Browsing by Subject "health care"
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Item Beyond Health Care: Why We Get Sick and What To Do About It(2017-10-06) Williams, David; Malcolm, Jan; Noor, Sahra; Jacobs, Lawrence RItem Economic Contribution of American Indian Health Care Spending in Northwest Minnesota(2020) Tuck, Brigid; Bhattacharyya, RaniItem The Economic Impact of Minnesota Hospitals and Health Systems(University of Minnesota Duluth, 2022) Haynes, Monica; Chiodi Grensing, Gina; Austin, Nana Kofi; Jones, JacqueHospitals and health systems play an important role in the community, not only as life saving health organizations but also as major employers and purchasers of goods that provide considerable economic impact. The Minnesota Hospital Association (MHA) contacted the Bureau of Business and Economic Research at the University of Minnesota Duluth’s Labovitz School of Business and Economics to study the economic impact of hospitals and health systems regionally and statewide. Inputs used in calculating the economic impacts of hospitals and health systems included total revenue, employment, salaries, and benefits for the 128 hospitals and health systems as well as revenue for supporting health care services, such as offices of physicians and nursing and community care facilities. In 2020, Minnesota hospitals and health systems reported total revenues of more than $21.4 billion, employment levels of 122,758 and employee compensation of $10.2 billion. The MHA regions with the highest revenues included the Twin Cities Metro Region ($10.3 billion), which includes the seven counties in the Twin Cities metro area; the Southeast Region 6 ($4.5 billion), which includes the Rochester metro area; and the Central Region 3 ($2.7 billion), which is the largest region by geography and includes 22 counties that span the entire central part of the state, including St. Cloud. In all six regions, hospitals and health systems ranked among the top ten largest industries by employment. MHA estimates that 66% of the state’s primary care clinic providers are associated with a hospital or health system, based on information obtained from the Minnesota Department of Employment and Economic Development (DEED). MHA also used DEED data to estimate the number of primary care clinic providers associated with hospitals and health systems at the regional level with the following results: Region 1 is 71%, Region 2 is 55%, Region 3 is 58%, Region 4 is 46%, Region 5 is 91%, and Region 6 is 87%. An estimated 13% of the state’s nursing home revenues could be attributed to nursing homes associated with hospital and health systems, based on data obtained from the Minnesota Department of Health’s Health Care Cost Information System. In total, $32.3 billion in direct revenue was generated by health systems, including hospitals, clinics, nursing homes, home health, ambulance, and other associated health care entities. Economic impact analysis tracks an initial economic shock or activity (like the direct spending of hospitals and health systems and their employees) through multiple rounds of industry and consumer spending to show the multiplier or ripple effects through a local economy. The initial shock or activity is considered the direct effect, the resulting increase in industry spending is the indirect effect, and the resulting increase in consumer spending is the induced effect. The research team used the IMPLAN Group’s input-output modeling data and software (IMPLAN version 3.1) for modeling economic impacts. The data used was the most recent IMPLAN data available, which is for the year 2020. Results reflect 2022 dollars. According to the results of economic impact modeling, Minnesota hospitals and health systems—along with their affiliated clinics, nursing homes, and other associated entities—supported almost 389,000 jobs in 2020, added almost $31 billion in labor income (wages and benefits), contributed $39.3 billion in additional value added to the state’s economy, and added $67.6 billion in new spending. In total, for every one job created by hospitals and health systems in the state, another 1.09 jobs were created in related industries.Item The Fragile Individual Health Insurance Market(2017-07-26) Corlette, Sabrina; Benson, Michelle; Piper, Emily; Schowalter, Jim; Jacobs, LawrenceItem Health Reform: Preserving a Strong Role for the States(2012-02-16) Leavitt, Michael O.; Jacobs, Lawrence; Hage, DaveItem Is Obamacare Taking America in the Right Direction?(2014-11-07) Daschle, TomItem Local Government Employee Health Care Finance in Minnesota: An Analysis of Large City Employee Health Benefit Spending(Hubert H. Humphrey Institute of Public Affairs, 2009-05-20) Milanowski, LoriEmployee health care finance is a complex and often misunderstood area of local budgets. Due to a lack of regulation around city budgets in Minnesota, a significant amount of transparency and accountability is lost to taxpayers and legislators when the compensation of city employees is reported as part of overall compensation or human services. This study set out to determine what city employee benefit spending looked like in 2008, and in identifying trends, resulted in an analysis of revenue sources related to employee health care benefit spending. Therefore, this study focuses on the main task of quantifying city health benefit spending and ways to increase efficiency in spending, and in addition, approaches the issue of tax payer burden and equity in relation to various city revenue sources. What this study found is that while voters are expected to “vote with their feet” and thus choose the appropriate mix and tax price of their local government services, the introduction of state aids (Local Government Aid) has further complicated the assessment in the generosity and tax burden related to local government employee health benefits. This study attempts not only to quantify, through multiple lenses and modes of analysis, average city spending on employee health care benefits in large Minnesota cities, but also provides a means of improving efficiency in spending in large cities in Minnesota. In addition, this study identifies the role and effect of the introduction of unrestricted LGA into local budgets, and state aid’s relation to medical benefit spending in cities.Item Mapping the Beneficial and Adverse Consequences of Receiving Weight-Related Advice from a Healthcare Provider: Identifying Strategies to Optimize Well-Being(2023-05) Standen, ErinIt is standard practice for healthcare providers to recommend weight loss to patients with obesity (U.S. Preventive Services Task Force). However, it is possible that people with higher weight perceive these interactions as stigmatizing even if