Implementation analysis of the Texas Vendor Drug Program

An agency is accountable to a legislative body in the implementation of public policy. It has a responsibility to ensure that the implementation of that policy is consistent with its statutory objectives.^ The analysis of the effectiveness of implementation of the Vendor Drug Program proceeded in the following manner. The federal and state roles and statutes pursuant to the formulation of the Vendor Drug Program were reviewed to determine statutory intent and formal provisions. The translation of these into programmatic details was examined focusing on the factors impacting the implementation process. Lastly, the six conditions outlined by Mazmanian and Sabatier as criteria for effective implementation, were applied to the implementation of the Vendor Drug Program to determine if the implementation was effective in relation to consistency with statutory objectives.^ The implementation of the statutes clearly met four of the six conditions for effective implementation: (1) clear and consistent objectives; (2) a valid causal theory; (3) structured the process to maximize agency and target compliance with the objectives; and (4) had continued support of constituency groups and sovereigns.^ The implementation was basically consistent with the statutory objectives, although the determination of vendor reimbursement has had and continues to have problems. ^

SUPERFUND: AN ANALYSIS OF IMPLEMENTATION FAILURE (CERCLA, HEALTH LAW POLICY)

In December, 1980, following increasing congressional and constituent-interest in problems associated with hazardous waste, the Comprehensive Environmental Recovery, Compensation and Liability Act (CERCLA) was passed. During its development, the legislative initiative was seriously compromised which resulted in a less exhaustive approach than was formerly sought. Still, CERCLA (Superfund) which established, among other things, authority to clean up abandoned waste dumps and to respond to emergencies caused by releases of hazardous substances was welcomed by many as an important initial law critical to the cleanup of the nation's hazardous waste. Expectations raised by passage of this bill were tragically unmet. By the end of four years, only six sites had been declared by the EPA as cleaned. Seemingly, even those determinations were liberal; of the six sites, two were identified subsequently as requiring further cleanup.^ This analysis is focused upon the implementation failure of the Superfund. In light of that focus, discussion encompasses development of linkages between flaws in the legislative language and foreclosure of chances for implementation success. Specification of such linkages is achieved through examination of the legislative initiative, identification of its flaws and characterization of attendant deficits in implementation ability. Subsequent analysis is addressed to how such legislative frailities might have been avoided and to attendant regulatory weaknesses which have contributed to implementation failure. Each of these analyses are accomplished through application of an expanded approach to the backward mapping analytic technique as presented by Elmore. Results and recommendations follow.^ Consideration is devoted to a variety of regulatory issues as well as to those pertinent to legislative and implementation analysis. Problems in assessing legal liability associated with hazardous waste management are presented, as is a detailed review of the legislative development of Superfund, and its initial implementation by Gorsuch's EPA. ^

The interorganizational implementation of state health policy: A network approach

This is an implementation analysis of three consecutive state health policies whose goal was to improve access to maternal and child health services in Texas from 1983 to 1986. Of particular interest is the choice of the unit of analysis, the policy subsystem, and the network approach to analysis. The network approach analyzes and compares the structure and decision process of six policy subsystems in order to explain program performance. Both changes in state health policy as well as differences in implementation contexts explain evolution of the program administrative and service unit, the policy subsystem. And, in turn, the evolution of the policy subsystem explains changes in program performance. ^

THE IMPLEMENTATION OF FEDERAL FAMILY PLANNING POLICY: AN ANALYSIS OF FACTORS AFFECTING STATE EXPENDITURES, FISCAL YEARS 1976-1981 (WOMEN, BUDGET, POPULATION)

