4 resultados para data source

em DigitalCommons@The Texas Medical Center


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Objectives. To investigate procedural gender equity by assessing predisposing, enabling and need predictors of gender differences in annual medical expenditures and utilization among hypertensive individuals in the U.S. Also, to estimate and compare lifetime medical expenditures among hypertensive men and women in the U.S. ^ Data source. 2001-2004 the Medical Expenditure Panel Survey (MEPS);1986-2000 National Health Interview Survey (NHIS) and National Health Interview Survey linked to mortality in the National Death Index through 2002 (2002 NHIS-NDI). ^ Study design. We estimated total medical expenditure using four equations regression model, specific medical expenditures using two equations regression model and utilization using negative binomial regression model. Procedural equity was assessed by applying the Aday et al. theoretical framework. Expenditures were estimated in 2004 dollars. We estimated hypertension-attributable medical expenditure and utilization among men and women. ^ To estimate lifetime expenditures from ages 20 to 85+, we estimated medical expenditures with cross-sectional data and survival with prospective data. The four equations regression model were used to estimate average annual medical expenditures defined as sum of inpatient stay, emergency room visits, outpatient visits, office based visits, and prescription drugs expenditures. Life tables were used to estimate the distribution of life time medical expenditures for hypertensive men and women at different age and factors such as disease incidence, medical technology and health care cost were assumed to be fixed. Both total and hypertension attributable expenditures among men and women were estimated. ^ Data collection. We used the 2001-2004 MEPS household component and medical condition files; the NHIS person and condition files from 1986-1996 and 1997-2000 sample adult files were used; and the 1986-2000 NHIS that were linked to mortality in the 2002 NHIS-NDI. ^ Principal findings. Hypertensive men had significantly less utilization for most measures after controlling predisposing, enabling and need factors than hypertensive women. Similarly, hypertensive men had less prescription drug (-9.3%), office based (-7.2%) and total medical (-4.5%) expenditures than hypertensive women. However, men had more hypertension-attributable medical expenditures and utilization than women. ^ Expected total lifetime expenditure for average life table individuals at age 20, was $188,300 for hypertensive men and $254,910 for hypertensive women. But the lifetime expenditure that could be attributed to hypertension was $88,033 for men and $40,960 for women. ^ Conclusion. Hypertensive women had more utilization and expenditure for most measures than hypertensive men, possibly indicating procedural inequity. However, relatively higher hypertension-attributable health care of men shows more utilization of resources to treat hypertension related diseases among men than women. Similar results were reported in lifetime analyses.^ Key words: gender, medical expenditures, utilization, hypertension-attributable, lifetime expenditure ^

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Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

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The purpose of this study was to understand the role of principle economic, sociodemographic and health status factors in determining the likelihood and volume of prescription drug use. Econometric demand regression models were developed for this purpose. Ten explanatory variables were examined: family income, coinsurance rate, age, sex, race, household head education level, size of family, health status, number of medical visits, and type of provider seen during medical visits. The economic factors (family income and coinsurance) were given special emphasis in this study.^ The National Medical Care Utilization and Expenditure Survey (NMCUES) was the data source. The sample represented the civilian, noninstitutionalized residents of the United States in 1980. The sample method used in the survey was a stratified four-stage, area probability design. The sample was comprised of 6,600 households (17,123 individuals). The weighted sample provided the population estimates used in the analysis. Five repeated interviews were conducted with each household. The household survey provided detailed information on the United States health status, pattern of health care utilization, charges for services received, and methods of payments for 1980.^ The study provided evidence that economic factors influenced the use of prescription drugs, but the use was not highly responsive to family income and coinsurance for the levels examined. The elasticities for family income ranged from -.0002 to -.013 and coinsurance ranged from -.174 to -.108. Income has a greater influence on the likelihood of prescription drug use, and coinsurance rates had an impact on the amount spent on prescription drugs. The coinsurance effect was not examined for the likelihood of drug use due to limitations in the measurement of coinsurance. Health status appeared to overwhelm any effects which may be attributed to family income or coinsurance. The likelihood of prescription drug use was highly dependent on visits to medical providers. The volume of prescription drug use was highly dependent on the health status, age, and whether or not the individual saw a general practitioner. ^

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Objective. To perform a systematic review of the internet based HIV prevention interventions.^ Data Source. Data resources including Ovid Medline, CINAHL (EBSCOhost and Psycinfo) were searched for the relevant articles. Study Selection: Studies were selected if the entire article was in English, Randomized control trial performed after 1998 till current, internet based aimed towards HIV/AIDS prevention. ^ Data Extraction. Each relevant article was coded using a code sheet which consisted of background information, study characteristics, study population information, program details, intervention and results. Data Synthesis: Total of seven relevant articles were coded and the information obtained was incorporated into the evidence tables for comparison.^ Conclusion. Overall the internet based HIV prevention studies have been very successful in recruiting large number of people but has not been able to show effective results due to high attrition. More research needs to be done in the area.^