Financial performance drivers and strategic control: The case of cancer treatment centers

Strategic control is defined as the use of qualitative and quantitative tools for the evaluation of strategic organizational performance. Most research in strategic planning has focused on strategy formulation and implementation, but little work has been done on strategic performance evaluation particularly in the area of cancer research. The objective of this study was to identify strategic control approaches and financial performance metrics used by major cancer centers in the country as an initial step in expanding the theory and practice behind strategic organizational performance. Focusing on hospitals which share similar mandate and resource constraints was expected to improve measurement precision. The results indicate that most cancer centers use a wide selection of evaluation tools, but sophisticated analytical approaches were less common. In addition, there was evidence that high-performing centers tend to invest a larger degree of resources in the area of strategic performance analysis than centers showing lower financial results. The conclusions point to the need for incorporating higher degree of analytical power in order to improve the tracking of strategic performance. This study is one of the first to concentrate in the area of strategic control.^

A comparative analysis of CHIP Perinatal policy in twelve states

The purpose of this comparative analysis of CHIP Perinatal policy (42 CFR § 457) was to provide a basis for understanding the variation in policy outputs across the twelve states that, as of June 2007, implemented the Unborn Child rule. This Department of Health and Human Services regulation expanded in 2002 the definition of “child” to include the period from conception to birth, allowing states to consider an unborn child a “targeted low-income child” and therefore eligible for SCHIP coverage. ^ Specific study aims were to (1) describe typologically the structural and contextual features of the twelve states that adopted a CHIP Perinatal policy; (2) describe and differentiate among the various designs of CHIP Perinatal policy implemented in the states; and (3) develop a conceptual model that links the structural and contextual features of the adopting states to differences in the forms the policy assumed, once it was implemented. ^ Secondary data were collected from publicly available information sources to describe characteristics of states’ political system, health system, economic system, sociodemographic context and implemented policy attributes. I posited that socio-demographic differences, political system differences and health system differences would directly account for the observed differences in policy output among the states. ^ Exploratory data analysis techniques, which included median polishing and multidimensional scaling, were employed to identify compelling patterns in the data. Scaled results across model components showed that economic system was most closely related to policy output, followed by health system. Political system and socio-demographic characteristics were shown to be weakly associated with policy output. Goodness-of-fit measures for MDS solutions implemented across states and model components, in one- and two-dimensions, were very good. ^ This comparative policy analysis of twelve states that adopted and implemented HHS Regulation 42 C.F.R. § 457 contributes to existing knowledge in three areas: CHIP Perinatal policy, public health policy and policy sciences. First, the framework allows for the identification of CHIP Perinatal program design possibilities and provides a basis for future studies that evaluate policy impact or performance. Second, studies of policy determinants are not well represented in the health policy literature. Thus, this study contributes to the development of the literature in public health policy. Finally, the conceptual framework for policy determinants developed in this study suggests new ways for policy makers and practitioners to frame policy arguments, encouraging policy change or reform. ^

The effect of triage team on time-in-department in a pediatric emergency department

Objective. To determine whether the use of a triage team would reduce the average time-in-department in a pediatric emergency department by 25%.^ Methods. A triage team consisting of a physician, a nurse, and a nurse's assistant initiated work-ups and saw patients who required minimal lab work-up and were likely to be discharged. Study days were randomized. Our inclusion criteria were all children seen in the emergency center between 6p and 2a Monday-Friday. Our exclusion criteria included resuscitations, inpatient-inpatient transfers, left without being seen, leaving against medical advice, any child seen outside of 6p-2am Monday-Friday and on the weekends. A Pearson-Chi square was used for comparison of the two groups for heterogeneity. For the time-in-department analysis, we performed a 2 sided t-test with a set alpha of 0.05 using Mann Whitney U looking for differences in time-in-department based on acuity level, disposition, and acuity level stratified by disposition. ^ Results. Among urgent and non-urgent patients, we found a statistically significant decrease in time-in-department in a pediatric emergency department. Urgent patients had a time-in-department that was 51 minutes shorter than patients seen on non-triage team days (p=0.007), which represents a 14% decrease in time-in-department. Non-urgent patients seen on triage team days had a time-in-department that was 24 minutes shorter than non-urgent patients seen on non-triage team days (p=0.009). From the disposition perspective, discharged patients seen on triage team days had a shorter time-in-department of 28 minutes as compared to those seen on non-triage team days (p=0.012). ^ Conclusion. Overall, there was a trend towards decreased time-in-department of 19 minutes (5.9% decrease) during triage team times. There was a statistically significant decrease in the time-in-department among urgent patients of 51 minutes (13.9% decrease) and among discharged patients of 28 minutes (8.4% decrease). Urgent care patients make up nearly a quarter of the emergency patient population and decreasing their time-in-department would likely make a significant impact on overall emergency flow.^

