Differences in performance for quality of care indicators for acute myocardial infarction (AMI) across various hospital categories in Texas

The study analyzed Hospital Compare data for Medicare Fee-for-service patients at least 65 years of age to determine whether hospital performance for AMI outcome and processes of care measures differ amongst Texas hospitals with respect to ownership status (for profit vs. not-for-profit), academic status (teaching vs. non-teaching) and geographical setting (rural vs. urban). ^ The study found a statistically significant difference between for-profit and not-for-profit hospitals in four process-of-care measures (aspirin at discharge, P=0.028; ACE or ARB inhibitor for LSVD, P=0.048; Smoking cessation advice: P=0.034; outpatients who got aspirin with 24 hours of arrival in the ED, P=0.044). No significant difference in performance was found between COTH-member teaching and non-teaching hospitals for any of the eight process-of-care measures or the two outcome measures for AMI. The study was unable to compare performance based on geographic setting of hospitals due to lack of sufficient data for rural hospitals. ^ The results of the study suggest that for-profit Texas hospitals might be slightly better than not-for –profit hospitals at providing possible heart attack patients with certain processes of care.^

Performance in healthcare organizations: The quality dimension

In the context of a healthcare organization, such as a hospital that provides medical care to its community, performance cannot be measured without special attention to quality. Indeed, quality is as important as finance not only in measuring performance for the organization, but also in securing the organization's viability and competitiveness in the long run.^ Yet quality today is not adequately understood and managed. An inductive framework for integrating finance and quality for purposes of organizational performance measurement as well as strategic planning is proposed in this dissertation. Future areas of research are discussed.^

Quality assurance plan for a vaccine preventable diseases surveillance program

Public health surveillance programs for vaccine preventable diseases (VPD) need functional quality assurance (QA) in order to operate with high quality activities to prevent preventable communicable diseases from spreading in the community. Having a functional QA plan can assure the performance and quality of a program without putting excessive stress on the resources. A functional QA plan acts as a check on the quality of day-to-day activities performed by the VPD surveillance program while also providing data that would be useful for evaluating the program. This study developed a QA plan that involves collection, collation, analysis and reporting of information based on standardized (predetermined) formats and indicators as an integral part of routine work for the vaccine preventable disease surveillance program at the City of Houston Department of Health and Human Services. The QA plan also provides sampling and analysis plans for assessing various QA indicators, as well as recommendations to the Houston Department of Health and Humans Services for implementation of the QA plan. The QA plan developed for VPD surveillance in the City of Houston is intended to be a low cost system that could serve as a template for QA plans as part of other public health programs not only in the city or the nation, but could be adapted for use anywhere across the globe. Having a QA plan for VPD surveillance in the City of Houston would serve well for the funding agencies like the CDC by assuring that the resources are being expended efficiently, while achieving the real goal of positively impacting the health and lives of the recipient/target population. ^

Process evaluation of the Texas occupational safety & health surveillance system

Introduction: The Texas Occupational Safety & Health Surveillance System (TOSHSS) was created to collect, analyze and interpret occupational injury and illness data in order to decrease the impact of occupational injuries within the state of Texas. This process evaluation was performed midway through the 4-year grant to assess the efficiency and effectiveness of the surveillance system’s planning and implementation activities1. ^ Methods: Two evaluation guidelines published by the Centers for Disease Control and Prevention (CDC) were used as the theoretical models for this process evaluation. The Framework for Program Evaluation in Public Health was used to examine the planning and design of TOSHSS using logic models. The Framework for Evaluating Public Health Surveillance Systems was used to examine the implementation of approximately 60 surveillance activities, including uses of the data obtained from the surveillance system. ^ Results/Discussion: TOSHSS planning activities omitted the creation of a scientific advisory committee and specific activities designed to maintain contacts with stakeholders; and proposed activities should be reassessed and aligned with ongoing performance measurement criteria, including the role of collaborators in helping the surveillance system achieve each proposed activity. TOSHSS implementation activities are substantially meeting expectations and received an overall score of 61% for all activities being performed. TOSHSS is considered a surveillance system that is simple, flexible, acceptable, fairly stable, timely, moderately useful, with good data quality and a PVP of 86%. ^ Conclusions: Through the third year of TOSHSS implementation, the surveillance system is has made a considerable contribution to the collection of occupational injury and illness information within the state of Texas. Implementation of the nine recommendations provided under this process evaluation is expected to increase the overall usefulness of the surveillance system and assist TDSHS in reducing occupational fatalities, injuries, and diseases within the state of Texas. ^ 1 Disclaimer: The Texas Occupational Safety and Health Surveillance System is supported by Grant/Cooperative Agreement Number (U60 OH008473-01A1). The content of the current evaluation are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health.^