The purpose of this study was to analyze the implementation of national family planning policy in the United States, which was embedded in four separate statutes during the period of study, Fiscal Years 1976-81. The design of the study utilized a modification of the Sabatier and Mazmanian framework for policy analysis, which defined implementation as the carrying out of statutory policy. The study was divided into two phases. The first part of the study compared the implementation of family planning policy by each of the pertinent statutes. The second part of the study identified factors that were associated with implementation of federal family planning policy within the context of block grants.^ Implemention was measured here by federal dollars spent for family planning, adjusted for the size of the respective state target populations. Expenditure data were collected from the Alan Guttmacher Institute and from each of the federal agencies having administrative authority for the four pertinent statutes, respectively. Data from the former were used for most of the analysis because they were more complete and more reliable.^ The first phase of the study tested the hypothesis that the coherence of a statute is directly related to effective implementation. Equity in the distribution of funds to the states was used to operationalize effective implementation. To a large extent, the results of the analysis supported the hypothesis. In addition to their theoretical significance, these findings were also significant for policymakers insofar they demonstrated the effectiveness of categorical legislation in implementing desired health policy.^ Given the current and historically intermittent emphasis on more state and less federal decision-making in health and human serives, the second phase of the study focused on state level factors that were associated with expenditures of social service block grant funds for family planning. Using the Sabatier-Mazmanian implementation model as a framework, many factors were tested. Those factors showing the strongest conceptual and statistical relationship to the dependent variable were used to construct a statistical model. Using multivariable regression analysis, this model was applied cross-sectionally to each of the years of the study. The most striking finding here was that the dominant determinants of the state spending varied for each year of the study (Fiscal Years 1976-1981). The significance of these results was that they provided empirical support of current implementation theory, showing that the dominant determinants of implementation vary greatly over time. ^

Implementation of active surveillance cultures and associated infection control practices for the reduction of methicillin resistant Staphylococcus aureus in the healthcare setting: An interrupted time series analysis

OBJECTIVE. To determine the effectiveness of active surveillance cultures and associated infection control practices on the incidence of methicillin resistant Staphylococcus aureus (MRSA) in the acute care setting. DESIGN. A historical analysis of existing clinical data utilizing an interrupted time series design. ^ SETTING AND PARTICIPANTS. Patients admitted to a 260-bed tertiary care facility in Houston, TX between January 2005 through December 2010. ^ INTERVENTION. Infection control practices, including enhanced barrier precautions, compulsive hand hygiene, disinfection and environmental cleaning, and executive ownership and education, were simultaneously introduced during a 5-month intervention implementation period culminating with the implementation of active surveillance screening. Beginning June 2007, all high risk patients were cultured for MRSA nasal carriage within 48 hours of admission. Segmented Poisson regression was used to test the significance of the difference in incidence of healthcare-associated MRSA during the 29-month pre-intervention period compared to the 43-month post-intervention period. ^ RESULTS. A total of 9,957 of 11,095 high-risk patients (89.7%) were screened for MRSA carriage during the intervention period. Active surveillance cultures identified 1,330 MRSA-positive patients (13.4%) contributing to an admission prevalence of 17.5% in high-risk patients. The mean rate of healthcare-associated MRSA infection and colonization decreased from 1.1 per 1,000 patient-days in the pre-intervention period to 0.36 per 1,000 patient-days in the post-intervention period (P<0.001). The effect of the intervention in association with the percentage of S. aureus isolates susceptible to oxicillin were shown to be statistically significantly associated with the incidence of MRSA infection and colonization (IRR = 0.50, 95% CI = 0.31-0.80 and IRR = 0.004, 95% CI = 0.00003-0.40, respectively). ^ CONCLUSIONS. It can be concluded that aggressively targeting patients at high risk for colonization of MRSA with active surveillance cultures and associated infection control practices as part of a multifaceted, hospital-wide intervention is effective in reducing the incidence of healthcare-associated MRSA.^

BENCHMARKING AND IMPLEMENTATION OF A NEW INDEPENDENT MONTE CARLO DOSE CALCULATION QUALITY ASSURANCE AUDIT TOOL FOR CLINICAL TRIALS

Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

Design and implementation of a multicriteria medical decision support system for diagnosis and treatment

