constructing one concentration measure representing fully-insured plans' transactions with employers and the other concentration measure representing insurers' bargaining with hospitals. As expected, we find that premiums are indeed higher for plans sold in markets with higher levels of concentration relevant to insurer transactions with employers, lower for plans in markets with higher levels of insurer concentration relevant to insurer bargaining with hospitals, and higher for plans in markets with higher levels of hospital market concentration.

Reducing sugar-sweetened beverage consumption by providing caloric information: how Black adolescents alter their purchases and whether the effects persist.

OBJECTIVES: We examined the ways in which adolescents altered the type and size of their purchases of sugar-sweetened beverages (SSBs), together with whether the effects persisted after removing caloric information signs in stores. METHODS: We used a case-crossover design with 6 stores located in low-income Black neighborhoods in Baltimore, Maryland, from 2012 to 2013. The intervention used 1 of 4 randomly posted signs with caloric information: absolute calories, number of teaspoons of sugar, and number of minutes of running or miles of walking necessary to burn off a beverage. We collected data for 4516 purchases by Black adolescents, including both baseline and postintervention periods with no signs posted. RESULTS: We found that providing caloric information significantly reduced the number of total beverage calories purchased, the likelihood of buying an SSB, and the likelihood of buying an SSB greater than 16 ounces (P < .05). After removing the signs, the quantity, volume, and number of calories from SSB purchases remained lower than baseline (P < .05). CONCLUSIONS: Providing caloric information was associated with purchasing a smaller SSB, switching to a beverage with no calories, or opting to not purchase a beverage; there was a persistent effect on reducing SSB purchases after signs were removed.