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.^

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.

Investigation of arterial spin labeling MRI for quantitative cerebral blood flow measurement

Arterial spin labeling (ASL) is a technique for noninvasively measuring cerebral perfusion using magnetic resonance imaging. Clinical applications of ASL include functional activation studies, evaluation of the effect of pharmaceuticals on perfusion, and assessment of cerebrovascular disease, stroke, and brain tumor. The use of ASL in the clinic has been limited by poor image quality when large anatomic coverage is required and the time required for data acquisition and processing. This research sought to address these difficulties by optimizing the ASL acquisition and processing schemes. To improve data acquisition, optimal acquisition parameters were determined through simulations, phantom studies and in vivo measurements. The scan time for ASL data acquisition was limited to fifteen minutes to reduce potential subject motion. A processing scheme was implemented that rapidly produced regional cerebral blood flow (rCBF) maps with minimal user input. To provide a measure of the precision of the rCBF values produced by ASL, bootstrap analysis was performed on a representative data set. The bootstrap analysis of single gray and white matter voxels yielded a coefficient of variation of 6.7% and 29% respectively, implying that the calculated rCBF value is far more precise for gray matter than white matter. Additionally, bootstrap analysis was performed to investigate the sensitivity of the rCBF data to the input parameters and provide a quantitative comparison of several existing perfusion models. This study guided the selection of the optimum perfusion quantification model for further experiments. The optimized ASL acquisition and processing schemes were evaluated with two ASL acquisitions on each of five normal subjects. The gray-to-white matter rCBF ratios for nine of the ten acquisitions were within ±10% of 2.6 and none were statistically different from 2.6, the typical ratio produced by a variety of quantitative perfusion techniques. Overall, this work produced an ASL data acquisition and processing technique for quantitative perfusion and functional activation studies, while revealing the limitations of the technique through bootstrap analysis. ^

Airliner cabin air quality exposure assessment

The airliner cabin environment and its effects on occupant health have not been fully characterized. This dissertation is: (1) A review of airliner environmental control systems (ECSs) that modulate the ventilation, temperature, relative humidity (RH), and barometric pressure (PB) of the cabin environment---variables related to occupant comfort and health. (2) A review and assessment of the methods and findings of key cabin air quality (CAQ) investigations. Several significant deficiencies impede the drawing of inferences about CAQ, e.g., lack of detail about investigative methods, differences in methods between investigations, limited assessment of CAQ variables, small sample sizes, and technological deficiencies of data collection. (3) A comprehensive evaluation of the methods used in the subsequent NIOSH-FAA Airliner CAQ Exposure Assessment Feasibility Study (STUDY) in which this author participated. A number of problems were identified which limit the usefulness of the data. (4) An analysis of the reliable 10-flight STUDY data. Univariate and multivariate methods applied to CO2 (a surrogate for air contaminants), temperature, RH, and PB, in association with percent passenger load, ventilation system, flight duration, airliner body type, and measurement location within the cabin, revealed neither the measured values nor their variability exceeded established health-based exposure limits. Regression analyses suggest CO2, temperature, and RH were affected by percent passenger load. In-flight measurements of CO2 and RH were relatively independent of ventilation system type or flight duration. Cabin temperature was associated with percent passenger load, ventilation system type, and flight duration. (5) A synthesis of the implications of the airliner ECS and cabin O2 environment on occupant health. A model was developed to predict consequences of the airliner cabin pressure altitude 8,000 ft limit and resulting model-estimated PO2 on cardiopulmonary status. Based on the PB, altitude, and environmental data derived from the 10 STUDY flights, the predicted PaO2 of adults with COPD, or elderly adults with or without COPD, breathing ambient cabin air could be < 55 mm Hg (SaO2 < 88%). Reduction in cabin PB found in the STUDY flights could aggravate various medical conditions and require the use of in-flight supplemental O2. ^

Interrelationships between the structural and functional aspects of social relationships, comorbidity and health related quality of life in breast cancer survivors

