973 resultados para United States. Public Health and Marine Hospital Service
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Reuse of record except for individual research requires license from Congressional Information Service, Inc.
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Reuse of record except for individual research requires license from Congressional Information Service, Inc.
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Mode of access: Internet.
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Bennett Champ Clark, chairman of subcommittee.
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A nested case-control study design was used to investigate the relationship between radiation exposure and brain cancer risk in the United States Air Force (USAF). The cohort consisted of approximately 880,000 men with at least 1 year of service between 1970 and 1989. Two hundred and thirty cases were identified from hospital discharge records with a diagnosis of primary malignant brain tumor (International Classification of Diseases, 9th revision, code 191). Four controls were exactly matched with each case on year of age and race using incidence density sampling. Potential career summary extremely low frequency (ELF) and microwave-radiofrequency (MWRF) radiation exposures were based upon the duration in each occupation and an intensity score assigned by an expert panel. Ionizing radiation (IR) exposures were obtained from personal dosimetry records.^ Relative to the unexposed, the overall age-race adjusted odds ratio (OR) for ELF exposure was 1.39, 95 percent confidence interval (CI) 1.03-1.88. A dose-response was not evident. The same was true for MWRF, although the OR = 1.59, with 95 percent CI 1.18-2.16. Excess risk was not found for IR exposure (OR = 0.66, 45 percent CI 0.26-1.72).^ Increasing socioeconomic status (SES), as identified by military pay grade, was associated with elevated brain tumor risk (officer vs. enlisted personnel age-race adjusted OR = 2.11, 95 percent CI 1.98-3.01, and senior officers vs. all others age-race adjusted OR = 3.30, 95 percent CI 2.0-5.46). SES proved to be an important confounder of the brain tumor risk associated with ELF and MWRF exposure. For ELF, the age-race-SES adjusted OR = 1.28, 95 percent CI 0.94-1.74, and for MWRF, the age-race-SES adjusted OR = 1.39, 95 percent CI 1.01-1.90.^ These results indicate that employment in Air Force occupations with potential electromagnetic field exposures is weakly, though not significantly, associated with increased risk for brain tumors. SES appeared to be the most consistent brain tumor risk factor in the USAF cohort. Other investigators have suggested that an association between brain tumor risk and SES may arise from differential access to medical care. However, in the USAF cohort health care is universally available. This study suggests that some factor other than access to medical care must underlie the association between SES and brain tumor risk. ^
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This investigation compares two different methodologies for calculating the national cost of epilepsy: provider-based survey method (PBSM) and the patient-based medical charts and billing method (PBMC&BM). The PBSM uses the National Hospital Discharge Survey (NHDS), the National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Ambulatory Medical Care Survey (NAMCS) as the sources of utilization. The PBMC&BM uses patient data, charts and billings, to determine utilization rates for specific components of hospital, physician and drug prescriptions. ^ The 1995 hospital and physician cost of epilepsy is estimated to be $722 million using the PBSM and $1,058 million using the PBMC&BM. The difference of $336 million results from $136 million difference in utilization and $200 million difference in unit cost. ^ Utilization. The utilization difference of $136 million is composed of an inpatient variation of $129 million, $100 million hospital and $29 million physician, and an ambulatory variation of $7 million. The $100 million hospital variance is attributed to inclusion of febrile seizures in the PBSM, $−79 million, and the exclusion of admissions attributed to epilepsy, $179 million. The former suggests that the diagnostic codes used in the NHDS may not properly match the current definition of epilepsy as used in the PBMC&BM. The latter suggests NHDS errors in the attribution of an admission to the principal diagnosis. ^ The $29 million variance in inpatient physician utilization is the result of different per-day-of-care physician visit rates, 1.3 for the PBMC&BM versus 1.0 for the PBSM. The absence of visit frequency measures in the NHDS affects the internal validity of the PBSM estimate and requires the investigator to make conservative assumptions. ^ The remaining ambulatory resource utilization variance is $7 million. Of this amount, $22 million is the result of an underestimate of ancillaries in the NHAMCS and NAMCS extrapolations using the patient visit weight. ^ Unit cost. The resource cost variation is $200 million, inpatient is $22 million and ambulatory is $178 million. The inpatient variation of $22 million is composed of $19 million in hospital per day rates, due to a higher cost per day in the PBMC&BM, and $3 million in physician visit rates, due to a higher cost per visit in the PBMC&BM. ^ The ambulatory cost variance is $178 million, composed of higher per-physician-visit costs of $97 million and higher per-ancillary costs of $81 million. Both are attributed to the PBMC&BM's precise identification of resource utilization that permits accurate valuation. ^ Conclusion. Both methods have specific limitations. The PBSM strengths are its sample designs that lead to nationally representative estimates and permit statistical point and confidence interval estimation for the nation for certain variables under investigation. However, the findings of this investigation suggest the internal validity of the estimates derived is questionable and important additional information required to precisely estimate the cost of an illness is absent. ^ The PBMC&BM is a superior method in identifying resources utilized in the physician encounter with the patient permitting more accurate valuation. However, the PBMC&BM does not have the statistical reliability of the PBSM; it relies on synthesized national prevalence estimates to extrapolate a national cost estimate. While precision is important, the ability to generalize to the nation may be limited due to the small number of patients that are followed. ^
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The 1982–1994 National Long-Term Care Surveys indicate an accelerating decline in disability among the U.S. elderly population, suggesting that a 1.5% annual decline in chronic disability for elderly persons is achievable. Furthermore, many risk factors for chronic diseases show improvements, many linked to education, from 1910 to the present. Projections indicate the proportion of persons aged 85–89 with less than 8 years of education will decline from 65% in 1980 to 15% in 2015. Health and socioeconomic status trends are not directly represented in Medicare Trust Fund and Social Security Administration beneficiary projections. Thus, they may have different economic implications from projections directly accounting for health trends. A 1.5% annual disability decline keeps the support ratio (ratio of economically active persons aged 20–64 to the number of chronically disabled persons aged 65+) above its 1994 value, 22:1, when the Hospital Insurance Trust Fund was in fiscal balance, to 2070. With no changes in disability, projections indicate a support ratio in 2070 of 8:1—63% below a cash flow balance.
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Issued Jan. 1977.
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"Serial no. 100-149."
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Includes indexes.
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Mode of access: Internet.
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Lettered on cover: Roster of Maine in the World War.