20 resultados para health costs

em DigitalCommons@The Texas Medical Center


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The aim of this study was to examine the association between determinants of access to healthcare and preventable hospitalizations, based on Davidson et al.'s framework for evaluating the effects of individual and community determinants on access to healthcare. The study population consisted of the low income, non-elderly, hospitalized adults residing in Harris County, Texas in 2004. The objectives of this study were to examine the proportion of the variance in preventable hospitalizations at the ZIP-code level, to analyze the association between the proximity to the nearest safety net clinic and preventable hospitalizations, to examine how the safety net capacity relates to preventable hospitalizations, to compare the relative strength of the associations of health insurance and the proximity to the nearest safety net clinic with preventable hospitalizations, and to estimate and compare the costs of preventable hospitalizations in Harris County with the average cost in the literature. The data were collected from Texas Health Care Information Collection (2004), Census 2000, and Project Safety Net (2004). A total of 61,841 eligible individuals were included in the final data analysis. A random-intercept multi-level model was constructed with two different levels of data: the individual level and the ZIP-code level. The results of this study suggest that ZIP-code characteristics explain about two percent of the variance in preventable hospitalizations and safety net capacity was marginally significantly associated with preventable hospitalizations (p= 0.062). Proximity to the nearest safety net clinic was not related to preventable hospitalizations; however, health insurance was significantly associated with a decreased risk of preventable hospitalization. The average direct cost was $6,466 per preventable hospitalization, which is significantly different from reports in the literature. ^

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Characteristics of Medicare-certified home health agencies in Texas and the contributions of selected agency characteristics on home health care costs were examined. Cost models were developed and estimated for both nursing and total visit costs using multiple regression procedures. The models included home health agency size, profit status, control, hospital-based affiliation, contract-cost ratio, service provision, competition, urban-rural input-price differences, and selected measures of patient case-mix. The study population comprised 314 home health agencies in Texas that had been certified at least one year on July, 1, 1986. Data for the analysis were obtained from Medicare Cost Reports for fiscal year ending between July 1, 1985 to June 30, 1986.^ Home health agency size, as measured by the logs of nursing and total visits, has a statistically significant negative linear relationship with nursing visit and total visit costs. Nursing and total visit costs decrease at a declining rate as size increases. The size-cost relationship is not altered when controlling for any other agency characteristic. The number of visits per patient per year, a measure of patient case-mix, is also negatively related to costs, suggesting that costs decline with care of chronic patients. Hospital-based affiliation and urban location are positively associated with costs. Together, the four characteristics explain 19 percent of the variance in nursing visit costs and 24 percent of the variance in total visit costs.^ Profit status and control, although correlated with other agency characteristics, exhibit no observable effect on costs. Although no relationship was found between costs and competition, contract cost ratio, or the provision on non-reimburseable services, no conclusions can be made due to problems with measurement of these variables. ^

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The United States health care system faces significant challenges, particularly with problems of the uninsured and with the rising costs of care. These problems lead many to study and discuss strategies for reforming the health care system. Four different plans for ideal health care reform, set forth by notable scholars or organizations, are explained herein. Then, states within the United States are examined in terms of their recent efforts at health care reform. Those states proposing significant changes to their health care systems are analyzed—namely, Maine, Massachusetts, and Vermont. The strategies used in these three states are compared to the strategies laid out by the experts in order to determine which strategies are the most popular in current health care reform efforts among the states studied here. These strategies are totaled to find which organization's plan for ideal reform seems to be the most popular. The strategies of managed competition are shown to be the most popular strategies among these three state health care reforms, while the strategies of the single-payer plan discussed herein were the least popular. All three states seem to utilize strategies that build upon their previous health care system, rather than implementing strategies that completely replace the previous system. ^

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The federal government is currently developing the Nationwide Health Information Network (NHIN). Described as a “network of networks,” the NHIN seeks to provide a nationwide, interoperable health information infrastructure that will securely connect consumers with those involved in health care. As part of the national health information technology (HIT) agenda, the NHIN aims to improve individual and population health by enabling health information to follow the consumer, be available for clinical decision-making, and support important public health measures such as biosurveillance. While the NHIN promises to improve clinical care to individuals and to reduce U.S. health care system costs overall, this electronic environment presents novel challenges for protecting individually identifiable health information. A major barrier to achieving public trust in the NHIN is the development of, and adherence to, a consistent and coordinated approach to privacy and security of health information. This paper will analyze the policy framework for electronic health information exchange with the NHIN. This exercise will demonstrate that the current policy is an effective framework for achieving effective biosurveillance with the NHIN. ^

