NEW TOOLS FOR MONITORING GAMMA CAMERA UNIFORMITY

Detector uniformity is a fundamental performance characteristic of all modern gamma camera systems, and ensuring a stable, uniform detector response is critical for maintaining clinical images that are free of artifact. For these reasons, the assessment of detector uniformity is one of the most common activities associated with a successful clinical quality assurance program in gamma camera imaging. The evaluation of this parameter, however, is often unclear because it is highly dependent upon acquisition conditions, reviewer expertise, and the application of somewhat arbitrary limits that do not characterize the spatial location of the non-uniformities. Furthermore, as the goal of any robust quality control program is the determination of significant deviations from standard or baseline conditions, clinicians and vendors often neglect the temporal nature of detector degradation (1). This thesis describes the development and testing of new methods for monitoring detector uniformity. These techniques provide more quantitative, sensitive, and specific feedback to the reviewer so that he or she may be better equipped to identify performance degradation prior to its manifestation in clinical images. The methods exploit the temporal nature of detector degradation and spatially segment distinct regions-of-non-uniformity using multi-resolution decomposition. These techniques were tested on synthetic phantom data using different degradation functions, as well as on experimentally acquired time series floods with induced, progressively worsening defects present within the field-of-view. The sensitivity of conventional, global figures-of-merit for detecting changes in uniformity was evaluated and compared to these new image-space techniques. The image-space algorithms provide a reproducible means of detecting regions-of-non-uniformity prior to any single flood image’s having a NEMA uniformity value in excess of 5%. The sensitivity of these image-space algorithms was found to depend on the size and magnitude of the non-uniformities, as well as on the nature of the cause of the non-uniform region. A trend analysis of the conventional figures-of-merit demonstrated their sensitivity to shifts in detector uniformity. The image-space algorithms are computationally efficient. Therefore, the image-space algorithms should be used concomitantly with the trending of the global figures-of-merit in order to provide the reviewer with a richer assessment of gamma camera detector uniformity characteristics.

Development of automated image analysis tools for verification of radiotherapy field accuracy with an electronic portal imaging device

The successful management of cancer with radiation relies on the accurate deposition of a prescribed dose to a prescribed anatomical volume within the patient. Treatment set-up errors are inevitable because the alignment of field shaping devices with the patient must be repeated daily up to eighty times during the course of a fractionated radiotherapy treatment. With the invention of electronic portal imaging devices (EPIDs), patient's portal images can be visualized daily in real-time after only a small fraction of the radiation dose has been delivered to each treatment field. However, the accuracy of human visual evaluation of low-contrast portal images has been found to be inadequate. The goal of this research is to develop automated image analysis tools to detect both treatment field shape errors and patient anatomy placement errors with an EPID. A moments method has been developed to align treatment field images to compensate for lack of repositioning precision of the image detector. A figure of merit has also been established to verify the shape and rotation of the treatment fields. Following proper alignment of treatment field boundaries, a cross-correlation method has been developed to detect shifts of the patient's anatomy relative to the treatment field boundary. Phantom studies showed that the moments method aligned the radiation fields to within 0.5mm of translation and 0.5$\sp\circ$ of rotation and that the cross-correlation method aligned anatomical structures inside the radiation field to within 1 mm of translation and 1$\sp\circ$ of rotation. A new procedure of generating and using digitally reconstructed radiographs (DRRs) at megavoltage energies as reference images was also investigated. The procedure allowed a direct comparison between a designed treatment portal and the actual patient setup positions detected by an EPID. Phantom studies confirmed the feasibility of the methodology. Both the moments method and the cross-correlation technique were implemented within an experimental radiotherapy picture archival and communication system (RT-PACS) and were used clinically to evaluate the setup variability of two groups of cancer patients treated with and without an alpha-cradle immobilization aid. The tools developed in this project have proven to be very effective and have played an important role in detecting patient alignment errors and field-shape errors in treatment fields formed by a multileaf collimator (MLC). ^

The utility of rapid participatory appraisal for community assessment, diagnosis, and policy development

