28 resultados para Military hospitals.
Resumo:
Many public health agencies and researchers are interested in comparing hospital outcomes, for example, morbidity, mortality, and hospitalization across areas and hospitals. However, since there is variation of rates in clinical trials among hospitals because of several biases, we are interested in controlling for the bias and assessing real differences in clinical practices. In this study, we compared the variations between hospitals in rates of severe Intraventricular Haemorrhage (IVH) infant using Frequentist statistical approach vs. Bayesian hierarchical model through simulation study. The template data set for simulation study was included the number of severe IVH infants of 24 intensive care units in Australian and New Zealand Neonatal Network from 1995 to 1997 in severe IVH rate in preterm babies. We evaluated the rates of severe IVH for 24 hospitals with two hierarchical models in Bayesian approach comparing their performances with the shrunken rates in Frequentist method. Gamma-Poisson (BGP) and Beta-Binomial (BBB) were introduced into Bayesian model and the shrunken estimator of Gamma-Poisson (FGP) hierarchical model using maximum likelihood method were calculated as Frequentist approach. To simulate data, the total number of infants in each hospital was kept and we analyzed the simulated data for both Bayesian and Frequentist models with two true parameters for severe IVH rate. One was the observed rate and the other was the expected severe IVH rate by adjusting for five predictors variables for the template data. The bias in the rate of severe IVH infant estimated by both models showed that Bayesian models gave less variable estimates than Frequentist model. We also discussed and compared the results from three models to examine the variation in rate of severe IVH by 20th centile rates and avoidable number of severe IVH cases. ^
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The Long Term Acute Care Hospitals (LTACH), which serve medically complex patients, have grown tremendously in recent years, by expanding the number of Medicare patient admissions and thus increasing Medicare expenditures (Stark 2004). In an attempt to mitigate the rapid growth of the LTACHs and reduce related Medicare expenditures, Congress enacted Section 114 of P.L. 110-173 (§114) of the Medicare, Medicaid and SCHIP Extension Act (MMSEA) in December 29, 2007 to regulate the LTCAHs industry. MMSEA increased the medical necessity reviews for Medicare admissions, imposed a moratorium on new LTCAHs, and allowed the Centers for Medicare and Medicaid Services (CMS) to recoup Medicare overpayments for unnecessary admissions. ^ This study examines whether MMSEA impacted LTACH admissions, operating margins and efficiency. These objectives were analyzed by comparing LTACH data for 2008 (post MMSEA) and data for 2006-2007 (pre-MMSEA). Secondary data were utilized from the American Hospital Association (AHA) database and the American Hospital Directory (AHD).^ This is a longitudinal retrospective study with a total sample of 55 LTACHs, selected from 396 LTACHs facilities that were fully operational during the study period of 2006-2008. The results of the research found no statistically significant change in total Medicare admissions; instead there was a small but not statistically significant reduction of 5% in Medicare admissions for 2008 in comparison to those for 2006. A statistically significant decrease in mean operating margins was confirmed between the years 2006 and 2008. The LTACHs' Technical Efficiency (TE), as computed by Data Envelopment Analysis (DEA), showed significant decrease in efficiency over the same period. Thirteen of the 55 LTACHs in the sample (24%) in 2006 were calculated as “efficient” utilizing the DEA analysis. This dropped to 13% (7/55) in 2008. Longitudinally, the decrease in efficiency using the DEA extension technique (Malmquist Index or MI) indicated a deterioration of 10% in efficiency over the same period. Interestingly, however, when the sample was stratified into high efficient versus low efficient subgroups (approximately 25% in each group), a comparison of the MIs suggested a significant improvement in Efficiency Change (EC) for the least efficient (MI 0.92022) and reduction in efficiency for the most efficient LTACHs (MI = 1.38761) over same period. While a reduction in efficiency for the most efficient is unexpected, it is not particularly surprising, since efficiency measure can vary over time. An improvement in efficiency, however, for the least efficient should be expected as those LTACHs begin to manage expenses (and controllable resources) more carefully to offset the payment/reimbursement pressures on their margins from MMSEA.^
Resumo:
