This cross-sectional study uses data from the American Medical Association Physician Masterfile to examine physician density by specialty type across metropolitan and rural US counties from 2010 to 2017.
To the Editor: The drug-overdose epidemic has led to an increase in the number of organ donors dying from drug intoxication 1 ; this pattern is confined to the United States and has not been observed in Europe. 2 Geographic disparity in the rates of death from drug intoxication in the United States 3 led us to explore trends and statewide variation in the number of donor organs recovered from persons who died from drug intoxication.We used data from the Organ Procurement and Transplantation Network (1999Network ( -2017) ) to examine state-specific patterns in the use of donor organs for adult heart transplantation that were recovered from persons who died from drug intoxication.Net annual changes in the size of the heart transplant waiting list (number of new registrations minus the total number of removals) were also determined.Age-adjusted annual rates of drug intoxication-related deaths from 1999 through 2016 were obtained from the Centers for Disease Control and Prevention WONDER online database. 4We calculated the percentage of heart donors among the total number of persons who died from drug intoxication during this period.The age-standardized rate of death from drug intoxication rose from 6.8 per 100,000 persons in 1999 to 20.8 per 100,000 persons in 2016.Among 37,232 U.S. adult donors from whom hearts were recovered for transplantation from 1999 through 2017, the percentage of those who died from drug intoxication increased from 1.5% to 17.6%.Most states had increases in the rates of drug intoxication-related deaths and organ recovery, with major increases in the Northeast, Midwest, and Southwest regions of the United States (Fig. 1A and1B).
Donations to charity-based crowdfunding environments have been on the rise in the last few years. Unsurprisingly, deception and fraud in such platforms have also increased, but have not been thoroughly studied to understand what characteristics can expose such behavior and allow its automatic detection and blocking. Indeed, crowdfunding platforms are the only ones typically performing oversight for the campaigns launched in each service. However, they are not properly incentivized to combat fraud among users and the campaigns they launch: on the one hand, a platform's revenue is directly proportional to the number of transactions (since the platform charges a fixed amount per donation); on the other hand, if a platform is transparent with respect to how much fraud it has, it may discourage potential donors from participating.
Background: Certain antihyperglycemic therapies modify CV disease courses in DM, but their uptake in practice appears limited among low-income adults. Methods: We employed a difference-in-difference (DiD) design to study the association between Medicaid Expansion and non-insulin antihyperglycemic prescriptions. We used 2012-2017 National and State Medicaid data to compare prescription claims between states that did (n=25) and did not expand (n=26) Medicaid by Jan 2014. Results: Following Medicaid Expansion, average quarterly non-insulin antihyperglycemic therapies/1000 enrollees increased by 4% in expansion and 2% in non-expansion states (left panel) with modest variation (right panel). Use of SGLT2i and GLP-1RA grew faster in early expansion than non-expansion states. DiD estimates for prescription change after Medicaid Expansion between expansion vs. non-expansion states was 1.6 (1.00 to 2.20; P<0.001) for all non-insulin therapies, 0.11 (-0.02 to 0.25; P=0.10) for SGLT2i, and 0.11 (0.04 to 0.18; P=0.002) for GLP-1RA. Excluding 7 states that expanded Medicaid after Jan 2014 yielded similar results. Conclusion: Medicaid Expansion was associated with greater access to non-insulin antihyperglycemic therapies, including GLP-1RA, among newly insured low-income adults, even after accounting for more DM detection. Future studies are needed to understand if policies facilitating these therapeutic changes impact CV health. Disclosure A. Sumarsono: None. L. Buckley: None. S.R. Machado: None. R.K. Wadhera: None. H. Warraich: None. R.J. Desai: Research Support; Self; Bayer AG, Novartis AG. B.M. Everett: Consultant; Self; Amarin Corporation, Amgen, Merck & Co., Inc., National Institute of Diabetes and Digestive and Kidney Diseases, Roche Diagnostic USA. Consultant; Spouse/Partner; Sequana. Consultant; Self; U.S. Food and Drug Administration. Research Support; Self; National Heart, Lung, and Blood Institute. D.K. McGuire: Consultant; Self; Afimmune, Applied Therapeutics, Merck Sharp & Dohme Corp., Metavant. Other Relationship; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eisai Co., Ltd., Eli Lilly and Company, Esperion Therapeutics, Inc., GlaxoSmithKline plc., Janssen Pharmaceuticals, Inc., Lexicon Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis. G.C. Fonarow: Consultant; Self; Abbott, AstraZeneca, Janssen Pharmaceuticals, Inc., Medtronic, Novartis Pharmaceuticals Corporation. J. Butler: Consultant; Self; Amgen, Array BioPharma, AstraZeneca, Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc., Bristol-Myers Squibb, CVRx, G3 Pharmaceuticals, Innolife Co., Ltd., Janssen Pharmaceuticals, Inc., Luitpold Pharmaceuticals, Inc., Medtronic, Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Relypsa, Inc., VIfor. A. Pandey: None. M. Vaduganathan: Advisory Panel; Self; Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc., Relypsa, Inc. Consultant; Self; Amgen, AstraZeneca, Baxter.
