COMPARISON OF THE ORGANIZATIONAL STRUCTURES AND EFFECTIVENESS OF THE INVESTOR-OWNED AND VOLUNTARY MULTIHOSPITAL SECTORS

Objectives. The central objective of this study was to systematically examine the internal structure of multihospital systems, determining the management principles used and the performance levels achieved in medical care and administrative areas.^ The Universe. The study universe consisted of short-term general American hospitals owned and operated by multihospital corporations. Corporations compared were the investor-owned (for-profit) and the voluntary multihospital systems. The individual hospital was the unit of analysis for the study.^ Theoretical Considerations. The contingency theory, using selected aspects of the classical and human relations schools of thought, seemed well suited to describe multihospital organization and was used in this research.^ The Study Hypotheses. The main null hypotheses generated were that there are no significant differences between the voluntary and the investor-owned multihospital sectors in their (1) hospital structures and (2) patient care and administrative performance levels.^ The Sample. A stratified random sample of 212 hospitals owned by multihospital systems was selected to equally represent the two study sectors. Of the sampled hospitals approached, 90.1% responded.^ The Analysis. Sixteen scales were constructed in conjunction with 16 structural variables developed from the major questions and sub-items of the questionnaire. This was followed by analysis of an additional 7 structural and 24 effectiveness (performance) measures, using frequency distributions. Finally, summary statistics and statistical testing for each variable and sub-items were completed and recorded in 38 tables.^ Study Findings. While it has been argued that there are great differences between the two sectors, this study found that with a few exceptions the null hypotheses of no difference in organizational and operational characteristics of non-profit and for-profit hospitals was accepted. However, there were several significant differences found in the structural variables: functional specialization, and autonomy were significantly higher in the voluntary sector. Only centralization was significantly different in the investor owned. Among the effectiveness measures, occupancy rate, cost of data processing, total manhours worked, F.T.E. ratios, and personnel per occupied bed were significantly higher in the voluntary sector. The findings indicated that both voluntary and for-profit systems were converging toward a common hierarchical corporate management approach. Factors of size and management style may be better descriptors to characterize a specific multihospital group than its profit or nonprofit status. (Abstract shortened with permission of author.) ^

Statistical Methods for Differential Expressions of Genes Detected in Multiple-Condition Experiment of Microarray

Most studies of differential gene-expressions have been conducted between two given conditions. The two-condition experimental (TCE) approach is simple in that all genes detected display a common differential expression pattern responsive to a common two-condition difference. Therefore, the genes that are differentially expressed under the other conditions other than the given two conditions are undetectable with the TCE approach. In order to address the problem, we propose a new approach called multiple-condition experiment (MCE) without replication and develop corresponding statistical methods including inference of pairs of conditions for genes, new t-statistics, and a generalized multiple-testing method for any multiple-testing procedure via a control parameter C. We applied these statistical methods to analyze our real MCE data from breast cancer cell lines and found that 85 percent of gene-expression variations were caused by genotypic effects and genotype-ANAX1 overexpression interactions, which agrees well with our expected results. We also applied our methods to the adenoma dataset of Notterman et al. and identified 93 differentially expressed genes that could not be found in TCE. The MCE approach is a conceptual breakthrough in many aspects: (a) many conditions of interests can be conducted simultaneously; (b) study of association between differential expressions of genes and conditions becomes easy; (c) it can provide more precise information for molecular classification and diagnosis of tumors; (d) it can save lot of experimental resources and time for investigators.^