7 resultados para Hospital Bed Capacity

em DigitalCommons@The Texas Medical Center


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Objective. The study reviewed one year of Texas hospital discharge data and Trauma Registry data for the 22 trauma services regions in Texas to identify regional variations in capacity, process of care and clinical outcomes for trauma patients, and analyze the statistical associations among capacity, process of care, and outcomes. ^ Methods. Cross sectional study design covering one year of state-wide Texas data. Indicators of trauma capacity, trauma care processes, and clinical outcomes were defined and data were collected on each indicator. Descriptive analyses were conducted of regional variations in trauma capacity, process of care, and clinical outcomes at all trauma centers, at Level I and II trauma centers and at Level III and IV trauma centers. Multilevel regression models were performed to test the relations among trauma capacity, process of care, and outcome measures at all trauma centers, at Level I and II trauma centers and at Level III and IV trauma centers while controlling for confounders such as age, gender, race/ethnicity, injury severity, level of trauma centers and urbanization. ^ Results. Significant regional variation was found among the 22 trauma services regions across Texas in trauma capacity, process of care, and clinical outcomes. The regional trauma bed rate, the average staffed bed per 100,000 varied significantly by trauma service region. Pre-hospital trauma care processes were significantly variable by region---EMS time, transfer time, and triage. Clinical outcomes including mortality, hospital and intensive care unit length of stay, and hospital charges also varied significantly by region. In multilevel regression analysis, the average trauma bed rate was significantly related to trauma care processes including ambulance delivery time, transfer time, and triage after controlling for age, gender, race/ethnicity, injury severity, level of trauma centers, and urbanization at all trauma centers. Transfer time only among processes of care was significant with the average trauma bed rate by region at Level III and IV. Also trauma mortality only among outcomes measures was significantly associated with the average trauma bed rate by region at all trauma centers. Hospital charges only among outcomes measures were statistically related to trauma bed rate at Level I and II trauma centers. The effect of confounders on processes and outcomes such as age, gender, race/ethnicity, injury severity, and urbanization was found significantly variable by level of trauma centers. ^ Conclusions. Regional variation in trauma capacity, process, and outcomes in Texas was extensive. Trauma capacity, age, gender, race/ethnicity, injury severity, level of trauma centers and urbanization were significantly associated with trauma process and clinical outcomes depending on level of trauma centers. ^ Key words: regionalized trauma systems, trauma capacity, pre-hospital trauma care, process, trauma outcomes, trauma performance, evaluation measures, regional variations ^