Purpose. To evaluate the use of the Legionella Urine Antigen Test as a cost effective method for diagnosing Legionnaires’ disease in five San Antonio Hospitals from January 2007 to December 2009. ^ Methods. The data reported by five San Antonio hospitals to the San Antonio Metropolitan Health District during a 3-year retrospective study (January 2007 to December 2009) were evaluated for the frequency of non-specific pneumonia infections, the number of Legionella Urine Antigen Tests performed, and the percentage of positive cases of Legionnaires’ disease diagnosed by the Legionella Urine Antigen Test.^ Results. There were a total of 7,087 cases of non-specific pneumonias reported across the five San Antonio hospitals studied from 2007 to 2009. A total of 5,371 Legionella Urine Antigen Tests were performed from January, 2007 to December, 2009 across the five San Antonio hospitals in the study. A total of 38 positive cases of Legionnaires’ disease were identified by the use of Legionella Urinary Antigen Test from 2007-2009.^ Conclusions. In spite of the limitations of this study in obtaining sufficient relevant data to evaluate the cost effectiveness of Legionella Urinary Antigen Test in diagnosing Legionnaires’ disease, the Legionella Urinary Antigen Test is simple, accurate, faster, as results can be obtained within minutes to hours; and convenient because it can be performed in emergency room department to any patient who presents with the clinical signs or symptoms of pneumonia. Over the long run, it remains to be shown if this test may decrease mortality, lower total medical costs by decreasing the number of broad-spectrum antibiotics prescribed, shorten patient wait time/hospital stay, and decrease the need for unnecessary ancillary testing, and improve overall patient outcomes.^
Resumo:
The purpose of this study was to compare the financial performance of small rural hospitals to that of small urban hospitals in Texas. Hospital-specific and environmental factors were studied as control variables.^ Small rural hospitals were found to be financially stronger on measures of liquidity but weaker on measures of profitability. Small urban hospitals performed better on measures of profitability and long-range solvency. When all measures in the five dimensions of financial performance were analyzed, no significant difference was found between the two groups of hospitals. None of the control variables included in the study was significantly associated with financial performance both for rural and urban hospitals. Conclusions were that small rural hospitals in Texas are experiencing a deterioration in financial condition but small, rural hospitals are not doing any worse than small urban hospitals; and that the financial hardship which rural hospitals suffer may be inherent in the nature of the institutions themselves, and not as a result of their smallness nor their rural settings. ^
Resumo:
This study demonstrated that accurate, short-term forecasts of Veterans Affairs (VA) hospital utilization can be made using the Patient Treatment File (PTF), the inpatient discharge database of the VA. Accurate, short-term forecasts of two years or less can reduce required inventory levels, improve allocation of resources, and are essential for better financial management. These are all necessary achievements in an era of cost-containment.^ Six years of non-psychiatric discharge records were extracted from the PTF and used to calculate four indicators of VA hospital utilization: average length of stay, discharge rate, multi-stay rate (a measure of readmissions) and days of care provided. National and regional levels of these indicators were described and compared for fiscal year 1984 (FY84) to FY89 inclusive.^ Using the observed levels of utilization for the 48 months between FY84 and FY87, five techniques were used to forecast monthly levels of utilization for FY88 and FY89. Forecasts were compared to the observed levels of utilization for these years. Monthly forecasts were also produced for FY90 and FY91.^ Forecasts for days of care provided were not produced. Current inpatients with very long lengths of stay contribute a substantial amount of this indicator and it cannot be accurately calculated.^ During the six year period between FY84 and FY89, average length of stay declined substantially, nationally and regionally. The discharge rate was relatively stable, while the multi-stay rate increased slightly during this period. FY90 and FY91 forecasts show a continued decline in the average length of stay, while the discharge rate is forecast to decline slightly and the multi-stay rate is forecast to increase very slightly.^ Over a 24 month ahead period, all three indicators were forecast within a 10 percent average monthly error. The 12-month ahead forecast errors were slightly lower. Average length of stay was less easily forecast, while the multi-stay rate was the easiest indicator to forecast.^ No single technique performed significantly better as determined by the Mean Absolute Percent Error, a standard measure of error. However, Autoregressive Integrated Moving Average (ARIMA) models performed well overall and are recommended for short-term forecasting of VA hospital utilization. ^
Resumo:
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 number of medical and social developments have had an impact on the neonatal mortality over the past ten to 15 years in the United States. The purpose of this study was to examine one of these developments, Newborn Intensive Care Units (NICUs), and evaluate their impact on neonatal mortality in Houston, Texas.^ This study was unique in that it used as its data base matched birth and infant death records from two periods of time: 1958-1960 (before NICUs) and 1974-1976 (after NICUs). The neonatal mortality of single, live infants born to Houston resident mothers was compared for two groups: infants born in hospitals which developed NICUs and infants born in all other Houston hospitals. Neonatal mortality comparisons were made using the following birth-characteristic variables: birthweight, gestation, race, sex, maternal age, legitimacy, birth order and prenatal care.^ The results of the study showed that hospitals which developed NICUs had a higher percentage of their population with high risk characteristics. In spite of this, they had lower neonatal mortality rates in two categories: (1) white 3.5-5.5 pounds birthweight infants, (2) low birthweight infants whose mothers received no prenatal care. Black 3.5-5.5 pounds birthweight infants did equally well in either hospital group. While the differences between the two hospital groups for these categories were not statistically significant at the p < 0.05 level, data from the 1958-1960 period substantiate that a marked change occurred in the 3.5-5.5 pounds birthweight category for those infants born in hospitals which developed NICUs. Early data were not available for prenatal care. These findings support the conclusion that, in Houston, NICUs had some impact on neonatal mortality among moderately underweight infants. ^
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Errors in the administration of medication represent a significant loss of medical resources and pose life altering or life threatening risks to patients. This paper considered the question, what impact do Computerized Physician Order Entry (CPOE) systems have on medication errors in the hospital inpatient environment? Previous reviews have examined evidence of the impact of CPOE on medication errors, but have come to ambiguous conclusions as to the impact of CPOE and decision support systems (DSS). Forty-three papers were identified. Thirty-one demonstrated a significant reduction in prescribing error rates for all or some drug types; decreases in minor errors were most often reported. Several studies reported increases in the rate of duplicate orders and failures to remove contraindicated drugs, often attributed to inappropriate design or to an inability to operate the system properly. The evidence on the effectiveness of CPOE to reduce errors in medication administration is compelling though it is limited by modest study sample sizes and designs. ^
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Background: Risky sexual behaviors have been shown to increase the risk of unintended pregnancy and sexually transmitted infections (STIs) among youth. Youth in military families may be especially at risk for engaging in risky sexual behaviors because they are exposed to factors that are unique to the military culture, such as multiple relocations and parental deployment. However, data on sexual behaviors among military-dependent youth are limited and few studies have examined how these factors influence the sexual behaviors among youth. Purpose: The purpose of this dissertation was to estimate the prevalence of risky sexual behaviors among military-dependent youth and to describe how military factors may influence their sexual behaviors. Methods: Youth, aged 15–19 years, who attended a military health facility in the southern United States between June 2011 and September 2011 were recruited to complete a short, paper-based survey (N= 208, males and females) and to participate in an in-depth interview (N = 25, females). For quantitative data, prevalence estimates were computed and chi-square analyses were conducted. Logistic regression analyses were also conducted, adjusting for age, gender, and parents' duty status. For qualitative data, thematic coding of transcribed interviews was performed. Common and unique themes were examined across participants' experiences. Results: Over half of the youth was sexually experienced (53.7%). Parental deployment and number of relocations were significantly associated with having had sex in the past 3 months; however no significant associations were found between these military factors and other sexual behaviors. Although some youth felt that being a military-dependent had negatively impacted their sexual decisions, most believed the military experience had little influence on their sexual decisions. Most youth in military families also perceived having higher parental expectations to avoid risky behaviors, in general, than youth in civilian families. Conclusions: The majority of military-dependent youth are sexually experienced; however, individual and parental factors may have a greater role in sexual initiation among youth than military stressors do. The findings highlight the need for implementation of evidence-based strategies to prevent teen pregnancy and STIs at military installations. Future studies with larger sample sizes are needed to further explore how youth may cope with these military factors and the impact of parental factors on the sexual behaviors of youth.^