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Emergency Departments (EDs) and Emergency Rooms (ERs) are designed to manage trauma, respond to disasters, and serve as the initial care for those with serious illnesses. However, because of many factors, the ED has become the doorway to the hospital and a “catch-all net” for patients including those with non-urgent needs. This increase in the population in the ED has lead to an increase in wait times for patients. It has been well documented that there has been a constant and consistent rise in the number of patients that frequent the ED (National Center for Health Statistics, 2002); the wait time for patients in the ED has increased (Pitts, Niska, Xu, & Burt, 2008); and the cost of the treatment in the ER has risen (Everett Clinic, 2008). Because the ED was designed to treat patients who need quick diagnoses and may be in potential life-threatening circumstances, management of time can be the ultimate enemy. If a system was implemented to decrease wait times in the ED, decrease the use of ED resources, and decrease costs endured by patients seeking care, better outcomes for patients and patient satisfaction could be achieved. The goal of this research was to explore potential changes and/or alternatives to relieve the burden endured by the ED. In order to explore these options, data was collected by conducting one-on-one interviews with seven physicians closely tied to a Level 1 ED (Emergency Room physicians, Trauma Surgeons and Primary Care physicians). A qualitative analysis was performed on the responses of one-on-one interviews with the aforementioned physicians. The interviews were standardized, open-ended questions that probe what makes an effective ED, possible solutions to improving patient care in the ED, potential remedies for the mounting problems that plague the ED, and the feasibility of bringing Primary Care Physicians to the ED to decrease the wait times experienced by the patient. From the responses, it is clear that there needs to be more research in this area, several areas need to be addressed, and a variety of solutions could be implemented. The most viable option seems to be making the ED its own entity (similar to the clinic or hospital) that includes urgent clinics as a part of the system, in which triage and better staffing would be the most integral part of its success.^

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This study aims to address two research questions. First, ‘Can we identify factors that are determinants both of improved health outcomes and of reduced costs for hospitalized patients with one of six common diagnoses?’ Second, ‘Can we identify other factors that are determinants of improved health outcomes for such hospitalized patients but which are not associated with costs?’ The Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) database from 2003 to 2006 was employed in this study. The total study sample consisted of hospitals which had at least 30 patients each year for the given diagnosis: 954 hospitals for acute myocardial infarction (AMI), 1552 hospitals for congestive heart failure (CHF), 1120 hospitals for stroke (STR), 1283 hospitals for gastrointestinal hemorrhage (GIH), 979 hospitals for hip fracture (HIP), and 1716 hospitals for pneumonia (PNE). This study used simultaneous equations models to investigate the determinants of improvement in health outcomes and of cost reduction in hospital inpatient care for these six common diagnoses. In addition, the study used instrumental variables and two-stage least squares random effect model for unbalanced panel data estimation. The study concluded that a few factors were determinants of high quality and low cost. Specifically, high specialty was the determinant of high quality and low costs for CHF patients; small hospital size was the determinant of high quality and low costs for AMI patients. Furthermore, CHF patients who were treated in Midwest, South, and West region hospitals had better health outcomes and lower hospital costs than patients who were treated in Northeast region hospitals. Gastrointestinal hemorrhage and pneumonia patients who were treated in South region hospitals also had better health outcomes and lower hospital costs than patients who were treated in Northeast region hospitals. This study found that six non-cost factors were related to health outcomes for a few diagnoses: hospital volume, percentage emergency room admissions for a given diagnosis, hospital competition, specialty, bed size, and hospital region.^

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A sample of 157 AIDS patients 17 years of age or over were followed for six months from the date of hospital discharge to derive average total cost of medical care, utilization and satisfaction with care. Those referred for home care follow-up after discharge from the hospital were compared with those who did not receive home care.^ The average total cost of medical care for all patients was $34,984. Home care patient costs averaged \$29,614 while patients with no home care averaged $37,091. Private hospital patients had average costs of \$50,650 compared with $25,494 for public hospital patients. Hospital days for the six months period averaged 23.9 per patient for the no home care group and 18.5 days for home care group. Patient satisfaction with care was higher in the home care group than no home care group, with a mean score of 68.2 compared with 61.1.^ Other health services information indicated that 98% of the private hospital patients had insurance while only 2% of public hospital patients had coverage. The time between the initial date of diagnosis with AIDS and admission to the study was longer for private hospital patients, survival time over the study period was shorter, and the number of hospitalizations prior to entering the study was higher for private hospital patients. These results suggest that patients treated in the private hospital were sicker than public hospital patients, which may explain their higher average total cost. Statistical analyses showed that cost and utilization have no significant relationship with home care or no home care when controlling for indicators of the severity of illness and treatment in public or private hospital.^ In future studies, selecting a matched group of patients from the same hospital and following them for nine months to one year would be helpful in making a more realistic comparison of the cost effectiveness of home care. ^