It is widely acknowledged in theoretical and empirical literature that social relationships, comprising of structural measures (social networks) and functional measures (perceived social support) have an undeniable effect on health outcomes. However, the actual mechanism of this effect has yet to be clearly understood or explicated. In addition, comorbidity is found to adversely affect social relationships and health related quality of life (a valued outcome measure in cancer patients and survivors). ^ This cross sectional study uses selected baseline data (N=3088) from the Women's Healthy Eating and Living (WHEL) study. Lisrel 8.72 was used for the latent variable structural equation modeling. Due to the ordinal nature of the data, Weighted Least Squares (WLS) method of estimation using Asymptotic Distribution Free covariance matrices was chosen for this analysis. The primary exogenous predictor variables are Social Networks and Comorbidity; Perceived Social Support is the endogenous predictor variable. Three dimensions of HRQoL, physical, mental and satisfaction with current quality of life were the outcome variables. ^ This study hypothesizes and tests the mechanism and pathways between comorbidity, social relationships and HRQoL using latent variable structural equation modeling. After testing the measurement models of social networks and perceived social support, a structural model hypothesizing associations between the latent exogenous and endogenous variables was tested. The results of the study after listwise deletion (N=2131) mostly confirmed the hypothesized relationships (TLI, CFI >0.95, RMSEA = 0.05, p=0.15). Comorbidity was adversely associated with all three HRQoL outcomes. Strong ties were negatively associated with perceived social support; social network had a strong positive association with perceived social support, which served as a mediator between social networks and HRQoL. Mental health quality of life was the most adversely affected by the predictor variables. ^ This study is a preliminary look at the integration of structural and functional measures of social relationships, comorbidity and three HRQoL indicators using LVSEM. Developing stronger social networks and forming supportive relationships is beneficial for health outcomes such as HRQoL of cancer survivors. Thus, the medical community treating cancer survivors as well as the survivor's social networks need to be informed and cognizant of these possible relationships. ^

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.^

Cataract surgery in cancer patients and its impact on quality of life as measured by the National Eye Institute Visual Functioning Questionnaire - 25 (NEI-VFQ-25)

Purpose. The measurement of quality of life has become an important topic in healthcare and in the allocation of limited healthcare resources. Improving the quality of life (QOL) in cancer patients is paramount. Cataract removal and lens implantation appears to improve patient well-being of cancer patients, though a formal measurement has never been published in the US literature. In this current study, National Eye Institute Visual Functioning Questionnaire (NEI-VFQ-25), a validated vision quality of life metric, was used to study the change in vision-related quality of life in cancer patients who underwent cataract extraction with intraocular lens implantation. ^ Methods. Under an IRB approved protocol, cancer patients who underwent cataract surgery with intraocular lens implantation (by a single surgeon) from December 2008 to March 2011, and who had completed a pre- and postoperative NEI-VFQ-25 were retrospectively reviewed. Post-operative data was collected at their routine 4-6 week post-op visit. Patients' demographics, cancer history, their pre and postoperative ocular examinations, visual acuities, and NEI-VFQ-25 with twelve components were included in the evaluation. The responses were evaluated using the Student t test, Spearman correlation and Wilcoxon signed rank test. ^ Results. 63 cases of cataract surgery (from 54 patients) from the MD Anderson Cancer Center were included in the study. Cancer patients had a significant improvement in the visual acuity (P<0.0001) postoperatively, along with a significant increase in vision-related quality of life (P<0.0001). Patients also had a statistically significant improvement in ten of the twelve subcategories which are addressed in the NEI-VFQ-25. ^ Conclusions. In our study, cataract extraction and intraocular implantation showed a significant impact on the vision-related quality of life in cancer patients. Although this study includes a small sample size, it serves as a positive pilot study to evaluate and quantify the impact of a surgical intervention on QOL in cancer patients and may help to design a larger study to measure vision related QOL per dollar spent for health care cost in cancer patients.^

Black/white disparities in infant mortality rates in the U.S.: A quality of care perspective

The infant mortality rate for non-Hispanic Black infants in the U.S. is 13.63 deaths per 1,000 live births while the IMR for non-Hispanic White persons in the U.S. is 5.76 deaths per 1,000 live births. Black women are 2 times as likely as White women to deliver preterm infants and Black women are 2 times as likely as White women to deliver low birth weight infants (weighing less than 2,500 grams at birth). Differential underlying risk factors among mothers of different racial/ethnic groups for delivering pre-term and low birth weight infants have been historically accepted as the cause of racial disparities in IMRs. However, differential underlying risk status may not be the only major causative factor. Differential or unequal access to and provision of care is widely speculated to be a leading contributing factor to the wide racial disparity in infant mortality.2 This paper conducts a systematic review of existing literature investigating racial disparities in obstetrical care provided by healthcare practitioners to evaluate whether inequities in healthcare services provided to pregnant mothers and their neonates exist. The search terms "racial disparities obstetrical care," "racial differences quality of prenatal care," and "infant mortality racial disparities" were entered into the EBSCO Medline, Ovid Medline, PubMed, and Academic Search Complete databases, and articles between years 1990–2011 were selected for abstract review. The only articles included were those that used statistical methods to assess whether racial inequalities were present in the obstetrical services provided to pregnant women. My literature search returned 5 articles. Four of the five studies yielded significant racial differences in obstetrical care. However, the one study that used a large, nationally representative valid sample did not represent significant differences. Thus, this review provides initial evidence for racial disparities in obstetrical care, but concludes that more studies are needed in this area. Not all of the studies reviewed were consistent in the use and measurement of services, and not all studies were significant. The policy and public health implications of possible racial disparities in obstetrical care include the need to develop standard of care protocols for ALL obstetrical patients across the United States to minimize and/or eliminate the inequities and differences in obstetrical services provided.^

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.