9 resultados para U.S. Customs Service.
em DigitalCommons@The Texas Medical Center
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List of Physicians and Surgeons arranged by location, giving post office address with population and location, the School practiced, date and college of graduation, all the existing and extinct medical colleges in North America, with locations, officers, number of professors, lecturers, demonstrators, etc., the various medical societies, penal, reformatory and charitable state institutions, hospitals, sanitariums, dispensaries, asylums and other medical institutions, boards of health, boards of medical examiners, health officers at principal points, the laws of registration and other laws relating to the profession, medical journals with names of editors, frequency of publication and subscription rates, medical libraries, a therapeutic classification of American health resorts, mineral springs, official list of officers of the medical departments of the U.S. Army, Navy and Marine Hospital Service, the U.S. Indian Service, roster of examining surgeons of the U.S. Pension Department, a descriptive sketch of each state, territory and province, embodying such matters as location, boundary, extent in miles and acres, latitude and longitude, statistics relating to climate, temperature, rate of mortality, etc. Full particulars of all national and inter-state associations and societies relating to medicine and surgery, and an INDEX TO THE PHYSICIANS OF THE UNITED STATES. Arranged alphabetically, with the number of the page and column in which the name appears.
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This study was conducted under the auspices of the Subcommittee on Risk Communication and Education of the Committee to Coordinate Environmental Health and Related Programs (CCEHRP) to determine how Public Health Service (PHS) agencies are communicating information about health risk, what factors contributed to effective communication efforts, and what specific principles, strategies, and practices best promote more effective health risk communication outcomes.^ Member agencies of the Subcommittee submitted examples of health risk communication activities or decisions they perceived to be effective and some examples of cases they thought had not been as effective as desired. Of the 10 case studies received, 7 were submitted as examples of effective health risk communication, and 3, as examples of less effective communication.^ Information contained in the 10 case studies describing the respective agencies' health risk communication strategies and practices was compared with EPA's Seven Cardinal Rules of Risk Communication, since similar rules were not found in any PHS agency. EPA's rules are: (1) Accept and involve the public as a legitimate partner. (2) Plan carefully and evaluate your efforts. (3) Listen to the public's specific concerns. (4) Be honest, frank, and open. (5) Coordinate and collaborate with other credible sources. (6) Meet the needs of the media. (7) Speak clearly and with compassion.^ On the basis of case studies analysis, the Subcommittee, in their attempts to design and implement effective health risk communication campaigns, identified a number of areas for improvement among the agencies. First, PHS agencies should consider developing a focus specific to health risk communication (i.e., office or specialty resource). Second, create a set of generally accepted practices and guidelines for effective implementation and evaluation of PHS health risk communication activities and products. Third, organize interagency initiatives aimed at increasing awareness and visibility of health risk communication issues and trends within and between PHS agencies.^ PHS agencies identified some specific implementation strategies the CCEHRP might consider pursuing to address the major recommendations. Implementation strategies common to PHS agencies emerged in the following five areas: (1) program development, (2) building partnerships, (3) developing training, (4) expanding information technologies, and (5) conducting research and evaluation. ^
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Objective. The purpose of this study was to identify the medical issues experienced by Military Working Dogs during their period of deployment in Iraq.^ Design. This study was a retrospective cross-sectional survey based on database and medical record abstraction.^ Population. Military Working Dogs (MWDs) that were deployed to Iraq at any time between 20 March 2003 and 31 December 2007 were the inclusive population of interest. Seven hundred ninety-five (795) MWDs were identified as having been deployed to Iraq during the inclusive dates. Four hundred ninety-six (496) MWDs were identified that had medical events during the deployment period. ^ Procedures. Eligible MWDs were identified through several sources, to include database query, medical record abstraction questionnaire, and medical record abstraction. Demographic information collected for each MWD included tattoo, name, age, gender, breed, Branch of Service, and duty certification. Information on each veterinary/medical clinical event (VCE) was collected. This information was coded, and data entered into a database for organization. Frequency and prevalence information were determined for each category of VCE.^ Results. The top four VCEs experienced by MWDs while deployed in Iraq were gastrohepatic, dermatologic, traumatic injury, and appendicular musculoskeletal issues.^ Conclusions. Training, equipment, and supplies for veterinary personnel who care for the deployed MWDs should be tailored accordingly to suit the identified medical needs of the MWDs. ^