Quality in healthcare organizations: Its meaning and measurement

This dissertation explores two important aspects of quality in healthcare: its meaning and its measurement. For a better understanding of what quality means, the history of quality in the manufacturing and service industries is reviewed. Concepts that are similar are pointed out as are concepts that are different. The definition introduced by the Institute of Medicine (IOM) for quality in healthcare and the six IOM aims of safety, timeliness, patient-centeredness, effectiveness, efficiency, and equitableness for a high quality healthcare system are adopted. The current activities by various organizations that proclaim improvement in quality or measurement of quality as their goal are reviewed. This is followed by examining what is offered by these organizations in terms of how many of IOM aims they address.^ This dissertation ends by offering a quality measurement framework that satisfies all IOM aims. Operational aspects of the measurement framework are discussed. Future areas of research are also discussed.^

Quality Data is Key to Improving Education

The Data Quality Campaign (DQC) has been focused since 2005 on advocating for states to build robust state longitudinal data systems (SLDS). While states have made great progress in their data infrastructure, and should continue to emphasize this work, t data systems alone will not improve outcomes. It is time for both DQC and states to focus on building capacity to use the information that these systems are producing at every level – from classrooms to state houses. To impact system performance and student achievement, the ingrained culture must be replaced with one that focuses on data use for continuous improvement. The effective use of data to inform decisions, provide transparency, improve the measurement of outcomes, and fuel continuous improvement will not come to fruition unless there is a system wide focus on building capacity around the collection, analysis, dissemination, and use of this data, including through research.

CHARACTERIZATION OF THE COUNT RATE PERFORMANCE AND EVALUATION OF THE EFFECTS OF HIGH COUNT RATES ON MODERN GAMMA CAMERAS

CHARACTERIZATION OF THE COUNT RATE PERFORMANCE AND EVALUATION OF THE EFFECTS OF HIGH COUNT RATES ON MODERN GAMMA CAMERAS Michael Stephen Silosky, B.S. Supervisory Professor: S. Cheenu Kappadath, Ph.D. Evaluation of count rate performance (CRP) is an integral component of gamma camera quality assurance and measurement of system dead time (τ) is important for quantitative SPECT. The CRP of three modern gamma cameras was characterized using established methods (Decay and Dual Source) under a variety of experimental conditions. For the Decay method, input count rate was plotted against observed count rate and fit to the paralyzable detector model (PDM) to estimate τ (Rates method). A novel expression for observed counts as a function of measurement time interval was derived and the observed counts were fit to this expression to estimate τ (Counts method). Correlation and Bland-Altman analysis were performed to assess agreement in estimates of τ between methods. The dependencies of τ on energy window definition and incident energy spectrum were characterized. The Dual Source method was also used to estimate τ and its agreement with the Decay method under identical conditions and the effects of total activity and the ratio of source activities were investigated. Additionally, the effects of count rate on several performance metrics were evaluated. The CRP curves for each system agreed with the PDM at low count rates but deviated substantially at high count rates. Estimates of τ for the paralyzable portion of the CRP curves using the Rates and Counts methods were highly correlated (r=0.999) but with a small (~6%) difference. No significant difference was observed between the highly correlated estimates of τ using the Decay or Dual Source methods under identical experimental conditions (r=0.996). Estimates of τ increased as a power-law function with decreasing ratio of counts in the photopeak to the total counts and linearly with decreasing spectral effective energy. Dual Source method estimates of τ varied as a quadratic with the ratio of the single source to combined source activities and linearly with total activity used across a large range. Image uniformity, spatial resolution, and energy resolution degraded linearly with count rate and image distorting effects were observed. Guidelines for CRP testing and a possible method for the correction of count rate losses for clinical images have been proposed.