Health care providers face the problem of trying to make decisions with inadequate information and also with an overload of (often contradictory) information. Physicians often choose treatment long before they know which disease is present. Indeed, uncertainty is intrinsic to the practice of medicine. Decision analysis can help physicians structure and work through a medical decision problem, and can provide reassurance that decisions are rational and consistent with the beliefs and preferences of other physicians and patients. ^ The primary purpose of this research project is to develop the theory, methods, techniques and tools necessary for designing and implementing a system to support solving medical decision problems. A case study involving “abdominal pain” serves as a prototype for implementing the system. The research, however, focuses on a generic class of problems and aims at covering theoretical as well as practical aspects of the system developed. ^ The main contributions of this research are: (1) bridging the gap between the statistical approach and the knowledge-based (expert) approach to medical decision making; (2) linking a collection of methods, techniques and tools together to allow for the design of a medical decision support system, based on a framework that involves the Analytic Network Process (ANP), the generalization of the Analytic Hierarchy Process (AHP) to dependence and feedback, for problems involving diagnosis and treatment; (3) enhancing the representation and manipulation of uncertainty in the ANP framework by incorporating group consensus weights; and (4) developing a computer program to assist in the implementation of the system. ^

Application of stellar photometry to the analysis of microarray images

Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

A survey of the implementation status of environmental management systems in U.S. colleges and universities, and, An environmental management system implementation model for U.S. colleges and universities

A census of 925 U.S. colleges and universities offering masters and doctorate degrees was conducted in order to study the number of elements of an environmental management system as defined by ISO 14001 possessed by small, medium and large institutions. A 30% response rate was received with 273 responses included in the final data analysis. Overall, the number of ISO 14001 elements implemented among the 273 institutions ranged from 0 to 16, with a median of 12. There was no significant association between the number of elements implemented among institutions and the size of the institution (p = 0.18; Kruskal-Wallis test) or among USEPA regions (p = 0.12; Kruskal-Wallis test). The proportion of U.S. colleges and universities that reported having implemented a structured, comprehensive environmental management system, defined by answering yes to all 16 elements, was 10% (95% C.I. 6.6%–14.1%); however 38% (95% C.I. 32.0%–43.8%) reported that they had implemented a structured, comprehensive environmental management system, while 30.0% (95% C.I. 24.7%–35.9%) are planning to implement a comprehensive environmental management system within the next five years. Stratified analyses were performed by institution size, Carnegie Classification and job title. ^ The Osnabruck model, and another under development by the South Carolina Sustainable Universities Initiative, are the only two environmental management system models that have been proposed specifically for colleges and universities, although several guides are now available. The Environmental Management System Implementation Model for U.S. Colleges and Universities developed is an adaptation of the ISO 14001 standard and USEPA recommendations and has been tailored to U.S. colleges and universities for use in streamlining the implementation process. In using this implementation model created for the U.S. research and academic setting, it is hoped that these highly specialized institutions will be provided with a clearer and more cost-effective path towards the implementation of an EMS and greater compliance with local, state and federal environmental legislation. ^

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

The Texas driver responsibility program: A preliminary analysis of the impact on impaired driving and trauma system funding