The selection of a model to guide the understanding and resolution of community problems is an important issue relating to the foundation of public health practice: assessment, policy development, and assurance. Many assessment models produce a diagnosis of community weaknesses, but fail to promote planning and interventions. Rapid Participatory Appraisal (RPA) is a participatory action research model which regards assessment as the first step in the problem solving process, and claims to achieve assessment and policy development within limited resources of time and money. Literature documenting the fulfillment of these claims, and thereby supporting the utility of the model, is relatively sparse and difficult to obtain. Very few articles discuss the changes resulting from RPA assessments in urban areas, and those that do describe studies conducted outside the U.S.A. ^ This study examines the utility of the RPA model and its underlying theories: systems theory, grounded theory, and principles of participatory change, as illustrated by the case study of a community assessment conducted for the Texas Diabetes Institute (TDI), San Antonio, Texas, and subsequent outcomes. Diabetes has a high prevalence and is a major issue in San Antonio. Faculty and students conducted the assessment by informal collaboration between two nursing and public health assessment courses, providing practical student experiences. The study area was large, and the flexibility of the model tested by its use in contiguous sub-regions, reanalyzing aggregated results for the study area. Official TDI reports, and a mail survey of agency employees, described policy development resulting from community diagnoses revealed by the assessment. ^ The RPA model met the criteria for utility from the perspectives of merit, worth, efficiency, and effectiveness. The RPA model best met the agencies' criteria (merit), met the data needs of TDI in this particular situation (worth), provided valid results within budget, time, and personnel constraints (efficiency), and stimulated policy development by TDI (effectiveness). ^ The RPA model appears to have utility for community assessment, diagnosis, and policy development in circumstances similar to the TDI diabetes study. ^

For-profit business safety interventions: A systematic, descriptive review of the literature

The purpose of this research was to determine if principles from organizational theory could be used as a framework to compare and contrast safety interventions developed by for-profit industry for the time period 1986–1996. A literature search of electronic databases and manual search of journals and local university libraries' book stacks was conducted for safety interventions developed by for-profit businesses. To maintain a constant regulatory environment, the business sectors of nuclear power, aviation and non-profits were excluded. Safety intervention evaluations were screened for scientific merit. Leavitt's model from organization theory was updated to include safety climate and renamed the Updated Leavitt's Model. In all, 8000 safety citations were retrieved, 525 met the inclusion criteria, 255 met the organizational safety intervention criteria, and 50 met the scientific merit criteria. Most came from non-public health journals. These 50 were categorized by the Updated Leavitt's Model according to where within the organizational structure the intervention took place. Evidence tables were constructed for descriptive comparison. The interventions clustered in the areas of social structure, safety climate, the interaction between social structure and participants, and the interaction between technology and participants. No interventions were found in the interactions between social structure and technology, goals and technology, or participants and goals. Despite the scientific merit criteria, many still had significant study design weaknesses. Five interventions tested for statistical significance but none of the interventions commented on the power of their study. Empiric studies based on safety climate theorems had the most rigorous designs. There was an attempt in these studies to address randomization amongst subjects to avoid bias. This work highlights the utility of using the Updated Leavitt's Model, a model from organizational theory, as a framework when comparing safety interventions. This work also highlights the need for better study design of future trials of safety interventions. ^

A health disparities perspective on developing emerging infectious disease preparedness

A systematic review of the literature yielded 10 articles that explored the interaction between race/ethnicity, citizenship, socioeconomic status, and health literacy domains with respect to preparedness agenda development. Current emerging infectious disease (EID) preparedness plans do not adequately address the needs of vulnerable populations for the events before, during, and after an epidemic. Central to the disadvantage of most vulnerable populations are various health disparity domains that persist as barriers for individuals and communities alike to engage in preparedness efforts. Seven out of the ten articles discussed the importance of including health disparity domains in preparedness policy. Two proposed frameworks for an emerging infectious disease framework that considers health disparities are presented in this study. ^ Framework 1 is beneficial for the evaluation phase after a disaster has struck and preparedness efforts have been initiated. It considers several existing disparities and remediation strategies at the individual, community, and system levels to reach adequate restructuring of preparedness aims. Framework 2 serves as a "how to" carry out preparedness during a disaster event. It is a revision of a framework proposed by Blumenshine et al. (2008) and explores those characteristics central to pandemic preparedness plan development/deployment. Although two frameworks were devised, no one framework will adequately address the needs of vulnerable populations during an epidemic. However, the two frameworks propose to demonstrate the inclusion of important health disparity domains in preparedness plan development. ^ The National Consensus Panel for Emergency Preparedness and Cultural Diversity has released guidelines that are considered the leading strategies necessary to reorient preparedness infrastructure. In order for vulnerable populations to benefit from ample protection during a disaster, inclusion of health disparity domains in the development phases of preparedness must occur prior to full deployment in communities. Although "promising practices" and other methods at the frontier of exploring these multidimensional constraints has entered the research arena, new studies on adequate preparedness merit further investigation and support.^

The role of a nursing home administrator's education in influencing quality of care in US nursing homes