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The purpose of this study was to assess the impact of the Arkansas Long-Term Care Demonstration Project upon Arkansas' Medicaid expenditures and upon the clients it serves. A Retrospective Medicaid expenditure study component used analyses of variance techniques to test for the Project's effects upon aggregated expenditures for 28 demonstration and control counties representing 25 percent of the State's population over four years, 1979-1982.^ A second approach to the study question utilized a 1982 prospective sample of 458 demonstration and control clients from the same 28 counties. The disability level or need for care of each patient was established a priori. The extent to which an individual's variation in Medicaid utilization and costs was explained by patient need, presence or absence of the channeling project's placement decision or some other patient characteristic was examined by multiple regression analysis. Long-term and acute care Medicaid, Medicare, third party, self-pay and the grand total of all Medicaid claims were analyzed for project effects and explanatory relationships.^ The main project effect was to increase personal care costs without reducing nursing home or acute care costs (Prospective Study). Expansion of clients appeared to occur in personal care (Prospective Study) and minimum care nursing home (Retrospective Study) for the project areas. Cost-shifting between Medicaid and Medicare in the project areas and two different patterns of utilization in the North and South projects tended to offset each other such that no differences in total costs between the project areas and demonstration areas occurred. The project was significant ((beta) = .22, p < .001) only for personal care costs. The explanatory power of this personal care regression model (R('2) = .36) was comparable to other reported health services utilization models. Other variables (Medicare buy-in, level of disability, Social Security Supplemental Income (SSI), net monthly income, North/South areas and age) explained more variation in the other twelve cost regression models. ^

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This research examined to what extent Health Belief Model (HBM) and socioeconomic variables were useful in explaining the choice whether or not more effective contraceptive methods were used among married fecund women intending no additional births. The source of the data was the 1976 National Survey of Family Growth conducted under the auspices of the National Center for Health Statistics. Using the HBM as a framework for multivariate analyses limited support was found (using available measures) that the HBM components of motivation and perceived efficacy influence the likelihood of more effective contraceptive method use. Support was also found that modifying variables suggested by the HBM can influence the effects of HBM components on the likelihood of more effective method use. Socioeconomic variables were found, using all cases and some subgroups, to have a significant additional influence on the likelihood of use of more effective methods. Limited support was found for the concept that the greater the opportunity costs of an unwanted birth the greater the likelihood of use of more effective contraceptive methods. This research supports the use of HBM and socioeconomic variables to explain the likelihood of a protective health behavior, use of more effective contraception if no additional births are intended.^

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The research project is an extension of the economic theory to the health care field and health care research projects evaluating the influence of demand and supply variables upon medical care inflation. The research tests a model linking the demographic and socioeconomic characteristics of the population, its community case mix, and technology, the prices of goods and services other than medical care, the way its medical services are delivered and the health care resources available to its population to different utilization patterns which, consequently, lead to variations in health care prices among metropolitan areas. The research considers the relationship of changes in community characteristics and resources and medical care inflation.^ The rapidly increasing costs of medical care have been of great concern to the general public, medical profession, and political bodies. Research and analysis of the main factors responsible for the rate of increase of medical care prices is necessary in order to devise appropriate solutions to cope with the problem. An understanding of the community characteristics and resources-medical care costs relationships in the metropolitan areas potentially offers guidance in individual plan and national policy development.^ The research considers 145 factors measuring community milieu (demographic, social, educational, economic, illness level, prices of goods and services other than medical care, hospital supply, physicians resources and techological factors). Through bivariate correlation analysis, the number of variables was reduced to a set of 1 to 4 variables for each cost equation. Two approaches were identified to track inflation in the health care industry. One approach measures costs of production which accounts for price and volume increases. The other approach measures price increases. One general and four specific measures were developed to represent each of the major approaches. The general measure considers the increase on medical care prices as a whole and the specific measures deal with hospital costs and physician's fees. The relationships among changes in community characteristics and resources and health care inflation were analyzed using bivariate correlation and regression analysis methods. It has been concluded that changes in community characteristics and resources are predictive of hospital costs and physician's fees inflation, but are not predictive of increases in medical care prices. These findings provide guidance in the formulation of public policy which could alter the trend of medical care inflation and in the allocation of limited Federal funds.^