Employment outcomes in liver transplant recipients: A policy analysis

Liver transplantation is a widely accepted treatment for end stage liver disease. Research has shown that people with end-stage liver disease experience improved survival and health-related quality of life after transplantation. However, the unemployment rate among liver transplant recipients remains high. The reasons for this were the subject of a study that was used as the primary dataset for this policy analysis. According to the primary data and background supporting data, many transplant recipients remain unemployed for fear of losing needed healthcare and disability benefits. When employment is considered as a health outcome, it is important in an era of evidence based medicine to ensure that healthcare interventions such as liver transplantation produce improved health outcomes. Therefore, the high unemployment rate among liver transplant recipients is a poor health outcome that should be addressed. In this policy analysis, it is proposed that policy might affect this outcome. The problem of unemployment after liver transplantation is structured and policies affecting the problem are evaluated according to the validated criteria - Effectiveness, Equity, Efficiency, and Feasibility. A policy solution is proposed, evaluated, and ultimately recommended to effectively address the problem, to make healthcare coverage more equitable for liver transplant recipients, and to provide a more cost-effective healthcare coverage model during this time of healthcare crisis.^

A case study approach to estimating the burden of research misconduct in publicly funded medical research

The economic impact of research misconduct in medical research has been unexplored. While research misconduct in publicly funded medical research has increasingly been the object of discussion, public policy debate, government and institutional action, and scientific research, the costs of research misconduct have been unexamined. The author develops a model to estimate the per case cost of research misconduct, specifically the costs of fabrication, falsification, and plagiarism, in publicly funded medical research. Using the database of Research Misconduct Findings maintained by the Office of Research Integrity, Department of Health and Human Services, the model is used to estimate costs of research misconduct in public funded medical research among faculty during the period 2000-2005.^

A systematic review of economic evaluations for interventions of cardiovascular diseases

Background. Cardiovascular disease (CVD) exhibits the most striking public health significance due to its high prevalence and mortality as well as huge economic burdens all over the world, especially in industrialized countries. Major risk factors of CVDs have been the targets of population-wide prevention in the United States. Economic evaluations provide structured information in regard to the efficiency of resource utilization which can inform decisions of resource allocation. The main purpose of this review is to investigate the pattern of study design of economic evaluations for interventions of CVDs. ^ Methods. Primary journal articles published during 2003-2008 were systematically retrieved via relevant keywords from Medline, NHS Economic Evaluation Database (NHS EED) and EBSCO Academic Search Complete. Only full economic evaluations for narrowly defined CVD interventions were included for this review. The methodological data of interest were extracted from the eligible articles and reorganized in Microsoft Access database. Chi-square tests in SPSS were used to analyze the associations between pairs of categorical data. ^ Results. One hundred and twenty eligible articles were reviewed after two steps of literature selection with explicit inclusion and exclusion criteria. Descriptive statistics were reported regarding the evaluated interventions, outcome measures, unit costing and cost reports. The chi-square test of the association between prevention level of intervention and category of time horizon showed no statistical significance. The chi-square test showed that sponsor type was significantly associated with whether new or standard intervention being concluded as more cost effective. ^ Conclusions. Tertiary prevention and medication interventions are the major interests for economic evaluators. The majority of the evaluations were claimed from either a provider’s or a payer’s perspective. Almost all evaluations adopted gross costing strategy for unit cost data rather than micro costing. EQ-5D is the most commonly used instrument for subjective outcome measurement. More than half of the evaluations used decision analytic modeling techniques. The lack of consistency in study design standards in published evaluations appears in several aspects. Prevention level of intervention is not likely to be a factor for evaluators to decide whether to design an evaluation in a lifetime horizon or not. Published evaluations sponsored by industry are more likely to conclude that new intervention is more cost effective than standard intervention.^

Interim analysis of clinical trials: Simulation studies of fractional Brownian motion