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A case-control study has been conducted examining the relationship between preterm birth and occupational physical activity among U.S. Army enlisted gravidas from 1981 to 1984. The study includes 604 cases (37 or less weeks gestation) and 6,070 controls (greater than 37 weeks gestation) treated at U.S. Army medical treatment facilities worldwide. Occupational physical activity was measured using existing physical demand ratings of military occupational specialties.^ A statistically significant trend of preterm birth with increasing physical demand level was found (p = 0.0056). The relative risk point estimates for the two highest physical demand categories were statistically significant, RR's = 1.69 (p = 0.02) and 1.75 (p = 0.01), respectively. Six of eleven additional variables were also statistically significant predictors of preterm birth: age (less than 20), race (non-white), marital status (single, never married), paygrade (E1 - E3), length of military service (less than 2 years), and aptitude score (less than 100).^ Multivariate analyses using the logistic model resulted in three statistically significant risk factors for preterm birth: occupational physical demand; lower paygrade; and non-white race. Controlling for race and paygrade, the two highest physical demand categories were again statistically significant with relative risk point estimates of 1.56 and 1.70, respectively. The population attributable risk for military occupational physical demand was 26%, adjusted for paygrade and race; 17.5% of the preterm births were attributable to the two highest physical demand categories. ^
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A life table methodology was developed which estimates the expected remaining Army service time and the expected remaining Army sick time by years of service for the United States Army population. A measure of illness impact was defined as the ratio of expected remaining Army sick time to the expected remaining Army service time. The variances of the resulting estimators were developed on the basis of current data. The theory of partial and complete competing risks was considered for each type of decrement (death, administrative separation, and medical separation) and for the causes of sick time.^ The methodology was applied to world-wide U.S. Army data for calendar year 1978. A total of 669,493 enlisted personnel and 97,704 officers were reported on active duty as of 30 September 1978. During calendar year 1978, the Army Medical Department reported 114,647 inpatient discharges and 1,767,146 sick days. Although the methodology is completely general with respect to the definition of sick time, only sick time associated with an inpatient episode was considered in this study.^ Since the temporal measure was years of Army service, an age-adjusting process was applied to the life tables for comparative purposes. Analyses were conducted by rank (enlisted and officer), race and sex, and were based on the ratio of expected remaining Army sick time to expected remaining Army service time. Seventeen major diagnostic groups, classified by the Eighth Revision, International Classification of Diseases, Adapted for Use In The United States, were ranked according to their cumulative (across years of service) contribution to expected remaining sick time.^ The study results indicated that enlisted personnel tend to have more expected hospital-associated sick time relative to their expected Army service time than officers. Non-white officers generally have more expected sick time relative to their expected Army service time than white officers. This racial differential was not supported within the enlisted population. Females tend to have more expected sick time relative to their expected Army service time than males. This tendency remained after diagnostic groups 580-629 (Genitourinary System) and 630-678 (Pregnancy and Childbirth) were removed. Problems associated with the circulatory system, digestive system and musculoskeletal system were among the three leading causes of cumulative sick time across years of service. ^
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Volunteering is intricately woven into the fabric of our society. In 2009 alone, approximately 63.4 million Americans participated in volunteer activities, collectively donating over 8.1 billion service-hours (Corporation for National and Community Service [CNCS], 2010). Each service-hour is determined by the U.S. Bureau of Labor Statistics (2010) to be valued at $20.85/hr which translates to a national savings of $169 billion. Thus, we can clearly observe the significance of volunteer contribution to the overall benefit of society. In addition, there is now evidence that voluntary service may also benefit the actual volunteer, especially individuals who are 65+ years. As we reach 2020 this elderly class, composed of nearly 13 million (CNCS, 2010) Americans, will be of much consequence. Their potential to contribute in community-related efforts may save the U.S. billions in labor costs, and may also help reduce healthcare-related expenditures if volunteering proves to be a protective factor. In this literature review, we set out to explore the potential relationship between volunteer participation and increased mental and physical wellness. We also examined volunteer demographic characteristics and common motives for engaging in service-related activities. Analysis showed that volunteer work often combined low-impact physical activity and mental satisfaction from serving others, resulting in overall health benefit. Demographic characteristics displayed were consistent with previous studies and found that a majority of volunteers were female, White, married status, having received college degree or higher, employed, middle-high SES. In addition, age was seen to be a key characteristic in forecasting volunteer motivation and self-reported perceived health benefits.^
