14 research outputs found
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Adults with diabetes residing in "food swamps" have higher hospitalization rates.
ObjectiveTo examine the relationship between food swamps and hospitalization rates among adults with diabetes.Data sourcesBlue Cross Blue Shield Association Community Health Management Hub® 2014, AHRQ Health Care Cost and Utilization Project state inpatient databases 2014, and HHS Area Health Resources File 2010-2014.Study designCross-sectional analysis of 784 counties across 15 states. Food swamps were measured using a ratio of fast food outlets to grocers. Multivariate linear regression estimated the association of food swamp severity and hospitalization rates. Population-weighted models were controlled for comorbidities; Medicaid; emergency room utilization; percentage of population that is female, Black, Hispanic, and over age 65; and state fixed effects. Analyses were stratified by rural-urban category.Principal findingsAdults with diabetes residing in more severe food swamps had higher hospitalization rates. In adjusted analyses, a one unit higher food swamp score was significantly associated with 49.79 (95 percent confidence interval (CI) = 19.28, 80.29) additional all-cause hospitalizations and 19.12 (95 percent CI = 11.09, 27.15) additional ambulatory care-sensitive hospitalizations per 1000 adults with diabetes. The food swamp/all-cause hospitalization rate relationship was stronger in rural counties than urban counties.ConclusionsFood swamps are significantly associated with higher hospitalization rates among adults with diabetes. Improving the local food environment may help reduce this disparity
U.S. county "food swamp" severity and hospitalization rates among adults with diabetes: A nonlinear relationship.
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The Impact of Retail Availability on Health Behaviors: Policy Applications for the Prevention & Management of Chronic Conditions
Chronic conditions contribute to vast sums of excess morbidity, mortality, and healthcare expenditures. Many leading risk factors for chronic conditions are related to behavior, including poor nutrition, alcohol misuse, and tobacco use. Literature from psychology, neuroscience, and behavioral economics suggests that aspects of the environment can encourage unhealthy behaviors. This dissertation uses natural experiments and new combinations of administrative data to explore the role of retail availability in the consumption of unhealthy foods, alcohol, and tobacco and health outcomes and service utilization for chronic conditions. The first paper assesses whether or not adults with diabetes residing in “food swamps” have higher rates of hospitalizations for complications. The second paper focuses on the privatization of liquor sales that occurred in Washington in 2012, investigating if the increase in liquor availability that followed privatization impacted hospitalizations for acute and chronic alcohol-related disorders and accidental injuries. The third paper analyzes the impact of CVS Health’s 2014 tobacco-free pharmacy policy on cigarette smoking among current smokers. Findings from these papers provide additional insight into to how governmental and organizational policies may be used to better prevent and manage chronic conditions
Cigarettes smoked among daily and non-daily smokers following CVS Health's tobacco-free pharmacy policy.
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U.S. county “food swamp” severity and hospitalization rates among adults with diabetes: A nonlinear relationship
The relationship between food environments and diabetes morbidity is vastly understudied, despite the well-recognized linkage between dietary quality and diabetes complications. Further, literature demonstrates that attributes of places can have nonlinear relationships with health outcomes. This study examines the extent to which "food swamps" are associated with greater rates of hospitalizations for complications among adults with diabetes over time as well as the linearity of this relationship. We conduct a longitudinal county-level analysis of 832 counties across 16 U.S. states in 2010, 2012, and 2014 using data from the USDA Food Environment Atlas and the AHRQ Health Care Cost and Utilization Project State Inpatient Databases. Food swamp severity is measured as the percentage of food outlets in a county that sell primarily unhealthy foods. Hierarchical linear mixed models with county random intercepts are estimated, controlling for area-level covariates and state and year fixed effects. Curvilinear relationships are explored by additively incorporating quadratic terms. We find that, over the study period, mean food swamp severity remained relatively stable. Mean hospitalization rates decreased from 296.72 to 262.82 hospitalizations per 1000 diabetic adults (p < 0.001). In adjusted models, greater food swamp severity was associated with higher hospitalization rates in a curvilinear manner (severity: β = 2.181, p = 0.02; severity2: β = -0.017, p = 0.04), plateauing at approximately 64% unhealthy outlets, a saturation point observed in 17% of observations. Policies that limit saturation of the environment with unhealthy outlets may help in the prevention of diabetic complications, but more saturated counties will likely require more extensive intervention
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The Early Impact of the Centers for Medicare & Medicaid Services State Innovation Models Initiative on 30-Day Hospital Readmissions Among Adults With Diabetes.