providers are well-intentioned when delivering weight-related advice. To the extent that weight-related advice is perceived as stigmatizing, the advice itself may undermine patients' health via stress, reduced engagement in health behaviors, and healthcare avoidance. In a series of three studies, I examined the immediate consequences of receiving weight-related advice from a healthcare provider on weight-based identity threat and behavioral motivation. In Study 1, I used a doctor-patient interaction scenario study to document people's responses to weight-related advice (versus control advice) from a healthcare provider. Participants who received weight-related advice reported greater weight-based identity threat (ps < 0.001 across three measures) and greater motivation to change their eating behavior (p < 0.001). In Study 2, participants were randomly assigned to read scenarios in which the provider: (a) requested consent to discuss weight (or did not); (b) framed behavioral recommendations around overall health (or around weight loss). These strategies were designed to maximize the motivational benefit and minimize the weight-based identity threat caused by weight-related advice. However, there were no significant differences in these outcomes based on study condition (ps > 0.48). In Study 3, undergraduates with higher weight (BMI > 25 kg/m2) attended a “student wellness check-in,” during which a trained research assistant gave them “standard” weight-related advice, “optimized” weight-related advice (i.e., in which the research assistant requested consent and used a health frame), or no weight-related advice. Receiving weight-related advice led to significantly greater weight-based identity threat and behavioral motivation (ps < 0.02), but there were no differences in threat or motivation between the standard and optimized weight-related advice groups (ps > 0.17). Taken together, these studies indicate that well-intentioned weight-related advice from healthcare providers can be perceived as stigmatizing, even when motivating. Further investigation is needed to identify strategies that reduce patients' experience of weight-based identity threat, especially because weight stigma may undermine the motivational benefits of weight-related advice and harm people's health.Item MNsure v. Auditor Event(2015-04-24) Beutner, Brian; Forsythe, Tom; Leitz, Scott; Nobles, JimItem Out-Of-Pocket Health Care Spending: Effects Of Partner Spending On Own Spending(2018-05) Adeniyi, TitilopeBackground. Delayed or foregone medical care because of cost is an ever-present possibility for most households and a current concern for many households in the United States. A small body of literature exists concerning the relationship between household out-of-pocket spending and household-member delayed or foregone health care and none of this literature focuses primarily on older adults. This research seeks to answer the following question: Among older adults, how does the existence of a pre-existing medical condition(s) in one’s partner effect one’s own out-of-pocket health care spending in the period following a recent medical condition diagnosis? Methods. This research used data from the Health and Retirement Study (HRS). The HRS surveys United States non-institutionalized residents at least 50 years of age and their partners every two years. The analytic sample was comprised of 2,325 observations for 524 households from the 2002 to 2012 survey waves. This research utilized a 2-part fixed-effects difference-in-differences model. The outcomes of interest were individual total and prescription out-of-pocket health care spending. Results. In contrast to unadjusted models, after adjusting for a number of individual and household characteristics, there was no significant difference in the change in total and prescription out-of-pocket spending behavior after a medical condition diagnosis when comparing individuals with and without a partner with a pre-existing medical condition. Conclusion. While most of the difference-in-differences results were not significant in the unadjusted, adjusted, and sensitivity analyses for both total and prescription out-of-pocket spending, all but a handful of these results were positive. Positive effect values are counter to the result that was expected. The positive sign indicates a tendency for individuals who have partners with a pre-existing condition to have a greater change in out-of-pocket spending than individuals without a partner with a pre-existing condition. A possible explanation for this finding could relate to increased health care literacy in households that have a partner with a pre-existing condition.Item Why and When Does a Mindfulness Intervention Promote Job Performance? The Interpersonal Mechanisms and Individual, Job, and Social Contingencies(2015-07) Yang, TaoThis dissertation develops and tests a theoretical model of the role of a mindfulness intervention in promoting job performance in service settings. I examine the client-focused mechanisms—attentiveness, perspective taking, and response flexibility—and individual (i.e., employee agreeableness), social (i.e., perception of workgroup service climate), and job (i.e., work overload) contingencies of the relationship between a mindfulness intervention and job performance. I conducted a pretest-posttest field experiment of 72 health care professionals in a health care organization with intervention (i.e., mindfulness meditation) and active control (i.e., wellness education) conditions and repeated measures from health care professionals and their patients over 15 days. Confirmatory factor analyses suggest that the three client-focused mechanisms were represented by a higher-order construct of patient centered behavior. Multilevel modeling and latent growth modeling suggest that the two conditions are distinct; compared with active control, the intervention yields pre-to-post increases in daily mindfulness and work behaviors including self-ratings of job performance and proactive patient care and patient ratings of patient centered behavior. Multilevel mediation analysis suggests that patient ratings of patient centered behavior fail to mediate the effect of a mindfulness intervention on patient satisfaction with job performance. Multilevel moderated mediation analyses suggest that agreeableness, perceived workgroup service climate, and work overload do not moderate the effect of a mindfulness intervention (via patient ratings of patient centered behavior) on patient satisfaction. Nonetheless, compared with active control, the mindfulness intervention yields higher patient rated patient centered behavior for health care professionals who have a higher level of agreeableness.