Objective. In 2003, the State of Texas instituted the Driver Responsibility Program (TDRP), a program consisting of a driving infraction point system coupled with a series of graded fines and annual surcharges for specific traffic violations such as driving while intoxicated (DWI). Approximately half of the revenues generated are earmarked to be disbursed to the state's trauma system to cover uncompensated trauma care costs. This study examined initial program implementation, the impact of trauma system funding, and initial impact on impaired driving knowledge, attitudes and behaviors. A model for targeted media campaigns to improve the program's deterrence effects was developed. ^ Methods. Data from two independent driver survey samples (conducted in 1999 and 2005), department of public safety records, state health department data and a state auditor's report were used to evaluate the program's initial implementation, impact and outcome with respect to drivers' impaired driving knowledge, attitudes and behavior (based on constructs of social cognitive theory) and hospital uncompensated trauma care funding. Survey results were used to develop a regression model of high risk drivers who should be targeted to improve program outcome with respect to deterring impaired driving. ^ Results. Low driver compliance with fee payment (28%) and program implementation problems were associated with lower surcharge revenues in the first two years ($59.5 million versus $525 million predicted). Program revenue distribution to trauma hospitals was associated with a 16% increase in designated trauma centers. Survey data demonstrated that only 28% of drivers are aware of the TDRP and that there has been no initial impact on impaired driving behavior. Logistical regression modeling suggested that target media campaigns highlighting the likelihood of DWI detection by law enforcement and the increased surcharges associated with the TDRP are required to deter impaired driving. ^ Conclusions. Although the TDRP raised nearly $60 million in surcharge revenue for the Texas trauma system over the first two years, this study did not find evidence of a change in impaired driving knowledge, attitudes or behaviors from 1999 to 2005. Further research is required to measure whether the program is associated with decreased alcohol-related traffic fatalities. ^

Analysis of a disaster medical track for the Certificate in Emergency Management and Preparedness Program at the University of Texas at Dallas

Since the tragic events of September 11, 2001, the United States has engaged in building the infrastructure and developing the expertise necessary to protect its borders and its citizens from further attacks against its homeland. One approach has been the development of academic courses to educate individuals on the nature and dangers of subversive attacks and to prepare them to respond to attacks and other large-scale emergencies in their roles as working professionals, participating members of their communities, and collaborators with first responders. An initial review of the literature failed to reveal any university-based emergency management courses or programs with a disaster medical component, despite the public health significance and need for such programs. In the Fall of 2003, The School of Management at The University of Texas at Dallas introduced a continuing education Certificate in Emergency Management and Preparedness Program. This thesis will (1) describe the development and implementation of a new Disaster Medical Track as a component of this Certificate in Emergency Management and Preparedness Program, (2) analyze the need for and effectiveness of this Disaster Medical Track, and (3) propose improvements in the track based on this analysis. ^

Health care policy analysis of Medicaid's early and periodic screening, diagnosis, and treatment (EPSDT) benefit in Colorado

The purpose of this thesis is to identify "best practice" recommendations for successful implementation of the EPSDT outreach program at Memorial Health System's Hospital for Children in Colorado Springs through a policy analysis of Medicaid EPSDT services in Colorado. A successful program at Memorial will increase education and awareness of EPSDT services, enrollment, and access to and utilization of health care services for eligible children. Methodology utilized in this study included questionnaires designed for the EPSDT contract administrator and outreach coordinators/workers; analysis of current federal and state policies; and studies conducted at the federal and state level, and by various advocacy groups. The need for this analysis of EPSDT came about in part through an awareness of increasingly high numbers of children in poverty and who are uninsured. Though the percentage of children living in poverty in Colorado is slightly below the national average (see Table 2), according to data analyzed by The Annie E. Casey Foundation, the percentage of children (0-18) living in poverty in Colorado increased from 10% in 2000 to 16% in 2006, a dramatic increase of 60% surpassed by only one other state in the nation (The Annie E. Casey Foundation, 2008). By comparison, the U.S. percentage of children in poverty during the same time frame rose from 17% to 18% (The Annie E. Casey Foundation, 2008). What kind of health care services are available to this vulnerable and growing group of Coloradans, and what are the barriers that affect their enrollment in, access to and utilization of these health care services? Barriers identified included difficulty with the application process; system and process issues; a lack of providers; and a lack of awareness and knowledge of EPSDT. Fiscal restraints and legislation at the federal and state level are also barriers to increasing enrollment and access to services. Outreach services are a critical component of providing EPSDT services, and there were several recommendations regarding outreach and case management that will benefit the program in the future. Through this analysis and identification of a broad range of barriers, a clearer picture emerged of current challenges within the EPSDT program as well as a broad range of strategies and recommendations to address these challenges. Through increased education and advocacy for EPSDT and the services it encompasses; stronger collaboration and cooperation between all groups involved, including providing a Medical Home for all eligible children; and new legislation putting more money and focus on comprehensive health care for low-income uninsured children; enrollment, access to and utilization of developmentally appropriate and quality health care services can be achieved. ^