Resumo:
Dietary intake is a complex, health-related behavior, and although individual-level theoretical models explain some variation in dietary intake, comprehensive theoretical models such as the ecological framework describe the multiple levels which influence diet-related behaviors. Thus, the ecological framework is a preferred model for designing comprehensive nutrition interventions. While ecological-based nutrition interventions have been described, little work has focused on interventions in the hospital setting. Because hospitals are considered the hallmarks of health, it might seem that hospitals would regularly engage in worksite nutrition promotion; however, recent publications and other anecdotal evidence have indicated otherwise. The first paper of this dissertation systematically reviewed the scientific literature between 1996 and 2012 and identified 13 outcome evaluation trials for hospital-based worksite nutrition interventions. Of these 13 interventions, only one intervention targeted three of the four levels of the ecological framework and no intervention targeted all four levels. Only half of the interventions targeted the physical environment of hospitals, thus warranting more investigation into this specific level of the ecological framework in this setting. ^ A critical type of nutrition-related physical environments is the consumer nutrition environment. Although other tools measure the consumer nutrition environments of stores and restaurants, no tool specifically measured the consumer nutrition environments of hospitals until the CDC developed the Healthy Hospital Environment Scan for Cafeterias, Vending Machines, and Gift Shops (HHES-CVG). The HHES-CVG, a tool which measures the consumer nutrition environments of hospital cafeterias, vending machines, and gifts shops, was released in November 2011, and in the second paper of this dissertation, the reliability of this tool was investigated. Two trained raters visited 39 hospitals across Southern California between February and May 2012, and based on analyses of the raters' findings, the HHES-CVG exhibited strong reliability metrics (inter-observer agreement between 74 and 100%, and an intraclass correlation coefficient of 0.961 for the overall nutrition composite score). Because the HHES-CVG was found to be a reliable tool, the third paper of this dissertation presented HHES-CVG results from the 39 hospitals. Overall, hospitals only scored about one-fourth of the total possible points for the nutrition composite score, indicating that most facilities do not have acceptable consumer nutrition environments. Some of the best practices observed in cafeterias were significantly associated with having a large facility and with having a contracted foodservice operation, but overall nutrition composite score was not associated with any specific facility or operation type. ^ The dissertation concluded that much work is needed in order to improve the consumer nutrition environments of hospitals. Practitioners and healthcare administrators should consider starting with ecological-based interventions addressing all levels including the physical environment.^
Resumo:
Hospitals, like all organizations, have both a mission and a finite supply of resources with which to accomplish that mission. Because the inventory of therapeutic drugs is among the more expensive resources needed by a hospital to achieve its mission, a conceptual model of structure plus process equals outcome posits that adequate emphasis should be placed on optimization of the organization's investment in this important structural resource to provide highest quality outcomes. Therefore emphasis should be placed on the optimization of pharmacy inventory because lowering the financial investment in drug inventory and associated costs increases productive efficiency, a key element of quality. ^ In this study, a post-intervention analysis of a hospital pharmacy inventory management technology implementation at The University of Texas M.D. Anderson Cancer Center was conducted to determine if an intervention which reduced a hospital's financial investment in pharmaceutical inventory provided an opportunity to incrementally optimize the organization's mix of structural resources thereby improving quality of care. The results suggest that hospital pharmacies currently lacking technology to support automated purchasing logistics and perpetual, real-time inventory management for drugs may achieve measurable benefits from the careful implementation of such technology, enabling the hospital to lower its investment in on-hand inventory and, potentially, to reduce overall purchasing expenditures. ^ The importance of these savings to the hospital and potentially to the patient should not be underestimated for their ability to generate funding for previously unfunded public health programs or in their ability to provide financial relief to patients in the form of lower drug costs given the current climate of escalating healthcare costs and tightening reimbursements.^