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The purpose of this 1982 national survey of all operational prepaid health plans, or PHPs (including health maintenance organizations), was to provide information on the current coverage of PHP mental health and substance abuse services, benefits and service provision, general and mental health organization characteristics, mental health service costs, and physical and mental health service utilization.^ Two survey instruments were designed, pretested and distributed to all operational PHPs throughout the United States. A total of 237 PHPs were surveyed, of which 205 (86.50 percent) completed and returned both questionnaires.^ One result of the rapid growth in the PHP field over the past ten years has been the expansion in both the number of PHPs as well as the organizational characteristics of these PHPs. However, little attention in the research literature has been given to the application of empirical results to the PHP arrangements. This project has attempted to contribute to current knowledge regarding prepaid mental health services from a national perspective, and explore, on a preliminary descriptive basis, the variety of potential service delivery arrangements for physical and mental health services (total services) and for mental health services.^ The study emphasized that PHPs must continue to monitor the costs and utilization of mental health services, particularly in light of the apparent elimination of data collection and statistical summary responsibilities within the federal government regarding PHP activities as well as the proposed legislation to eliminate mandated mental health and substance abuse services from basic health plan benefits for federally qualified PHPs. ^

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Medication reconciliation, with the aim to resolve medication discrepancy, is one of the Joint Commission patient safety goals. Medication errors and adverse drug events that could result from medication discrepancy affect a large population. At least 1.5 million adverse drug events and $3.5 billion of financial burden yearly associated with medication errors could be prevented by interventions such as medication reconciliation. This research was conducted to answer the following research questions: (1a) What are the frequency range and type of measures used to report outpatient medication discrepancy? (1b) Which effective and efficient strategies for medication reconciliation in the outpatient setting have been reported? (2) What are the costs associated with medication reconciliation practice in primary care clinics? (3) What is the quality of medication reconciliation practice in primary care clinics? (4) Is medication reconciliation practice in primary care clinics cost-effective from the clinic perspective? Study designs used to answer these questions included a systematic review, cost analysis, quality assessments, and cost-effectiveness analysis. Data sources were published articles in the medical literature and data from a prospective workflow study, which included 150 patients and 1,238 medications. The systematic review confirmed that the prevalence of medication discrepancy was high in ambulatory care and higher in primary care settings. Effective strategies for medication reconciliation included the use of pharmacists, letters, a standardized practice approach, and partnership between providers and patients. Our cost analysis showed that costs associated with medication reconciliation practice were not substantially different between primary care clinics using or not using electronic medical records (EMR) ($0.95 per patient per medication in EMR clinics vs. $0.96 per patient per medication in non-EMR clinics, p=0.78). Even though medication reconciliation was frequently practiced (97-98%), the quality of such practice was poor (0-33% of process completeness measured by concordance of medication numbers and 29-33% of accuracy measured by concordance of medication names) and negatively (though not significantly) associated with medication regimen complexity. The incremental cost-effectiveness ratios for concordance of medication number per patient per medication and concordance of medication names per patient per medication were both 0.08, favoring EMR. Future studies including potential cost-savings from medication features of the EMR and potential benefits to minimize severity of harm to patients from medication discrepancy are warranted. ^