Nursing home literature links poor management practices to poor quality of care and resident outcomes. Since Nursing Home Administrators (NHAs) require an array of skills to perform their role, it is important to explore what makes a NHA effective. This research fills a gap in the literature and provides a possible option to improve the quality of care in nursing homes. Purpose of the study. The study examines whether NHAs with advanced education (defined as a Masters degree or more) are associated with better quality of care in licensed nursing homes (NHs). Design and Methods. Data was derived from the CDC’s 2004 National Nursing Home Survey, which is a representative sample of NHs across the US. A Donabedian- inspired structure-process-outcomes study model was created to explain how education relates to quality of care. Quality of care was defined as onsite oral care, employee influenza vaccination rates and staff recognition programs. Statistical analyses included multivariate logistic regression; covariates included facility-level variables used in similar peer-reviewed research but also included select measures from the Area Resource File to control for county-level factors. Results. Descriptive and analytical analyses confirm that NHAs with a Bachelor’s degree, Associate degree or high school diploma perform less well than NHAs with a Masters degree or more. NHAs with advanced education are more likely to have onsite dental care and recognition programs for staff than NHAs with a Bachelor’s degree (or less). Also NHAs with less than graduate education are more likely to provide off-site dental care. Employee vaccination rates are not impacted by education. Adding certification, tenure or years of experience to a NHA with advanced education gives them an advantage. In fact, certification and experience alone do not have a positive relationship to care indicators; however adding these to advanced education produces a significant result. Implications. This research provides preliminary evidence that advanced education for the NHA is associated with better quality of care. If future research can confirm these findings, there is merit in revisiting the qualifications. Education can be a legitimate option to support quality improvement efforts in US nursing homes. ^

HIV prevalence and contextual risk-factors among injection drug users in Harris County, Texas

Injection drug use is the third most frequent risk factor for new HIV infections in the United States. A dual mode of exposure: unsafe drug using practices and risky sexual behaviors underlies injection drug users' (IDUs) risk for HIV infection. This research study aims to characterize patterns of drug use and sexual behaviors and to examine the social contexts associated with risk behaviors among a sample of injection drug users. ^ This cross-sectional study includes 523 eligible injection drug users from Houston, Texas, recruited into the 2009 National HIV Behavioral Surveillance project. Three separate set of analyses were carried out. First, using latent class analysis (LCA) and maximum likelihood we identified classes of behavior describing levels of HIV risk, from nine drug and sexual behaviors. Second, eight separate multivariable regression models were built to examine the odds of reporting a given risk behavior. We constructed the most parsimonious multivariable model using a manual backward stepwise process. Third, we examined whether HIV serostatus knowledge (self-reported positive, negative, or unknown serostatus) is associated with drug use and sexual HIV risk behaviors. ^ Participants were mostly male, older, and non-Hispanic Black. Forty-two percent of our sample had behaviors putting them at high risk, 25% at moderate risk, and 33% at low risk for HIV infection. Individuals in the High-risk group had the highest probability of risky behaviors, categorized as almost always sharing needles (0.93), seldom using condoms (0.10), reporting recent exchange sex partners (0.90), and practicing anal sex (0.34). We observed that unsafe injecting practices were associated with high risk sexual behaviors. IDUs who shared needles had higher odds of having anal sex (OR=2.89, 95%CI: 1.69-4.92) and unprotected sex (OR=2.66, 95%CI: 1.38-5.10) at last sex. Additionally, homelessness was associated with needle sharing (OR=2.24, 95% CI: 1.34-3.76) and cocaine use was associated with multiple sex partners (OR=1.82, 95% CI: 1.07-3.11). Furthermore, twenty-one percent of the sample was unaware of their HIV serostatus. The three groups were not different from each other in terms of drug-use behaviors: always using a new sterile needle, or in sharing needles or drug preparation equipment. However, IDUs unaware of their HIV serostatus were 33% more likely to report having more than three sexual partners in the past 12 months; 45% more likely to report to have unprotected sex and 85% more likely to use drug and or alcohol during or before at last sex compared to HIV-positive IDUs. ^ This analysis underscores the merit of LCA approach to empirically categorize injection drug users into distinct classes and identify their risk pattern using multiple indicators and our results show considerable overlap of high risk sexual and drug use behaviors among the high-risk class members. The observed clustering pattern of drug and sexual risk behavior among this population confirms that injection drug users do not represent a homogeneous population in terms of HIV risk. These findings will help develop tailored prevention programs.^

Commentary on "Alternative Strategies for Identifying High-Performing Charter Schools in Texas"

In the last few years policy makers and practitioners nationally have shown much interest in identifying, recognizing, and replicating successful charter schools, many of which are showing that they can educate low-income and otherwise at-risk students remarkably well. However past efforts to identify high performing schools have been problematic. Using these systematic, rigorous value-added methods, the authors identify 44 Open Enrollment charter schools that merit a “high-performer” rating. Nearly all of those campuses identified serve a disadvantaged student population. The article also finds that most of those high performers are highly cost-effective, earning high ratings on the cost-efficiency measures. The authors argue for more widespread use of value-added modeling in the state accountability system. The approach taken to identifying high-performers is sensible and fair, but any formulaic approach to school labels comes with some limitations.