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Background. Kidney disease is a growing public health phenomenon in the U.S. and in the world. Downstream interventions, dialysis and renal transplants covered by Medicare's renal disease entitlement policy in those who are 65 years and over have been expensive treatments that have been not foolproof. The shortage of kidney donors in the U.S. has grown in the last two decades. Therefore study of upstream events in kidney disease development and progression is justified to prevent the rising prevalence of kidney disease. Previous studies have documented the biological route by which obesity can progress and accelerate kidney disease, but health services literature on quantifying the effects of overweight and obesity on economic outcomes in the context of renal disease were lacking. Objectives . The specific aims of this study were (1) to determine the likelihood of overweight and obesity in renal disease and in three specific adult renal disease sub-populations, hypertensive, diabetic and both hypertensive and diabetic (2) to determine the incremental health service use and spending in overweight and obese renal disease populations and (3) to determine who financed the cost of healthcare for renal disease in overweight and obese adult populations less than 65 years of age. Methods. This study was a retrospective cross-sectional study of renal disease cases pooled for years 2002 to 2009 from the Medical Expenditure Panel Survey. The likelihood of overweight and obesity was estimated using chi-square test. Negative binomial regression and generalized gamma model with log link were used to estimate healthcare utilization and healthcare expenditures for six health event categories. Payments by self/family, public and private insurance were described for overweight and obese kidney disease sub-populations. Results. The likelihood of overweight and obesity was 0.29 and 0.46 among renal disease and obesity was common in hypertensive and diabetic renal disease population. Among obese renal disease population, negative binomial regression estimates of healthcare utilization per person per year as compared to normal weight renal disease persons were significant for office-based provider visits and agency home health visits respectively (p=0.001; p=0.005). Among overweight kidney disease population health service use was significant for inpatient hospital discharges (p=0.027). Over years 2002 to 2009, overweight and obese renal disease sub-populations had 53% and 63% higher inpatient facility and doctor expenditures as compared to normal weight renal disease population and these result were statistically significant (p=0.007; p=0.026). Overweigh renal disease population had significant total expenses per person per year for office-based and outpatient associated care. Overweight and obese renal disease persons paid less from out-of-pocket overall compared to normal weight renal disease population. Medicare and Medicaid had the highest mean annual payments for obese renal disease persons, while mean annual payments per year were highest for private insurance among normal weight renal disease population. Conclusion. Overweight and obesity were common in those with acute and chronic kidney disease and resulted in higher healthcare spending and increased utilization of office-based providers, hospital inpatient department and agency home healthcare. Healthcare for overweight and obese renal disease persons younger than 65 years of age was financed more by private and public insurance and less by out of pocket payments. With the increasing epidemic of obesity in the U.S. and the aging of the baby boomer population, the findings of the present study have implications for public health and for greater dissemination of healthcare resources to prevent, manage and delay the onset of overweight and obesity that can progress and accelerate the course of the kidney disease.^
Resumo:
Objectives: This study included two overarching objectives. Through a systematic review of the literature published between 1990 and 2012, the first objective aimed to assess whether insuring the uninsured would result in higher costs compared to insuring the currently insured. Studies that quantified the actual costs associated with insuring the uninsured in the U.S. were included. Based upon 2009 data from the Medical Expenditure Panel Survey (MEPS), the second objective aimed to assess and compare the self-reported health of populations with four different insurance statuses. The second part of this study involved a secondary data analysis of both currently insured and currently uninsured individuals who participated in the MEPS in 2009. The null hypothesis was that there were no differences across the four categories of health insurance status for self-reported health status and healthcare service use. The alternative hypothesis was that were differences across the four categories of health insurance status for self-reported health status and healthcare service use. Methods: For the systematic review, three databases were searched using search terms to identify studies that actually quantified the cost of insuring the uninsured. Thirteen studies were selected, discussed, and summarized in tables. For the secondary data analysis of MEPS data, this study compared four categories of health insurance status: (1) currently uninsured persons who will become eligible for Medicaid under the Patient Protection and Affordable Care Act (PPACA) healthcare reforms in 2014; (2) currently uninsured persons who will be required to buy private insurance through the PPACA health insurance exchanges in 2014; (3) persons currently insured under Medicaid or SCHIP; and (4) persons currently insured with private insurance. The four categories were compared on the basis of demographic information, health status