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Objectives: To compare mental health care utilization regarding the source, types, and intensity of mental health services received, unmet need for services, and out of pocket cost among non-institutionalized psychologically distressed women and men. ^ Method: Cross-sectional data for 19,325 non-institutionalized mentally distressed adult respondents to the “The National Survey on Drug Use and Health” (NSDUH), for the years 2006 -2008, representing over twenty-nine millions U.S. adults was analyzed. To assess the relative odds for women compared to men, logistic regression analysis was used for source of service, for types of barriers, for unmet need and cost; zero inflated negative binomial regression for intensity of utilization; and ordinal logistic regression analysis for quantifying out-of-pocket expenditure. ^ Results: Overall, 43% of mentally distressed adults utilized a form of mental health treatment; representing 12.6 million U.S psychologically distressed adults. Females utilized more mental health care compared to males in the previous 12 months (OR: 1. 70; 95% CI: 1.54, 1.83). Similarly, females were 54% more likely to get help for psychological distress in an outpatient setting and females were associated with an increased probability of using medication for mental distress (OR: 1.72; 95% CI: 1.63, 1.98). Women were 1.25 times likelier to visit a mental health center (specialty care) than men. ^ Females were positively associated with unmet needs (OR: 1.50; 95% CI: 1.29, 1.75) after taking into account predisposing, enabling, and need (PEN) characteristics. Women with perceived unmet needs were 23% (OR: 0.77; 95% CI: 0.59, 0.99) less likely than men to report societal accommodation (stigma) as a barrier to mental health care. At any given cutoff point, women were 1.74 times likelier to be in the higher payment categories for inpatient out of pocket cost when other variables in the model are held constant. Conclusions: Women utilize more specialty mental healthcare, report more unmet need, and pay more inpatient out of pocket costs than men. These gender disparities exist even after controlling for predisposing, enabling, and need variables. Creating policies that not only provide mental health care access but also de-stigmatize mental illness will bring us one step closer to eliminating gender disparities in mental health care.^

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Preventable Hospitalizations (PHs) are hospitalizations that can be avoided with appropriate and timely care in the ambulatory setting and hence are closely associated with primary care access in a community. Increased primary care availability and health insurance coverage may increase primary care access, and consequently may be significantly associated with risks and costs of PHs. Objective. To estimate the risk and cost of preventable hospitalizations (PHs); to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs, first alone and then simultaneously; and finally, to estimate the impact of expansions in primary care availability and health insurance coverage on the burden of PHs among non-elderly adult residents of Harris County. Methods. The study population was residents of Harris County, age 18 to 64, who had at least one hospital discharge in a Texas hospital in 2008. The primary independent variables were availability of primary care physicians, availability of primary care safety net clinics and health insurance coverage. The primary dependent variables were PHs and associated hospitalization costs. The Texas Health Care Information Collection (THCIC) Inpatient Discharge data was used to obtain information on the number and costs of PHs in the study population. Risk of PHs in the study population, as well as average and total costs of PHs were calculated. Multivariable logistic regression models and two-step Heckman regression models with log-transformed costs were used to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs respectively, while controlling for individual predisposing, enabling and need characteristics. Predicted PH risk and cost were used to calculate the predicted burden of PHs in the study population and the impact of expansions in primary care availability and health insurance coverage on the predicted burden. Results. In 2008, hospitalized non-elderly adults in Harris County had 11,313 PHs and a corresponding PH risk of 8.02%. Congestive heart failure was the most common PH. PHs imposed a total economic burden of $84 billion at an average of $7,449 per PH. Higher primary care safety net availability was significantly associated with the lower risk of PHs in the final risk model, but only in the uninsured. A unit increase in safety net availability led to a 23% decline in PH odds in the uninsured, compared to only a 4% decline in the insured. Higher primary care physician availability was associated with increased PH costs in the final cost model (β=0.0020; p<0.05). Lack of health insurance coverage increased the risk of PH, with the uninsured having 30% higher odds of PHs (OR=1.299; p<0.05), but reduced the cost of a PH by 7% (β=-0.0668; p<0.05). Expansions in primary care availability and health insurance coverage were associated with a reduction of about $1.6 million in PH burden at the highest level of expansion. Conclusions. Availability of primary care resources and health insurance coverage in hospitalized non-elderly adults in Harris County are significantly associated with the risk and costs of PHs. Expansions in these primary care access factors can be expected to produce significant reductions in the burden of PHs in Harris County.^

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Better morbidity and mortality outcomes associated with increased hospital procedural volume have been demonstrated across a number of different medical procedures. Existence of such a volume-outcome relationship is posited to lead to increased specialization of care, such that patients requiring specific procedures are funneled to physicians and hospitals that achieve a minimum volume of such procedures each year. In this study, the 2009 Nationwide Inpatient Sample is used to examine the relationship between hospital volume and patient outcome among patients undergoing procedures related to malignant brain cancer. Multiple regression models were used to examine the impact of hospital volume on length of inpatient stay and cost of inpatient stay; logistic regression was used to examine the impact of hospital volume on morbidity. Hospital volume was found to be a significant predictor of both length of stay and cost of stay. Hospital volume was associated with a lower length of stay, but was also associated with increased costs. Hospital volume was not found to be a statistically significant predictor of morbidity, though less than three percent of this sample died while in the hospital. Volume is indeed a significant predictor of outcome for procedures related to brain malignancies, though further research regarding the cost of such procedures is recommended.^