Driving a car is a complex skill that includes interacting with multiple systems inside the vehicle. Today's challenge in the automotive industry is to produce innovative In-Vehicle Information Systems (IVIS) that are pleasant to use and satisfy the costumers' needs while, simultaneously, maintaining the delicate balance of primary task vs. secondary tasks while driving. The authors report a MCDM approach for rank ordering a large heterogeneous set of human-machine interaction technologies; the final set consisted of hundred and one candidates. They measured candidate technologies on eight qualitative criteria that were defined by domain experts, using a group decision-making approach. The main objective was ordering alternatives by their decision score, not the selection of one or a small set of them. The authors' approach assisted decision makers in exploring the characteristics of the most promising technologies and they focused on analyzing the technologies in the top quartile, as measured by their MCDM model. Further, a clustering analysis of the top quartile revealed the presence of important criteria trade-offs.
Comparing health policy measures before elections and identifying potential gaps in the health policy debate can be challenging. We explored the use of the Health System Performance Assessment for Universal Health Coverage framework to analyse health policy proposals by classifying health policy measures outlined in political manifestos into four health system functions: governance, financing, resource generation and service delivery. As a case study, we analysed the political manifestos of all Portuguese parties with parliamentary representation ahead of the election in March 2024. We calculated the share of measures per health system function for individual political manifestos and identified potential gaps in the health policy debate. When required, we used additional classification criteria and local expertise on political and institutional knowledge. A snap general election was announced in Portugal in November 2023, following an alleged corruption scandal, and political parties began publishing their manifestos on their websites in January 2024. We identified and classified 350 health-related measures across the four functions: governance, 29.7% (104 measures); financing, 16.9% (59 measures); resource generation, 33.4% (117 measures); and service delivery, 20.0% (70 measures). These findings enabled characterization of the priorities of parties, facilitated cross-party comparisons and identified missing topics in the political debate. We show that the framework can be adapted to analyse political manifestos, providing a systematic method for comparing and synthesizing health policy proposals. We further demonstrate the potential for extending the framework's applicability beyond health system performance assessment, opening new avenues for policy analysis.
<b>Objective:</b> Certain antihyperglycemic therapies modify cardiovascular and kidney outcomes among persons with type 2 diabetes mellitus (T2DM), but uptake in practice appears restricted to certain demographics. We examine the association of Medicaid expansion with use of and expenditures related to antihyperglycemic therapies among Medicaid beneficiaries. <p><b> </b></p> <p><b>Methods:</b> We employed a difference-in-difference design to analyze the association of Medicaid expansion on prescription of non-insulin antihyperglycemic therapies. We used 2012-2017 National & State Medicaid data to compare prescription claims and costs between states that did (n=25) and did not expand (n=26) Medicaid by January 2014. </p> <p><b> </b></p> <p><b>Results:</b> Following Medicaid expansion in 2014, average non-insulin antihyperglycemic therapies per state/1,000 enrollees increased by 4.2%/quarter in expansion states and 1.6%/quarter in non-expansion states. For SGLT2i and GLP-1RA, quarterly growth rates per-1,000 enrollees were 125.3% and 20.7% for expansion states and 87.6% and 16.0% for non-expansion states, respectively. Expansion states had faster utilization and total spending growth in SGLT2i and GLP-1RA than non-expansion states. Difference-in-difference estimates for change in volume of prescriptions after Medicaid expansion between expansion vs. non-expansion states was 1.68 (1.09 to 2.26;P<0.001) for all non-insulin therapies, 0.125 (-0.003 to 0.25;P=0.056) for SGLT2i, and 0.12 (0.055 to 0.18;P<0.001) for GLP-1RA.</p> <p><b> </b></p> <p><b>Conclusion:</b> Use of non-insulin antihyperglycemic therapies, including SGLT2i and GLP-1RA, increased among low-income adults in both Medicaid expansion and non-expansion states, with a significantly greater increase in overall use and in GLP-1RA use in expansion states. Future evaluation of the population-level health impact of expanded access to these therapies is needed. </p>
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