BackgroundThe Centers for Medicare & Medicaid Services (CMS) State Innovation Models (SIM) Initiative funds states to accelerate delivery system and payment reforms. All SIM states focus on improving diabetes care, but SIM's effect on 30-day readmissions among adults with diabetes remains unclear.MethodsA quasi-experimental research design estimated the impact of SIM on 30-day hospital readmissions among adults with diabetes in 3 round 1 SIM states (N=671,996) and 3 comparison states (N=2,719,603) from 2010 to 2015. Difference-in-differences multivariable logistic regression models that incorporated 4-group propensity score weighting were estimated. Heterogeneity of SIM effects by grantee state and for CMS populations were assessed.ResultsIn adjusted difference-in-difference analyses, SIM was associated with an increase in odds of 30-day hospital readmission among patients in SIM states in the post-SIM versus pre-SIM period relative to the ratio in odds of readmission among patients in the comparison states post-SIM versus pre-SIM (ratio of adjusted odds ratio=1.057, P=0.01). Restricting the analyses to CMS populations (Medicare and Medicaid beneficiaries), resulted in consistent findings (ratio of adjusted odds ratio=1.057, P=0.034). SIM did not have different effects on 30-day readmissions by state.ConclusionsWe found no evidence that SIM reduced 30-day readmission rates among adults with diabetes during the first 2 years of round 1 implementation, even among CMS beneficiaries. It may be difficult to reduce readmissions statewide without greater investment in health information exchange and more intensive use of payment models that promote interorganizational coordination
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Implementation Variation in Natural Experiments of State Health Policy Initiatives.
ObjectivesAn increasing number of federal initiatives allow states flexibility in selecting the strategies used to achieve initiative-specific goals. Variation in the foci and intensity of implementation may explain why federal policy initiatives succeed in some states and fail in others. The CMS State Innovation Models (SIM) initiative is a complex policy intervention implemented with substantial variation across states and may have variable impacts. This paper presents a method to characterize and account for that variation in states' implementation foci and intensity in natural policy experiments.Study designA combination of quantitative and qualitative measures of SIM implementation was used to characterize the foci of payment and delivery system reforms across states.MethodsA modified Delphi expert panel process was used to prioritize the features of SIM implementation that would differentiate grantee states with respect to improved health outcomes. Three researchers then reviewed summaries of published evaluations and reports to characterize and score states on each implementation feature. Expert panelists guided the researchers on developing the criteria and weights applied to the focus areas when calculating SIM implementation intensity scores for states.ResultsOver 3 years of an expert panel process, 4 dimensions of SIM implementation that would most affect health outcomes were prioritized: 1) extent and breadth of stakeholder engagement, (2) extent that SIM implementation was focused on improving behavioral health, (3) amount of SIM funding per capita, and (4) breadth and depth of value-based payment reforms. Scoring states based on the prioritized factors resulted in composite scores that differentiated states into 3 categories: high, moderate, and low implementation intensity.ConclusionsWe developed a stakeholder-driven method to measure and account for variation in implementation foci and intensity in a federal policy initiative that was implemented heterogeneously across grantee states. Our method for characterizing state implementation variation may be useful for natural policy experiments examining the variable impact of policy initiatives
Cigarettes smoked among daily and non-daily smokers following CVS Health’s tobacco-free pharmacy policy
IntroductionIn September 2014, CVS Health ceased tobacco sales in all of its 7700 pharmacies nationwide. We investigate the impact of the CVS policy on the number of cigarettes smoked per day among metropolitan daily and non-daily smokers, who may respond to the availability of smoking cues in different manners.MethodsData are from the US Census Bureau Tobacco Use Supplement to the Current Population Survey 2014-2015 and the Blue Cross and Blue Shield Institute Community Health Management Hub. Adjusted difference-in-difference (DID) regressions assess changes in the number of cigarettes smoked per day among daily smokers (n=10 759) and non-daily smokers (n=3055), modelling core-based statistical area (CBSA) level CVS pharmacy market share continuously. To assess whether the policy had non-linear effects across the distribution of CVS market share, we also examine market share using tertiles.ResultsCVS's tobacco-free pharmacy policy was associated with a significant reduction in the number of cigarettes smoked by non-daily smokers in the continuous DID (rate ratio=0.985, p=0.022), with a larger reduction observed among non-daily smokers in CBSAs in the highest third of CVS market share compared with those living in CBSAs with no CVS presence (rate ratio=0.706, p=0.027). The policy, however, was not significantly associated with differential changes in the number of cigarettes by daily smokers.ConclusionThe removal of tobacco products from CVS pharmacies was associated with a reduction in the number of cigarettes smoked per day among non-daily smokers in metropolitan CBSAs, particularly those in which CVS had a large pharmacy market share