Interim clinical trial monitoring procedures were motivated by ethical and economic considerations. Classical Brownian motion (Bm) techniques for statistical monitoring of clinical trials were widely used. Conditional power argument and α-spending function based boundary crossing probabilities are popular statistical hypothesis testing procedures under the assumption of Brownian motion. However, it is not rare that the assumptions of Brownian motion are only partially met for trial data. Therefore, I used a more generalized form of stochastic process, called fractional Brownian motion (fBm), to model the test statistics. Fractional Brownian motion does not hold Markov property and future observations depend not only on the present observations but also on the past ones. In this dissertation, we simulated a wide range of fBm data, e.g., H = 0.5 (that is, classical Bm) vs. 0.5< H <1, with treatment effects vs. without treatment effects. Then the performance of conditional power and boundary-crossing based interim analyses were compared by assuming that the data follow Bm or fBm. Our simulation study suggested that the conditional power or boundaries under fBm assumptions are generally higher than those under Bm assumptions when H > 0.5 and also matches better with the empirical results. ^

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.^

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.^

Children with acute leukemia: A comparison of outcomes and cost-effectiveness from allogeneic blood stem cell and bone marrow transplantation

The relative merits of PBSCT versus BMT for children with standard and high risk hematologic malignancies remain unclear. In a retrospective single center study, we compared allogeneic peripheral blood stem cell transplantation (PBSCT) (n=30) with bone marrow transplantation (BMT) (n=110) in children with acute leukemia. We studied recipients of HLA matched sibling stem cells, and of stem cells from alternative donors (HLA mismatched and/or unrelated) and determined whether sourcing the stem cells from PB or marrow affected engraftment, incidence of acute and chronic GvHD, and disease-free survival at 1 year. Our results show a modest reduction in time to engraftment from PB stem cells and no greater risk of GvHD, but illustrate that the severity of the underlying disease is by far the greatest determinant of 1 year survival. Patients in the BMT group had a higher treatment success rate and lower costs than the recipients of the PBSCT within the standard but not the high risk disease group, where the treatment success rate and the cumulative costs were lower in the PBSCT group compared to the BMT group. Our current incremental cost-effectiveness ratio and analysis of uncertainty suggest that allogeneic transplantation of bone marrow grafts was a more cost-effective treatment option compared to peripheral blood stem cells in patients with standard risk childhood acute leukemia disease. For high risk disease our data are less prescriptive, since the differences were more limited and the range of costs much larger. Neither option demonstrated a clear advantage from a cost-effectiveness standpoint.^

Understanding disparities in emergency department visits for asthma

Asthma is the most common chronic disorder in childhood, affecting an estimated 6.2 million children under 18 years (1). The purpose of this study was to look at individual- and community-level characteristics simultaneously to examine and explain the factors that contribute to the use of emergency department services by children 18 years old or less and to determine if there was an association between air quality and ED visits in the same population, from 2005-2007 in Houston/Harris County. Data were collected from the Houston Safety Net Hospital Emergency Department Use Study and the 2000 US Census. Bivariate and multivariate logistic regression models and mixed effects models were used to analyze data that was collected during the study period.^ There were 704,902 ED visits made by children 18 and younger, who were living in Houston from January 1, 2005 to December 31, 2007. Of those, 19,098 had a primary discharge diagnosis of asthma. Asthma ED visits varied by season, with proportions of ED visits for asthma highest from September-December. African-American children were 2.6 (95% CI, 2.43-2.66) times more likely to have an ED visit for asthma compared to White children. Poverty, single parent headed households, and younger age all a greater likelihood of having gone to the ED for asthma treatment. Compared to Whites living in lightly-monitored pollution areas, African-Americans and Hispanics living in heavily monitored areas were 1.15 (95% CI, 1.04-1.28) times more likely to have an ED visit for asthma.^ Race and poverty seem to account for a large portion of the disparities in ED use found among children. This was true even after accounting for multiple individual- and community-level variables. These results suggest that racial disparities in asthma continue to pose risks for African American children, and they point to the need for additional research into potential explanations and remedies. Programs to reduce inappropriate ED use must be sensitive to an array of complex socioeconomic issues within minority and income populations. ^