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In 1941 the Texas Legislature appropriated $500,000 to the Board of Regents of the University of Texas to establish a cancer research hospital. The M. D. Anderson Foundation offered to match the appropriation with a grant of an equal sum and to provide a permanent site in Houston. In August, 1942 the Board of Regent of the University and the Trustees of the Foundation signed an agreement to embark on this project. This institution was to be the first one in the medical center, which was incorporated in October, 1945. The Board of Trustees of the Texas Medical Center commissioned a hospital survey to: - Define the needed hospital facilities in the area - Outline an integrated program to meet these needs - Define the facilities to be constructed - Prepare general recommendations for efficient progress The Hospital Study included information about population, hospitals, and other health care and education facilities in Houston and Harris County at that time. It included projected health care needs for future populations, education needs, and facility needs. It also included detailed information on needs for chronic illnesses, a school of public health, and nursing education. This study provides valuable information about the general population and the state of medicine in Houston and Harris County in the 1940s. It gives a unique perspective on the anticipated future as civic leaders looked forward in building the city and region. This document is critical to an understanding of the Texas Medical Center, Houston and medicine as they are today. SECTIONS INCLUDE: Abstract The Abstract was a summary of the 400 page document including general information about the survey area, community medical assets, and current and projected medical needs which the Texas Medical Center should meet. The 123 recommendations were both general (e.g., 12. “That in future planning, the present auxiliary department of the larger hospitals be considered inadequate to carry an added teaching research program of any sizable scope.”) and specific (e.g., 22. That 14.3% of the total acute bed requirement be allotted for obstetric care, reflecting a bed requirement of 522 by 1950, increasing to 1,173 by 1970.”) Section I: Survey Area This section basically addressed the first objective of the survey: “define the needed hospital facilities in the area.” Based on the admission statistics of hospitals, Harris County was included in the survey, with the recognition that growth from out-lying regional areas could occur. Population characteristics and vital statistics were included, with future trends discussed. Each of the hospitals in the area and government and private health organizations, such as the City-County Welfare Board, were documented. Statistics on the facilities use and capacity were given. Eighteen recommendations and observations on the survey area were given. Section II: Community Program This section basically addressed the second objective of the survey: “outline an integrated program to meet these needs.” The information from the Survey Area section formed the basis of the plans for development of the Texas Medical Center. In this section, specific needs, such as what medical specialties were needed, the location and general organization of a medical center, and the academic aspects were outlined. Seventy-four recommendations for these plans were provided. Section III: The Texas Medical Center The third and fourth objectives are addressed. The specific facilities were listed and recommendations were made. Section IV: Special Studies: Chronic Illness The five leading causes of death (heart disease, cancer, “apoplexy”, nephritis, and tuberculosis) were identified and statistics for morbidity and mortality provided. Diagnostic, prevention and care needs were discussed. Recommendations on facilities and other solutions were made. Section IV: Special Studies: School of Public Health An overview of the state of schools of public health in the US was provided. Information on the direction and need of this special school was also provided. Recommendations on development and organization of the proposed school were made. Section IV: Special Studies: Needs and Education Facilities for Nurses Nursing education was connected with hospitals, but the changes to academic nursing programs were discussed. The needs for well-trained nurses in an expanded medical environment were anticipated to result in significant increased demands of these professionals. An overview of the current situation in the survey area and recommendations were provided. Appendix A Maps, tables and charts provide background and statistical information for the previous sections. Appendix B Detailed census data for specific areas of the survey area in the report were included. Sketches of each of the fifteen hospitals and five other health institutions showed historical information, accreditations, staff, available facilities (beds, x-ray, etc.), academic capabilities and financial information.

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This study is a retrospective longitudinal study at Texas Children's Hospital, a 350-bed tertiary level pediatric teaching hospital in Houston, Texas, for the period 1990 to 2006. It measured the incidence and trends of positive pre-employment drug tests among new job applicants At TCH. ^ Over the study period, 16,219 job applicants underwent pre-employment drug screening at TCH. Of these, 330 applicants (2%) tested positive on both the EMIT and GC/MS. After review by the medical review officer, the number of true drug test positive applicants decreased to 126 (0.78%). ^ According to the overall annual positive drug test incidence rates, the highest overall incidence was in 2002 (14.71 per 1000 tests) and the lowest in 2004 (3.17 per 1000 tests). Despite a marked increase in 2002, over the 15-year study period the overall incidence tended to decrease. Incidence rates and trends of other illegal drugs are further discussed in the study. And in general, these incidence rates also decline in the study period. In addition to that, we found the overall, positive drug tests were more common in females than in males (55.5% versus 44.4%). ^

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The 2005 Annual Statement of Community Benefits Standard (ASCBS) and the annual report of the Community Benefits Plan, Summary of Current Hospital Charity Care Policy and Community Benefits, were used to identify various environmental and policy relationships with regard to eligibility for charity care requirements, a component for meeting the nonprofit requirements established by the Texas Legislature for nonprofit tax exemption (Texas Health and Safety Code, §311.04610). ^ Charity care policies are established by the individual hospital (or systems) and are generally defined as rules concerning care provided by the institution without the expectation of payment. This study has been undertaken to provide specific information about the charity care eligibility requirement policies of nonprofit hospitals. These hospitals are the part of the safety net for those persons who are indigent, low-income and uninsured. This study examines nonprofit hospitals by physical location, bed size, religious affiliation, trauma level, disproportionate share, and teaching designations. County information includes population, percentage of residents eligible for Medicaid benefits, ethnic makeup of county residents, poverty level, designation of a hospital district or operators of a public hospital, and the number of nonprofit and for-profit hospitals located in the county. Although this information has been collected by the Texas Department of State Health Services (DSHS), no other analysis has been conducted. ^

