Active Primary Care Physicians in Nebraska: Data Comparison, Supply, and Characteristics

https://digitalcommons.unmc.edu/coph_policy_reports/1020/thumbnail.jp

Primary Care Physician Assistants in Nebraska

https://digitalcommons.unmc.edu/coph_policy_reports/1022/thumbnail.jp

Primary Care Nurse Practitioners in Nebraska

https://digitalcommons.unmc.edu/coph_policy_reports/1021/thumbnail.jp

The burden of antimicrobial resistance in the Americas in 2019: a cross-country systematic analysis

Background Antimicrobial resistance (AMR) is an urgent global health challenge and a critical threat to modern health care. Quantifying its burden in the WHO Region of the Americas has been elusive—despite the region’s long history of resistance surveillance. This study provides comprehensive estimates of AMR burden in the Americas to assess this growing health threat. Methods We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with AMR for 23 bacterial pathogens and 88 pathogen–drug combinations for countries in the WHO Region of the Americas in 2019. We obtained data from mortality registries, surveillance systems, hospital systems, systematic literature reviews, and other sources, and applied predictive statistical modelling to produce estimates of AMR burden for all countries in the Americas. Five broad components were the backbone of our approach: the number of deaths where infection had a role, the proportion of infectious deaths attributable to a given infectious syndrome, the proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of pathogens resistant to an antibiotic class, and the excess risk of mortality (or duration of an infection) associated with this resistance. We then used these components to estimate the disease burden by applying two counterfactual scenarios: deaths attributable to AMR (compared to an alternative scenario where resistant infections are replaced with susceptible ones), and deaths associated with AMR (compared to an alternative scenario where resistant infections would not occur at all). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. Findings We estimated 569,000 deaths (95% UI 406,000–771,000) associated with bacterial AMR and 141,000 deaths (99,900–196,000) attributable to bacterial AMR among the 35 countries in the WHO Region of the Americas in 2019. Lower respiratory and thorax infections, as a syndrome, were responsible for the largest fatal burden of AMR in the region, with 189,000 deaths (149,000–241,000) associated with resistance, followed by bloodstream infections (169,000 deaths [94,200–278,000]) and peritoneal/intra-abdominal infections (118,000 deaths [78,600–168,000]). The six leading pathogens (by order of number of deaths associated with resistance) were Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. Together, these pathogens were responsible for 452,000 deaths (326,000–608,000) associated with AMR. Methicillin-resistant S. aureus predominated as the leading pathogen–drug combination in 34 countries for deaths attributable to AMR, while aminopenicillin-resistant E. coli was the leading pathogen–drug combination in 15 countries for deaths associated with AMR. Interpretation Given the burden across different countries, infectious syndromes, and pathogen–drug combinations, AMR represents a substantial health threat in the Americas. Countries with low access to antibiotics and basic health-care services often face the largest age-standardised mortality rates associated with and attributable to AMR in the region, implicating specific policy interventions. Evidence from this study can guide mitigation efforts that are tailored to the needs of each country in the region while informing decisions regarding funding and resource allocation. Multisectoral and joint cooperative efforts among countries will be a key to success in tackling AMR in the Americas.publishedVersio

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Assessing Interstate Migration Among International Medical Graduates in the United States

This presentation was given during the Association of American Medical Colleges Physician Workforce Research Conference

Use of mobile health applications for health-promoting behavior among individuals with chronic medical conditions

Background: Chronic medical conditions (CCs) are leading causes of morbidity and mortality in the United States. Strategies to control CCs include targeting unhealthy behaviors, often through the use of patient empowerment tools, such as mobile health (mHealth) technology. However, no conclusive evidence exists that mHealth applications (apps) are effective among individuals with CCs for chronic disease self-management. Methods: We used data from the Health Information National Trends Survey (HINTS 5, Cycle 1, 2017). A sample of 1864 non-institutionalized US adults (≥18 years) who had a smartphone and/or a tablet computer and at least one CC was analyzed. Using multivariable logistic regressions, we assessed predisposing, enabling, and need predictors of three health-promoting behaviors (HPBs): tracking progress on a health-related goal, making a health-related decision, and health-related discussions with a care provider among smart device and mHealth apps owners. Results: Compared to those without mHealth apps, individuals with mHealth apps had significantly higher odds of using their smart devices to track progress on a health-related goal (adjusted odds ratio (aOR) 8.74, 95% confidence interval (CI): 5.66–13.50, P \u3c.001), to make a health-related decision (aOR 1.77, 95% CI: 1.16–2.71, P \u3c.01) and in health-related discussions with care providers (aOR 2.0, 95% CI: 1.26–3.19, P \u3c.01). Other significant factors of at least one type of HPB among smart device and mHealth apps users were age, gender, education, occupational status, having a regular provider, and self-rated general health. Conclusion: mHealth apps are associated with increased rates of HPB among individuals with CCs. However, certain groups, like older adults, are most affected by a digital divide where they have lower access to mHealth apps and thus are not able to take advantage of these tools. Rigorous randomized clinical trials among various segments of the population and different health conditions are needed to establish the effectiveness of these mHealth apps. Healthcare providers should encourage validated mHealth apps for patients with CCs

Privacy and security issues in mobile health: Current research and future directions

Mobile health (mHealth) is being recognized as an innovative approach to deliver health care in an accessible, portable and cost effective manner. Despite the numerous benefits associated with the use of mobile devices, there are major concerns with mhealth in the area of privacy and security. These aspects need to be considered at every stage of design and development of mHealth devices and applications which need to be developed by security-trained, trusted manufacturers who should be accountable to minimize damages in the healthcare industry. It is also crucial for users and/or organizations to be more cautious and responsible to use mobile devices. Major stakeholders, including those in the user׳s community (patients and providers), vendors and developers, and policy makers need to come together to survey the landscape, identify the issues, and develop policies, regulations, safeguards and industry standards