A qualitative analysis of leadership styles and the selection of quality improvement in primary care practice

In the Practice Change Model, physicians act as key stakeholders, people who have both an investment in the practice and the capacity to influence how the practice performs. This leadership role is critical to the development and change of the practice. Leadership roles and effectiveness are an important factor in quality improvement in primary care practices.^ The study conducted involved a comparative case study analysis to identify leadership roles and the relationship between leadership roles and the number and type of quality improvement strategies adopted during a Practice Change Model-based intervention study. The research utilized secondary data from four primary care practices with various leadership styles. The practices are located in the San Antonio region and serve a large Hispanic population. The data was collected by two ABC Project Facilitators from each practice during a 12-month period including Key Informant Interviews (all staff members), MAP (Multi-method Assessment Process), and Practice Facilitation field notes. This data was used to evaluate leadership styles, management within the practice, and intervention tools that were implemented. The chief steps will be (1) to analyze if the leader-member relations contribute to the type of quality improvement strategy or strategies selected (2) to investigate if leader-position power contributes to the number of strategies selected and the type of strategy selected (3) and to explore whether the task structure varies across the four primary care practices.^ The research found that involving more members of the clinic staff in decision-making, building bridges between organizational staff and clinical staff, and task structure are all associated with the direct influence on the number and type of quality improvement strategies implemented in primary care practice.^ Although this research only investigated leadership styles of four different practices, it will offer future guidance on how to establish the priorities and implementation of quality improvement strategies that will have the greatest impact on patient care improvement. ^

Evaluation of the association between cryptosporidiosis outbreaks and two interactive water fountain parks: Epidemiologic analysis and implications for public health

Background. A community-wide outbreak of cryptosporidiosis occurred in Dallas County during the summer of 2008. A subset of cases occurring with onset of illness within a 2 week interval was epidemiologically linked to 2 neighborhood interactive water fountain parks. ^ Methods. A case control study was conducted to evaluate risk factors associated with developing illness with cryptosporidiosis from the fountain parks. Cases were selected from a line list from the epidemiological study. The selection for the controls was either healthy family members or a daycare center nearby. Cases and controls were not matched. ^ Results. Interviews were completed for 44 fountain park attendees who met case definition and 54 community controls. Twenty-seven percent (27.3%) of the cases and 13.0% of the controls were between the ages of 0–4 years. Thirty-nine percent (38.6%) of the cases and 24.1% of the controls were between the ages of 5–13 years. Fourteen percent (13.6%) of the cases and 33.3% of the controls were between the ages of 14–31 years. Twenty percent (20.5%) of the cases and 29.6% of the controls were between the ages of 32–63 years. 47.7% of the cases and 42.6% of the controls were males. Fountain park attendees who reported having been splashed in the face with water were 10 times more likely to become ill than controls (OR = 10.0, 95% CI = 2.8–35.1). Persons who reported having swallowed water from the interactive fountains were 34 times more likely to become ill than controls (OR = 34.3, 95%CI = 9.3–125.7). ^ Conclusion. Prompt reporting of cases, identification of outbreak sources, and immediate implementation of remediation measures were critical in curtailing further transmission from these particular sites through the remainder of the season. This investigation underscores the potential for cryptosporidiosis outbreaks to occur in interactive fountain parks, and the need for enhanced preventive measures in these settings. Education of the public regarding avoidance of behaviors such as drinking water from interactive fountains is also an important component of public health prevention efforts. ^