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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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Since the tragic events of September, 11 2001 the United States bioterrorism and disaster preparedness has made significant progress; yet, numerous research studies of nationwide hospital emergency response have found alarming shortcomings in surge capacity and training level of health care personnel in responding to bioterrorism incidents. The primary goals of this research were to assess hospital preparedness towards the threat of bioterrorist agents in the Southwest Region of the United States and provide recommendations for its improvement. Since little formal research has been published on the hospital preparedness of Oklahoma, Arizona, Texas and New Mexico, this research study specifically focused on the measurable factors affecting the respective states' resources and level of preparedness, such as funding, surge capacity and preparedness certification status.^ Over 300 citations of peer-reviewed articles and 17 Web sites were reviewed, of which 57 reports met inclusion criteria. The results of the systematic review highlighted key gaps in the existing literature and the key targets for future research, as well as identified strengths and weaknesses of the hospital preparedness in the Southwest states compared to the national average. ^ Based on the conducted research, currently, the Southwest states hospital systems are unable fully meet presidential preparedness mandates for emergency and disaster care: the staffed beds to 1,000 population value fluctuated around 1,5 across the states; funding for the hospital preparedness lags behind hospital costs by millions of dollars; and public health-hospital partnership in bioterrorism preparedness is quite weak as evident in lack of joint exercises and training. However, significant steps towards it are being made, including on-going hospital preparedness certification by the Joint Commission of Health Organization. Variations in preparedness levels among states signify that geographic location might determine a hospital level of bioterrorism preparedness as well, tending to favor bigger states such as Texas.^ Suggested recommendations on improvement of the hospital bioterrorism preparedness are consistent with the existing literature and include establishment and maintenance of solid partnerships between hospitals and public health agencies, conduction of joint exercises and drills for the health care personnel and key partners, improved state and federal funding specific to bioterrorism preparedness objectives, as well as on-going training of the clinical personnel on recognition of the bioterrorism agents.^

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Information technology (IT) in the hospital organization is fast becoming a key asset, particularly in light of recent reform legislation in the United States calling for expanding the role of IT in our health care system. Future payment reductions to hospitals included in current health reform are based on expected improvements in hospital operating efficiency. Since over half of hospital expenses are for labor, improved efficiency in use of labor resources can be critical in meeting this challenge. Policy makers have touted the value of IT investments to improve efficiency in response to payment reductions. ^ This study was the first to directly examine the relationship between electronic health record (EHR) technology and staffing efficiency in hospitals. As the hospital has a myriad of outputs for inpatient and outpatient care, efficiency was measured using an industry standard performance metric – full time equivalent employees per adjusted occupied bed (FTE/AOB). Three hypotheses were tested in this study.^ To operationalize EHR technology adoption, we developed three constructs to model adoption, each of which was tested by separate hypotheses. The first hypothesis that a larger number of EHR applications used by a hospital would be associated with greater staffing efficiency (or lower values of FTE/AOB) was not accepted. Association between staffing efficiency and specific EHR applications was the second hypothesis tested and accepted with some applications showing significant impacts on observed values for FTE/AOB. Finally, the hypothesis that the longer an EHR application was used in a hospital would be associated with greater labor efficiency was not accepted as the model showed few statistically significant relationships to FTE/AOB performance. Generally, there does not appear a strong relationship between EHR usage and improved labor efficiency in hospitals.^ While returns on investment from EHR usage may not come from labor efficiencies, they may be better sought using measures of quality, contribution to an efficient and effective local health care system, and improved customer satisfaction through greater patient throughput.^