information, and health conditions with relatively high prevalence. Chi-square tests were run to determine if there were differences between the four groups in regard to health insurance status and health status. With some exceptions, the two currently insured groups had worse self-reported health status compared to the two currently uninsured groups. Results: The thirteen studies that met the inclusion criteria for the systematic review included: (1) three cost studies from 1993, 1995, and 1997; (2) four cost studies from 2001, 2003, and 2004; (3) one study of disabilities and one study of immigrants; (4) two state specific studies of uninsured status; and (5) two current studies of healthcare reform. Of the thirteen studies reviewed, four directly addressed the study question about whether insuring the uninsured was more or less expensive than insuring the currently insured. All four of the studies provided support for the study finding that the cost of insuring the uninsured would generally not be higher than insuring those already insured. One study indicated that the cost of insuring the uninsured would be less expensive than insuring the population currently covered by Medicaid, but more expensive to insure than the populations of those covered by employer-sponsored insurance and non-group private insurance. While the nine other studies included in the systematic review discussed the costs associated with insuring the uninsured population, they did not directly compare the costs of insuring the uninsured population with the costs associated with insuring the currently insured population. For the MEPS secondary data analysis, the results of the chi-square tests indicated that there were differences in the distribution of disease status by health insurance status. As anticipated, with some exceptions, the uninsured reported lower rates of disease and healthcare service use. However, for the variable attention deficit disorder, the uninsured reported higher disease rates than the two insured groups. Additionally, for the variables high blood pressure, high cholesterol, and joint pain, the currently insured under Medicaid or SCHIP group reported a lower rate of disease than the two currently insured groups. This result may be due to the lower mean age of the currently insured under Medicaid or SCHIP group. Conclusion: Based on this study, with some exceptions, the costs for insuring the uninsured should not exceed healthcare-related costs for insuring the currently uninsured. The results of the systematic review indicated that the U.S. is already paying some of the costs associated with insuring the uninsured. PPACA will expand health insurance coverage to millions of Americans who are currently uninsured, as the individual mandate and insurance market reforms will require. Because many of the currently uninsured are relatively healthy young persons, the costs associated with expanding insurance coverage to the uninsured are anticipated to be relatively modest. However, for the purposes of construing these results, it is important to note that once individuals obtain insurance, it is anticipated that they will use more healthcare services, which will increase costs. (Abstract shortened by UMI.)^
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This cross-sectional analysis of the data from the Third National Health and Nutrition Examination Survey was conducted to determine the prevalence and determinants of asthma and wheezing among US adults, and to identify the occupations and industries at high risk of developing work-related asthma and work-related wheezing. Separate logistic models were developed for physician-diagnosed asthma (MD asthma), wheezing in the previous 12 months (wheezing), work-related asthma and work-related wheezing. Major risk factors including demographic, socioeconomic, indoor air quality, allergy, and other characteristics were analyzed. The prevalence of lifetime MD asthma was 7.7% and the prevalence of wheezing was 17.2%. Mexican-Americans exhibited the lowest prevalence of MD asthma (4.8%; 95% confidence interval (CI): 4.2, 5.4) when compared to other race-ethnic groups. The prevalence of MD asthma or wheezing did not vary by gender. Multiple logistic regression analysis showed that Mexican-Americans were less likely to develop MD asthma (adjusted odds ratio (ORa) = 0.64, 95%CI: 0.45, 0.90) and wheezing (ORa = 0.55, 95%CI: 0.44, 0.69) when compared to non-Hispanic whites. Low education level, current and past smoking status, pet ownership, lifetime diagnosis of physician-diagnosed hay fever and obesity were all significantly associated with MD asthma and wheezing. No significant effect of indoor air pollutants on asthma and wheezing was observed in this study. The prevalence of work-related asthma was 3.70% (95%CI: 2.88, 4.52) and the prevalence of work-related wheezing was 11.46% (95%CI: 9.87, 13.05). The major occupations identified at risk of developing work-related asthma and wheezing were cleaners; farm and agriculture related occupations; entertainment related occupations; protective service occupations; construction; mechanics and repairers; textile; fabricators and assemblers; other transportation and material moving occupations; freight, stock and material movers; motor vehicle operators; and equipment cleaners. The population attributable risk for work-related asthma and wheeze were 26% and 27% respectively. The major industries identified at risk of work-related asthma and wheeze include entertainment related industry; agriculture, forestry and fishing; construction; electrical machinery; repair services; and lodging places. The population attributable risk for work-related asthma was 36.5% and work-related wheezing was 28.5% for industries. Asthma remains an important public health issue in the US and in the other regions of the world. ^