HUMAN PROPHASE CHROMOSOME UNIQUE BAND SEQUENCES; DEFINITION, CHARACTERIZATION, AND APPLICATION (CYTOGENETICS, IMAGE PROCESSING)

Extensive experience with the analysis of human prophase chromosomes and studies into the complexity of prophase GTG-banding patterns have suggested that at least some prophase chromosomal segments can be accurately identified and characterized independently of the morphology of the chromosome as a whole. In this dissertation the feasibility of identifying and analyzing specified prophase chromosome segments was thus investigated as an alternative approach to prophase chromosome analysis based on whole chromosome recognition. Through the use of prophase idiograms at the 850-band-stage (FRANCKE, 1981) and a comparison system based on the calculation of cross-correlation coefficients between idiogram profiles, we have demonstrated that it is possible to divide the 24 human prophase idiograms into a set of 94 unique band sequences. Each unique band sequence has a banding pattern that is recognizable and distinct from any other non-homologous chromosome portion.^ Using chromosomes 11p and 16 thru 22 to demonstrate unique band sequence integrity at the chromosome level, we found that prophase chromosome banding pattern variation can be compensated for and that a set of unique band sequences very similar to those at the idiogram level can be identified on actual chromosomes.^ The use of a unique band sequence approach in prophase chromosome analysis is expected to increase efficiency and sensitivity through more effective use of available banding information. The use of a unique band sequence approach to prophase chromosome analysis is discussed both at the routine level by cytogeneticists and at an image processing level with a semi-automated approach to prophase chromosome analysis. ^

Assessing the impact of electronic health record technology adoption on hospital labor efficiency

Information technology (IT) in the hospital organization is fast becoming a key asset, particularly in light of recent reform legislation in the United States calling for expanding the role of IT in our health care system. Future payment reductions to hospitals included in current health reform are based on expected improvements in hospital operating efficiency. Since over half of hospital expenses are for labor, improved efficiency in use of labor resources can be critical in meeting this challenge. Policy makers have touted the value of IT investments to improve efficiency in response to payment reductions. ^ This study was the first to directly examine the relationship between electronic health record (EHR) technology and staffing efficiency in hospitals. As the hospital has a myriad of outputs for inpatient and outpatient care, efficiency was measured using an industry standard performance metric – full time equivalent employees per adjusted occupied bed (FTE/AOB). Three hypotheses were tested in this study.^ To operationalize EHR technology adoption, we developed three constructs to model adoption, each of which was tested by separate hypotheses. The first hypothesis that a larger number of EHR applications used by a hospital would be associated with greater staffing efficiency (or lower values of FTE/AOB) was not accepted. Association between staffing efficiency and specific EHR applications was the second hypothesis tested and accepted with some applications showing significant impacts on observed values for FTE/AOB. Finally, the hypothesis that the longer an EHR application was used in a hospital would be associated with greater labor efficiency was not accepted as the model showed few statistically significant relationships to FTE/AOB performance. Generally, there does not appear a strong relationship between EHR usage and improved labor efficiency in hospitals.^ While returns on investment from EHR usage may not come from labor efficiencies, they may be better sought using measures of quality, contribution to an efficient and effective local health care system, and improved customer satisfaction through greater patient throughput.^

Decomposition of $\rm R\times C$ contingency table chi -square: Application to binned DNA fragment size data and population structure analysis

The purpose of this research is to develop a new statistical method to determine the minimum set of rows (R) in a R x C contingency table of discrete data that explains the dependence of observations. The statistical power of the method will be empirically determined by computer simulation to judge its efficiency over the presently existing methods. The method will be applied to data on DNA fragment length variation at six VNTR loci in over 72 populations from five major racial groups of human (total sample size is over 15,000 individuals; each sample having at least 50 individuals). DNA fragment lengths grouped in bins will form the basis of studying inter-population DNA variation within the racial groups are significant, will provide a rigorous re-binning procedure for forensic computation of DNA profile frequencies that takes into account intra-racial DNA variation among populations. ^