An analysis of the RightCare policy at Ben Taub General Hospital, Houston, Texas

Introduction. This study is a two-part evaluation of the RightCare policy, a policy implemented to reduce crowding at the Emergency Center (EC) at Ben Taub General Hospital in Houston, Harris County, Texas. This research includes an evaluation of the policy's impact on specific hospital measures, along with a description of the policy's demise from the point of view of hospital staff. Objective. The purpose of this study is two-fold: (1) To determine whether RightCare policy affected the level of crowding in the Emergency Center and (2) to identify the conditions that may have led to the policy's demise. Methods. For the policy impact portion of this research, hospital measures were collected from existing databases. Analysis included a pre-post comparative design in which the 12 months preceding the policy's implementation were compared with the 12 months following the policy's implementation. For the policy perception portion, employees were surveyed using an on-line questionnaire. Results. The results of the study are mixed. Some measures improved, including time spent on ambulance diversion and the proportion of those who left without being seen, while others did not, such as return visits and total length of stay. Employees generally supported the policy, but expressed concerns over insufficient training and funding. Conclusion. The RightCare policy was a good initial attempt to improve crowded conditions in the EC. The study showed that a clearer policy design, improved training, adequate staffing levels, and better communication would improve operational outcomes in the future.^

The influence of socioeconomic status on the relationship between diabetes and amputations: A systematic review of the literature

This paper synthesizes the current knowledge available regarding the impact of socioeconomic status on diabetes and amputations. In September 2009, searches in the OVID Medline and PubMed databases were performed using keywords associated with race/ethnicity, educational level, insurance status, veteran status, low income, diabetes, and lower extremity amputation. Articles published between 1996 and the search date were used. The pertinent articles were analyzed, summarized, and synthesized. ^ The majority of the articles agreed that African American, American Indian, and Latino minorities experience significantly higher rates of diabetes-related lower extremity amputation (LEA) when compared to whites. Few articles suggested that the disparity experienced by minorities and others of low SES was due to biology; most articles link it to a combination of lower income, lower educational attainment, uninsured or underinsured status, and a greater prevalence of detrimental health behaviors such as smoking. These, in turn, are linked to decreased knowledge of self-care, delayed health care seeking, delayed diagnoses and treatment, discrimination, and low quality health care. Interventions focused on patient education, established regimens of treatment, foot care, and control of diabetes have been shown to be effective, although none have lowered the rate of diabetes-related LEA to rates found in the general population.^

Cost analysis of opt-in consent procedures for the Texas statewide immunization information system, ImmTrac

Background. Childhood immunization programs have dramatically reduced the morbidity and mortality associated with vaccine-preventable diseases. Proper documentation of immunizations that have been administered is essential to prevent duplicate immunization of children. To help improve documentation, immunization information systems (IISs) have been developed. IISs are comprehensive repositories of immunization information for children residing within a geographic region. The two models for participation in an IIS are voluntary inclusion, or "opt-in," and voluntary exclusion, or "opt-out." In an opt-in system, consent must be obtained for each participant, conversely, in an opt-out IIS, all children are included unless procedures to exclude the child are completed. Consent requirements for participation vary by state; the Texas IIS, ImmTrac, is an opt-in system.^ Objectives. The specific objectives are to: (1) Evaluate the variance among the time and costs associated with collecting ImmTrac consent at public and private birthing hospitals in the Greater Houston area; (2) Estimate the total costs associated with collecting ImmTrac consent at selected public and private birthing hospitals in the Greater Houston area; (3) Describe the alternative opt-out process for collecting ImmTrac consent at birth and discuss the associated cost savings relative to an opt-in system.^ Methods. Existing time-motion studies (n=281) conducted between October, 2006 and August, 2007 at 8 birthing hospitals in the Greater Houston area were used to assess the time and costs associated with obtaining ImmTrac consent at birth. All data analyzed are deidentified and contain no personal information. Variations in time and costs at each location were assessed and total costs per child and costs per year were estimated. The cost of an alternative opt-out system was also calculated.^ Results. The median time required by birth registrars to complete consent procedures varied from 72-285 seconds per child. The annual costs associated with obtaining consent for 388,285 newborns in ImmTrac's opt-in consent process were estimated at $702,000. The corresponding costs of the proposed opt-out system were estimated to total $194,000 per year. ^ Conclusions. Substantial variation in the time and costs associated with completion of ImmTrac consent procedures were observed. Changing to an opt-out system for participation could represent significant cost savings. ^

Using small area estimation and geographic information systems technology to target health services for the uninsured

The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^